From 0463aa9fc3ef02d30d7177c0065cd4b7d36a39f7 Mon Sep 17 00:00:00 2001 From: Hans Date: Mon, 27 Oct 2025 14:46:54 +0800 Subject: [PATCH 01/33] Disable build flatc for tvOS or visionOS (#26380) ### Description To fix build error. ### Motivation and Context Currently will build fail. ``` CMake Error at /Users/runner/work/onnxruntime-custom/onnxruntime-custom/tvOS/RelWithDebInfo/_deps/flatbuffers-src/CMakeLists.txt:636 (install): -- CMAKE_CXX_FLAGS: -DNDEBUG -Wp,-D_FORTIFY_SOURCE=2 -Wp,-D_GLIBCXX_ASSERTIONS -fstack-protector-strong -O3 -pipe -g -ffunction-sections -fdata-sections -fvisibility=hidden -fvisibility-inlines-hidden -DCPUINFO_SUPPORTED install TARGETS given no BUNDLE DESTINATION for MACOSX_BUNDLE executable target "flatc". ``` --- cmake/external/onnxruntime_external_deps.cmake | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/cmake/external/onnxruntime_external_deps.cmake b/cmake/external/onnxruntime_external_deps.cmake index 603d578e696ef..b02d0e82d9ee4 100644 --- a/cmake/external/onnxruntime_external_deps.cmake +++ b/cmake/external/onnxruntime_external_deps.cmake @@ -440,7 +440,7 @@ if(onnxruntime_USE_VCPKG) find_package(flatbuffers REQUIRED) else() # We do not need to build flatc for iOS or Android Cross Compile -if (CMAKE_SYSTEM_NAME STREQUAL "iOS" OR CMAKE_SYSTEM_NAME STREQUAL "Android" OR CMAKE_SYSTEM_NAME STREQUAL "Emscripten") +if (CMAKE_SYSTEM_NAME STREQUAL "iOS" OR CMAKE_SYSTEM_NAME STREQUAL "tvOS" OR CMAKE_SYSTEM_NAME STREQUAL "visionOS" OR CMAKE_SYSTEM_NAME STREQUAL "Android" OR CMAKE_SYSTEM_NAME STREQUAL "Emscripten") set(FLATBUFFERS_BUILD_FLATC OFF CACHE BOOL "FLATBUFFERS_BUILD_FLATC" FORCE) endif() set(FLATBUFFERS_BUILD_TESTS OFF CACHE BOOL "FLATBUFFERS_BUILD_TESTS" FORCE) From 5568c3afa6071ab4c0fdd998853a01cf3d5aa3e4 Mon Sep 17 00:00:00 2001 From: keshavv27 <165012837+keshavv27@users.noreply.github.com> Date: Mon, 27 Oct 2025 09:49:00 -0700 Subject: [PATCH 02/33] [NV TRT RTX EP] Package CUDA Runtime and TRT RTX with NV TensorRT RTX EP python wheel (#26115) ### Description - CUDA Runtime added as a dependency for NV EP python wheel - TRT RTX dlls and license copied to wheel as public wheels for TRT RTX are currently unavailable - Use onnxruntime.preload_dlls() to load CUDA Runtime DLL - python package name for NV EP is onnxruntime-trt-rtx ### Motivation and Context Enables out-of-the-box usage for the NV TensorRT RTX EP python wheel @gaugarg-nv @thevishalagarwal @gedoensmax @ishwar-raut1 --- cmake/onnxruntime_python.cmake | 20 ++++++++++++++++++++ setup.py | 23 +++++++++++++++++++++-- tools/ci_build/build.py | 4 ++++ 3 files changed, 45 insertions(+), 2 deletions(-) diff --git a/cmake/onnxruntime_python.cmake b/cmake/onnxruntime_python.cmake index ff49be1ab3d6b..e449bb107e77b 100644 --- a/cmake/onnxruntime_python.cmake +++ b/cmake/onnxruntime_python.cmake @@ -962,13 +962,33 @@ if (onnxruntime_USE_TENSORRT) endif() if (onnxruntime_USE_NV) + if (WIN32 OR ${CMAKE_SYSTEM_NAME} STREQUAL "Linux") + file(GLOB NV_LIB_FILES LIST_DIRECTORIES false "${TENSORRT_RTX_ROOT}/lib/tensorrt_*.dll" + "${TENSORRT_RTX_ROOT}/bin/tensorrt_*.dll" + "${TENSORRT_RTX_ROOT}/lib/libtensorrt_*.so" + "${TENSORRT_RTX_ROOT}/bin/libtensorrt_*.so") + message(STATUS "NV lib files: " ${NV_LIB_FILES}) + endif() add_custom_command( TARGET onnxruntime_pybind11_state POST_BUILD COMMAND ${CMAKE_COMMAND} -E copy + ${NV_LIB_FILES} $ $ $/onnxruntime/capi/ ) + if (EXISTS "${TENSORRT_RTX_ROOT}/doc/LICENSE.txt") + add_custom_command( + TARGET onnxruntime_pybind11_state POST_BUILD + COMMAND ${CMAKE_COMMAND} -E copy "${TENSORRT_RTX_ROOT}/doc/LICENSE.txt" $/onnxruntime/TRT_RTX_LICENSE.txt + ) + endif() + if (EXISTS "${TENSORRT_RTX_ROOT}/doc/Acknowledgements.txt") + add_custom_command( + TARGET onnxruntime_pybind11_state POST_BUILD + COMMAND ${CMAKE_COMMAND} -E copy "${TENSORRT_RTX_ROOT}/doc/Acknowledgements.txt" $/onnxruntime/TRT_RTX_Acknowledgements.txt + ) + endif() endif() if (onnxruntime_USE_MIGRAPHX) diff --git a/setup.py b/setup.py index 6bfb53329f319..a679b6bfcee0f 100644 --- a/setup.py +++ b/setup.py @@ -374,6 +374,10 @@ def finalize_options(self): "libHtpPrepare.so", ] dl_libs.extend(qnn_deps) + # NV TensorRT RTX + nv_tensorrt_rtx_deps = ["libtensorrt_rtx.so", "libtensorrt_onnxparser_rtx.so"] + dl_libs.extend(nv_tensorrt_rtx_deps) + libs.extend(nv_tensorrt_rtx_deps) if nightly_build: libs.extend(["libonnxruntime_pywrapper.so"]) elif platform.system() == "Darwin": @@ -454,6 +458,9 @@ def finalize_options(self): "migraphx_tf.dll", ] libs.extend(migraphx_deps) + # NV TensorRT RTX Libs + nv_tensorrt_rtx_deps = ["tensorrt_onnxparser_rtx_*.dll", "tensorrt_rtx_*.dll"] + libs.extend(nv_tensorrt_rtx_deps) if is_manylinux: if is_openvino: @@ -496,8 +503,15 @@ def finalize_options(self): examples_names = ["mul_1.onnx", "logreg_iris.onnx", "sigmoid.onnx"] examples = [path.join("datasets", x) for x in examples_names] -# Extra files such as EULA and ThirdPartyNotices (and Qualcomm License, only for QNN release packages) -extra = ["LICENSE", "ThirdPartyNotices.txt", "Privacy.md", "Qualcomm_LICENSE.pdf"] +# Extra files such as EULA and ThirdPartyNotices (and Qualcomm License, only for QNN release packages)(and TensorRT RTX License and Acknowledgements for TRT RTX EP) +extra = [ + "LICENSE", + "ThirdPartyNotices.txt", + "Privacy.md", + "Qualcomm_LICENSE.pdf", + "TRT_RTX_LICENSE.txt", + "TRT_RTX_Acknowledgements.txt", +] # Description readme_file = "docs/python/ReadMeOV.rst" if is_openvino else "docs/python/README.rst" @@ -764,6 +778,11 @@ def reformat_run_count(count_str): with open(requirements_path) as f: install_requires = f.read().splitlines() +# Adding CUDA Runtime as dependency for NV TensorRT RTX python wheel +if package_name == "onnxruntime-trt-rtx": + install_requires.append("nvidia-cuda-runtime-cu12~=12.0") + cuda_version = parse_arg_remove_string(sys.argv, "--cuda_version=") + def save_build_and_package_info(package_name, version_number, cuda_version, rocm_version, qnn_version): sys.path.append(path.join(path.dirname(__file__), "onnxruntime", "python")) diff --git a/tools/ci_build/build.py b/tools/ci_build/build.py index 9447dcc2d0baf..c316b0db6a1b0 100644 --- a/tools/ci_build/build.py +++ b/tools/ci_build/build.py @@ -2005,6 +2005,10 @@ def build_python_wheel( args.append(f"--qnn_version={qnn_version}") elif use_azure: args.append("--use_azure") + elif wheel_name_suffix == "trt-rtx": + cuda_version = cuda_version or parse_cuda_version_from_json(cuda_home) + if cuda_version: + args.append(f"--cuda_version={cuda_version}") run_subprocess(args, cwd=cwd) From fdaf8b642d8632ed15f7461bdcec436f486835c8 Mon Sep 17 00:00:00 2001 From: Dmitri Smirnov Date: Mon, 27 Oct 2025 10:41:54 -0700 Subject: [PATCH 03/33] Make onnxruntime_benchmark run (#26404) ### Description Picked other models instead of those removed. ### Motivation and Context Measure --- onnxruntime/test/onnx/microbenchmark/main.cc | 3 ++- onnxruntime/test/onnx/microbenchmark/modeltest.cc | 7 ++++--- 2 files changed, 6 insertions(+), 4 deletions(-) diff --git a/onnxruntime/test/onnx/microbenchmark/main.cc b/onnxruntime/test/onnx/microbenchmark/main.cc index 24d02caa96aa1..b356dda740a31 100644 --- a/onnxruntime/test/onnx/microbenchmark/main.cc +++ b/onnxruntime/test/onnx/microbenchmark/main.cc @@ -39,10 +39,11 @@ BENCHMARK(BM_CPUAllocator) ->Arg(sizeof(Tensor)); static void BM_ResolveGraph(benchmark::State& state) { + constexpr const ORTCHAR_T* model_path = ORT_TSTR("transformers/test_data/models/gpt2_embedlayer_exp.onnx"); std::shared_ptr model_copy; auto logger = env->GetLoggingManager()->CreateLogger("test"); auto st = - onnxruntime::Model::Load(ORT_TSTR("../models/opset8/test_tiny_yolov2/model.onnx"), model_copy, nullptr, *logger); + onnxruntime::Model::Load(model_path, model_copy, nullptr, *logger); if (!st.IsOK()) { ::std::cerr << "Parse model failed: " << st.ErrorMessage().c_str() << ::std::endl; abort(); diff --git a/onnxruntime/test/onnx/microbenchmark/modeltest.cc b/onnxruntime/test/onnx/microbenchmark/modeltest.cc index 6305ce2472916..bac070a7186fe 100644 --- a/onnxruntime/test/onnx/microbenchmark/modeltest.cc +++ b/onnxruntime/test/onnx/microbenchmark/modeltest.cc @@ -14,11 +14,12 @@ extern OrtEnv* env; extern const OrtApi* g_ort; static void BM_LoadModel(benchmark::State& state) { + constexpr const ORTCHAR_T* model_path = ORT_TSTR("transformers/test_data/models/gpt2_embedlayer_exp.onnx"); auto logger = env->GetLoggingManager()->CreateLogger("test"); for (auto _ : state) { std::shared_ptr yolomodel; auto st = - onnxruntime::Model::Load(ORT_TSTR("../models/opset8/test_tiny_yolov2/model.onnx"), yolomodel, nullptr, *logger); + onnxruntime::Model::Load(model_path, yolomodel, nullptr, *logger); if (!st.IsOK()) { state.SkipWithError(st.ErrorMessage().c_str()); break; @@ -39,7 +40,7 @@ BENCHMARK(BM_LoadModel); #ifdef USE_CUDA static void BM_CreateSession_WithGPU(benchmark::State& state) { - const ORTCHAR_T* model_path = ORT_TSTR("../models/opset8/test_bvlc_alexnet/model.onnx"); + const ORTCHAR_T* model_path = ORT_TSTR("transformers/test_data/models/gpt2_embedlayer_exp.onnx"); OrtSessionOptions* session_option; ORT_BREAK_ON_ERROR(g_ort->CreateSessionOptions(&session_option)); ORT_BREAK_ON_ERROR(OrtSessionOptionsAppendExecutionProvider_CUDA(session_option, 0)); @@ -56,7 +57,7 @@ BENCHMARK(BM_CreateSession_WithGPU); #endif static void BM_CreateSession(benchmark::State& state) { - const ORTCHAR_T* model_path = ORT_TSTR("../models/opset8/test_bvlc_alexnet/model.onnx"); + const ORTCHAR_T* model_path = ORT_TSTR("transformers/test_data/models/gpt2_embedlayer_exp.onnx"); OrtSessionOptions* session_option; ORT_BREAK_ON_ERROR(g_ort->CreateSessionOptions(&session_option)); for (auto _ : state) { From 6e19cbde5c0ba84064439ca737d8968a4f64d17a Mon Sep 17 00:00:00 2001 From: Changming Sun Date: Mon, 27 Oct 2025 11:27:34 -0700 Subject: [PATCH 04/33] Upgrade cpuinfo (#26405) Upgrade cpuinfo to a newer version to maintain it up to date. --- cmake/deps.txt | 2 +- cmake/vcpkg-ports/cpuinfo/portfile.cmake | 4 ++-- cmake/vcpkg-ports/cpuinfo/vcpkg.json | 4 ++-- 3 files changed, 5 insertions(+), 5 deletions(-) diff --git a/cmake/deps.txt b/cmake/deps.txt index bf76753c1b3c0..22c793705ddeb 100644 --- a/cmake/deps.txt +++ b/cmake/deps.txt @@ -47,7 +47,7 @@ protoc_mac_universal;https://github.com/protocolbuffers/protobuf/releases/downlo psimd;https://github.com/Maratyszcza/psimd/archive/072586a71b55b7f8c584153d223e95687148a900.zip;1f5454b01f06f9656b77e4a5e2e31d7422487013 pthreadpool;https://github.com/google/pthreadpool/archive/dcc9f28589066af0dbd4555579281230abbf74dd.zip;533a77943203ef15ca608bcd9dbe2c94da7451d2 pybind11;https://github.com/pybind/pybind11/archive/refs/tags/v2.13.6.zip;f780292da9db273c8ef06ccf5fd4b623624143e9 -pytorch_cpuinfo;https://github.com/pytorch/cpuinfo/archive/de0ce7c7251372892e53ce9bc891750d2c9a4fd8.zip;c45b8d3619b9bccbd26dc5f657959aee38b18b7a +pytorch_cpuinfo;https://github.com/pytorch/cpuinfo/archive/877328f188a3c7d1fa855871a278eb48d530c4c0.zip;9152d4bf6b8bde9f19b116de3bd8a745097ed9df re2;https://github.com/google/re2/archive/refs/tags/2024-07-02.zip;646e1728269cde7fcef990bf4a8e87b047882e88 safeint;https://github.com/dcleblanc/SafeInt/archive/refs/tags/3.0.28.zip;23f252040ff6cb9f1fd18575b32fa8fb5928daac tensorboard;https://github.com/tensorflow/tensorboard/archive/373eb09e4c5d2b3cc2493f0949dc4be6b6a45e81.zip;67b833913605a4f3f499894ab11528a702c2b381 diff --git a/cmake/vcpkg-ports/cpuinfo/portfile.cmake b/cmake/vcpkg-ports/cpuinfo/portfile.cmake index eeb0007195ca3..80192840ee9b0 100644 --- a/cmake/vcpkg-ports/cpuinfo/portfile.cmake +++ b/cmake/vcpkg-ports/cpuinfo/portfile.cmake @@ -6,8 +6,8 @@ endif() vcpkg_from_github( OUT_SOURCE_PATH SOURCE_PATH REPO pytorch/cpuinfo - REF de0ce7c7251372892e53ce9bc891750d2c9a4fd8 - SHA512 0fde9210b700d2648d37c8deeb0d5c0d007d8ca5689578dd3bce4c460886b20d7649f0194d2ea06b02238fe9d4f06193599ec3ab5cafb19f1f860b00404264fa + REF 877328f188a3c7d1fa855871a278eb48d530c4c0 + SHA512 b6d5a9ce9996eee3b2f09f39115f7ae178fe4d4814cc35b049a59d04a82228e268aa52d073c307ccb56a427428622940e1c77f004c99851dfca0d3a5d803658b HEAD_REF master PATCHES patch_cpuinfo_h_for_arm64ec.patch diff --git a/cmake/vcpkg-ports/cpuinfo/vcpkg.json b/cmake/vcpkg-ports/cpuinfo/vcpkg.json index ce93591dba5ac..f1ccda72679b1 100644 --- a/cmake/vcpkg-ports/cpuinfo/vcpkg.json +++ b/cmake/vcpkg-ports/cpuinfo/vcpkg.json @@ -1,7 +1,7 @@ { "name": "cpuinfo", - "version-date": "2024-12-09", - "port-version": 3, + "version-date": "2025-10-23", + "port-version": 4, "description": "CPU INFOrmation library (x86/x86-64/ARM/ARM64, Linux/Windows/Android/macOS/iOS)", "homepage": "https://github.com/pytorch/cpuinfo", "license": "BSD-2-Clause", From 954bb7bc0112f28a90fbe330af4e682024d47991 Mon Sep 17 00:00:00 2001 From: Yulong Wang <7679871+fs-eire@users.noreply.github.com> Date: Mon, 27 Oct 2025 12:09:58 -0700 Subject: [PATCH 05/33] [WebGPU] allow async shader compilation (#25941) ### Description Reduce the time blocked waiting for the shader to be compiled. ### Motivation and Context Try to optimize the responsiveness of the application when running ort-web in main thread. See #25882 --- .../core/providers/webgpu/program_manager.cc | 35 ++++++++++++++----- .../core/providers/webgpu/program_manager.h | 6 ++-- .../core/providers/webgpu/webgpu_context.cc | 2 +- 3 files changed, 31 insertions(+), 12 deletions(-) diff --git a/onnxruntime/core/providers/webgpu/program_manager.cc b/onnxruntime/core/providers/webgpu/program_manager.cc index aa0db6ad06301..e96a7cbf1af04 100644 --- a/onnxruntime/core/providers/webgpu/program_manager.cc +++ b/onnxruntime/core/providers/webgpu/program_manager.cc @@ -10,6 +10,7 @@ #include "core/providers/webgpu/program_manager.h" #include "core/providers/webgpu/shader_helper.h" +#include "core/providers/webgpu/webgpu_context.h" namespace onnxruntime { namespace webgpu { @@ -22,7 +23,7 @@ ProgramArtifact::ProgramArtifact(const ProgramBase& program, wgpu::ComputePipeli Status ProgramManager::NormalizeDispatchGroupSize(uint32_t& x, uint32_t& y, uint32_t& z) const { ORT_RETURN_IF(x == 0 || y == 0 || z == 0, "Invalid dispatch group size (", x, ", ", y, ", ", z, ")"); - auto limit_per_dimension = limits_.maxComputeWorkgroupsPerDimension; + auto limit_per_dimension = webgpu_context_.DeviceLimits().maxComputeWorkgroupsPerDimension; if (x > limit_per_dimension || y > limit_per_dimension || z > limit_per_dimension) { double size = static_cast(x) * static_cast(y) * static_cast(z); double dispatch_avg = std::ceil(std::sqrt(size)); @@ -39,7 +40,7 @@ Status ProgramManager::NormalizeDispatchGroupSize(uint32_t& x, uint32_t& y, uint } Status ProgramManager::CalculateSegmentsForInputsAndOutputs(ProgramBase& program) { - const uint64_t maxStorageBufferBindingSize = limits_.maxStorageBufferBindingSize; + const uint64_t maxStorageBufferBindingSize = webgpu_context_.DeviceLimits().maxStorageBufferBindingSize; // Inputs for (size_t i = 0; i < program.Inputs().size(); ++i) { @@ -70,10 +71,11 @@ Status ProgramManager::Build(const ProgramBase& program, uint32_t normalized_dispatch_z, wgpu::ComputePipeline& compute_pipeline, std::vector& shape_uniform_ranks) const { + auto& device = webgpu_context_.Device(); ShaderHelper shader_helper{program, program_metadata, - device_, - limits_, + device, + webgpu_context_.DeviceLimits(), normalized_dispatch_x, normalized_dispatch_y, normalized_dispatch_z}; @@ -110,7 +112,7 @@ Status ProgramManager::Build(const ProgramBase& program, wgpu::ShaderModuleDescriptor descriptor{}; descriptor.nextInChain = &wgsl_source; - auto shader_module = device_.CreateShaderModule(&descriptor); + auto shader_module = device.CreateShaderModule(&descriptor); // TODO: a new cache hierarchy for constants. // @@ -186,9 +188,26 @@ Status ProgramManager::Build(const ProgramBase& program, pipeline_descriptor.label = program.Name().c_str(); #endif - compute_pipeline = device_.CreateComputePipeline(&pipeline_descriptor); - - return Status(); + struct CreateComputePipelineContext { + wgpu::ComputePipeline& pipeline; + Status status; + } create_pipeline_context{compute_pipeline, {}}; + + ORT_RETURN_IF_ERROR( + webgpu_context_.Wait( + device.CreateComputePipelineAsync( + &pipeline_descriptor, + wgpu::CallbackMode::WaitAnyOnly, + [](wgpu::CreatePipelineAsyncStatus status, wgpu::ComputePipeline pipeline, wgpu::StringView message, CreateComputePipelineContext* context) { + if (status == wgpu::CreatePipelineAsyncStatus::Success) { + context->pipeline = std::move(pipeline); + } else { + context->status = ORT_MAKE_STATUS(ONNXRUNTIME, FAIL, "Failed to create a WebGPU compute pipeline: ", std::string_view{message}); + } + }, + &create_pipeline_context))); + + return create_pipeline_context.status; } const ProgramArtifact* ProgramManager::Get(const std::string& key) const { diff --git a/onnxruntime/core/providers/webgpu/program_manager.h b/onnxruntime/core/providers/webgpu/program_manager.h index a473051593852..7ac8b45886356 100644 --- a/onnxruntime/core/providers/webgpu/program_manager.h +++ b/onnxruntime/core/providers/webgpu/program_manager.h @@ -16,6 +16,7 @@ namespace onnxruntime { class Tensor; namespace webgpu { +class WebGpuContext; class ProgramArtifact { public: @@ -34,7 +35,7 @@ class ProgramArtifact { class ProgramManager { public: - ProgramManager(const wgpu::Device& device, const wgpu::Limits& limits) : device_(device), limits_(limits) {} + ProgramManager(WebGpuContext& webgpu_context) : webgpu_context_(webgpu_context) {} Status NormalizeDispatchGroupSize(uint32_t& x, uint32_t& y, uint32_t& z) const; Status CalculateSegmentsForInputsAndOutputs(ProgramBase& program); @@ -54,8 +55,7 @@ class ProgramManager { private: std::unordered_map programs_; - const wgpu::Device& device_; - const wgpu::Limits& limits_; + WebGpuContext& webgpu_context_; }; } // namespace webgpu diff --git a/onnxruntime/core/providers/webgpu/webgpu_context.cc b/onnxruntime/core/providers/webgpu/webgpu_context.cc index 0e4004db35b10..ba2e86fbcdcb3 100644 --- a/onnxruntime/core/providers/webgpu/webgpu_context.cc +++ b/onnxruntime/core/providers/webgpu/webgpu_context.cc @@ -145,7 +145,7 @@ void WebGpuContext::Initialize(const WebGpuBufferCacheConfig& buffer_cache_confi BufferCacheMode::Disabled); // create program manager - program_mgr_ = std::make_unique(Device(), DeviceLimits()); + program_mgr_ = std::make_unique(*this); // set query type #if !defined(__wasm__) From 771a4d49cd2385702c911d6390e38e5539242f83 Mon Sep 17 00:00:00 2001 From: Xiaofei Han Date: Tue, 28 Oct 2025 03:16:02 +0800 Subject: [PATCH 06/33] [webgpu] Fused GeneratePositionIDs into FusedQKRotaryEmbedding (#26400) ### Description This PR fused GeneratePositionIDs into FusedQKRotaryEmbedding which can reduce one kernel call. ### Motivation and Context Previously, for GQA, the processing flow was: `SplitPackedQKVProgram -> GeneratePositionIDs -> FusedQKRotaryEmbedding -> FlashAttention` After this change, the pipeline becomes: `SplitPackedQKVProgram -> FusedQKRotaryEmbedding -> FlashAttention` on NV5080, the token generation speed improved ~4%(128tps->133tps) --- .../webgpu/bert/group_query_attention.cc | 52 +------------------ .../webgpu/bert/group_query_attention.h | 13 ----- .../webgpu/bert/rotary_embedding.cc | 13 +++-- 3 files changed, 10 insertions(+), 68 deletions(-) diff --git a/onnxruntime/contrib_ops/webgpu/bert/group_query_attention.cc b/onnxruntime/contrib_ops/webgpu/bert/group_query_attention.cc index ce9fc988ac351..80a909438aa73 100644 --- a/onnxruntime/contrib_ops/webgpu/bert/group_query_attention.cc +++ b/onnxruntime/contrib_ops/webgpu/bert/group_query_attention.cc @@ -67,49 +67,6 @@ Status SplitPackedQKV(onnxruntime::webgpu::ComputeContext& context, const Webgpu return context.RunProgram(program); } -Status GeneratePositionIDsProgram::GenerateShaderCode(ShaderHelper& sh) const { - const auto& output = sh.AddOutput("output", ShaderUsage::UseUniform); - const auto& seqlens = sh.AddInput("seqlens", ShaderUsage::UseUniform); - sh.MainFunctionBody() << " var pos_id: i32 = 0;\n" - << " let batch_idx = global_idx / uniforms.sequence_length;\n" - << " let sequence_idx = i32(global_idx % uniforms.sequence_length);\n" - << " let seqlen = " << seqlens.GetByOffset("batch_idx") << ";\n"; - if (is_first_prompt_) { - sh.MainFunctionBody() << " let total_seqlen = seqlen + 1;\n" - << " if (sequence_idx < total_seqlen) {\n" - << " pos_id = sequence_idx;\n" - << " } else {\n" - << " pos_id = 1;\n" - << " }\n" - << " " << output.SetByOffset("global_idx", "pos_id") << "\n"; - } else if (is_subsequent_prompt_) { - sh.MainFunctionBody() << " let total_seqlen = seqlen + 1;\n" - << " let past_seqlen = total_seqlen - i32(uniforms.sequence_length);\n" - << " if (past_seqlen + sequence_idx < total_seqlen) {\n" - << " pos_id = past_seqlen + sequence_idx;\n" - << " } else {\n" - << " pos_id = 1;\n" - << " }\n" - << " " << output.SetByOffset("global_idx", "pos_id") << "\n"; - } else { - sh.MainFunctionBody() << " if (global_idx < uniforms.batch_size) {\n" - << " " << output.SetByOffset("global_idx", "seqlen") << "\n" - << " }\n"; - } - return Status::OK(); -} - -Status GeneratePositionIDs(onnxruntime::webgpu::ComputeContext& context, const WebgpuAttentionParameters& params, const Tensor* seqlens, Tensor* output_tensor) { - GeneratePositionIDsProgram program(params.is_first_prompt_, params.is_subsequent_prompt_); - auto output_size = params.batch_size_ * params.sequence_length_; - program.CacheHint(params.is_first_prompt_, params.is_subsequent_prompt_) - .AddInput({seqlens, ProgramTensorMetadataDependency::Rank}) - .AddOutput({output_tensor, ProgramTensorMetadataDependency::Rank}) - .AddUniformVariables({{static_cast(params.batch_size_)}, {static_cast(params.sequence_length_)}}) - .SetDispatchGroupSize((output_size + WORKGROUP_SIZE - 1) / WORKGROUP_SIZE); - return context.RunProgram(program); -} - // Fused Q/K rotary embedding Status RunFusedQKRotaryEmbedding(onnxruntime::webgpu::ComputeContext& context, const WebgpuAttentionParameters& params, @@ -120,10 +77,6 @@ Status RunFusedQKRotaryEmbedding(onnxruntime::webgpu::ComputeContext& context, const Tensor* sin_cache, Tensor* query_out, Tensor* key_out) { - Tensor pos_ids = context.CreateGPUTensor(DataTypeImpl::GetType(), - TensorShape({params.batch_size_, params.sequence_length_})); - ORT_RETURN_IF_ERROR(GeneratePositionIDs(context, params, seqlen_k, &pos_ids)); - const auto half_rotary_embedding_dim = gsl::narrow_cast(cos_cache->Shape()[1]); const auto head_size = params.head_size_; @@ -171,7 +124,7 @@ Status RunFusedQKRotaryEmbedding(onnxruntime::webgpu::ComputeContext& context, .AddInputs({ {query_in, ProgramTensorMetadataDependency::Rank}, {key_in, ProgramTensorMetadataDependency::Rank}, - {&pos_ids, ProgramTensorMetadataDependency::Rank}, + {seqlen_k, ProgramTensorMetadataDependency::Rank}, {cos_cache, ProgramTensorMetadataDependency::Rank}, {sin_cache, ProgramTensorMetadataDependency::Rank}, }) @@ -188,8 +141,7 @@ Status RunFusedQKRotaryEmbedding(onnxruntime::webgpu::ComputeContext& context, {gsl::make_span(k_global_dims)}, {gsl::make_span(k_input_output_strides)}, {q_domain_size}, - }) - .AddIndices(TensorShape{1, 1}); + }); return context.RunProgram(program); } diff --git a/onnxruntime/contrib_ops/webgpu/bert/group_query_attention.h b/onnxruntime/contrib_ops/webgpu/bert/group_query_attention.h index 1fb1e1ffc91fd..77ecc047636e3 100644 --- a/onnxruntime/contrib_ops/webgpu/bert/group_query_attention.h +++ b/onnxruntime/contrib_ops/webgpu/bert/group_query_attention.h @@ -14,19 +14,6 @@ namespace webgpu { using namespace onnxruntime::webgpu; -class GeneratePositionIDsProgram final : public Program { - public: - GeneratePositionIDsProgram(bool is_first_prompt, bool is_subsequent_prompt) : Program{"GeneratePositionIDs"}, is_first_prompt_(is_first_prompt), is_subsequent_prompt_(is_subsequent_prompt) {} - - Status GenerateShaderCode(ShaderHelper& sh) const override; - - WEBGPU_PROGRAM_DEFINE_UNIFORM_VARIABLES({"batch_size", ProgramUniformVariableDataType::Uint32}, {"sequence_length", ProgramUniformVariableDataType::Uint32}); - - private: - bool is_first_prompt_; - bool is_subsequent_prompt_; -}; - class SplitPackedQKVProgram final : public Program { public: SplitPackedQKVProgram() : Program{"SplitPackedQKV"} {} diff --git a/onnxruntime/contrib_ops/webgpu/bert/rotary_embedding.cc b/onnxruntime/contrib_ops/webgpu/bert/rotary_embedding.cc index 79c8f45fb7832..5536a26b3e00b 100644 --- a/onnxruntime/contrib_ops/webgpu/bert/rotary_embedding.cc +++ b/onnxruntime/contrib_ops/webgpu/bert/rotary_embedding.cc @@ -54,14 +54,12 @@ Status FusedQKRotaryEmbeddingProgram::GenerateShaderCode(ShaderHelper& shader) c // Inputs const auto& q_input = shader.AddInput("q_input", ShaderUsage::UseUniform); const auto& k_input = shader.AddInput("k_input", ShaderUsage::UseUniform); - const auto& position_ids = shader.AddInput("position_ids", ShaderUsage::UseUniform); + const auto& seqlens = shader.AddInput("seqlens", ShaderUsage::UseUniform); const auto& cos_cache = shader.AddInput("cos_cache", ShaderUsage::UseUniform); const auto& sin_cache = shader.AddInput("sin_cache", ShaderUsage::UseUniform); // Outputs const auto& q_output = shader.AddOutput("q_output", ShaderUsage::UseUniform); const auto& k_output = shader.AddOutput("k_output", ShaderUsage::UseUniform); - // Indices helper - const auto& dummy_indices = shader.AddIndices("dummy_indices", ShaderUsage::None); const auto interleaved_str = interleaved_ ? "true" : "false"; @@ -70,8 +68,13 @@ Status FusedQKRotaryEmbeddingProgram::GenerateShaderCode(ShaderHelper& shader) c << " let half_rotary_dim = uniforms.cos_cache_shape[1];\n" << " let bsnh = global_idx / uniforms.q_global_stride % uniforms.q_global_shape;\n" << " if (bsnh[3] < half_rotary_dim) {\n" - << " let pos_ids_idx = " << position_ids.BroadcastedIndicesToOffset("bsnh.xy", dummy_indices) << ";\n" - << " let position_id = u32(" << position_ids.GetByOffset("pos_ids_idx") << ") + select(0u, bsnh[1], pos_ids_idx == 0u);\n" + << " let batch_idx = bsnh[0];\n" + << " let sequence_idx = bsnh[1];\n" + << " let seqlen_i = " << seqlens.GetByOffset("batch_idx") << ";\n" + << " let seqlen = u32(seqlen_i);\n" + << " let total_seqlen = seqlen + 1u;\n" + << " let past_seqlen = total_seqlen - uniforms.q_global_shape[1];\n" + << " let position_id = past_seqlen + sequence_idx;\n" << " let cos_v = " << cos_cache.GetByIndices("vec2(position_id, bsnh[3])") << ";\n" << " let sin_v = " << sin_cache.GetByIndices("vec2(position_id, bsnh[3])") << ";\n" << " let qi = dot(bsnh, uniforms.q_input_output_stride) + select(0u, bsnh[3], " << interleaved_str << ");\n" From 06004826cc99dd8b8b92dbf000db3d3525716f22 Mon Sep 17 00:00:00 2001 From: Rene Haas Date: Tue, 28 Oct 2025 00:46:48 +0100 Subject: [PATCH 07/33] [Web] Add wasm and mjs files to package.json exports to improve bundler support (#26394) ### Description Currently the files which are needed for wasm aren't exported from the package at all. The files in question are: ``` ort-wasm-simd-threaded.wasm ort-wasm-simd-threaded.jsep.wasm ort-wasm-simd-threaded.asyncify.wasm ort-wasm-simd-threaded.mjs ort-wasm-simd-threaded.jsep.mjs ort-wasm-simd-threaded.asyncify.mjs ``` This PR changes that and adds them to `exports` field in the `package.json`. ### Motivation and Context Bundlers like `webpack` use the `copyPlugin` to move those files into the `public` directory, so the files can be accessed by a stable url. However more advanced and "state of the art" bundlers like `vite` are able to [import asset urls directly](https://vite.dev/guide/assets.html#explicit-url-imports). Vite takes the asset, moves it to to public assets folder (possibily renames the asset and adds a hash etc.). The imported value then is the bundled assets final url. Those urls can then be used in the `env.wasm.wasmPaths` directly. In vites case the full code example is: ```js import wasmUrl from 'onnxruntime-web/ort-wasm-simd-threaded.wasm?url'; import mjsUrl from 'onnxruntime-web/ort-wasm-simd-threaded.mjs?url'; env.wasm.wasmPaths = { wasm: wasmUrl, mjs: mjsUrl, }; ``` With those added exports we can leverage more of the bundlers capabilities and in vites case there isn't any need to add any additional configs. It would just work. When importing we also get proper suggestions: imports ---- I would like additional tests to ensure that the exports are available, but I couldn't make the `e2e` tests work on my system. I would appreciate some guidance on that topic. --- js/web/package.json | 10 ++++++++- js/web/test/e2e/package.json | 6 +++++- js/web/test/e2e/run-data.js | 2 ++ js/web/test/e2e/src/cjs-js/vite-main.js | 13 ++++++++++++ js/web/test/e2e/src/esm-js/vite-main.js | 13 ++++++++++++ js/web/test/e2e/vite.config.esm-js.js | 22 +++++++++++++++++++ js/web/test/e2e/vite.config.umd-js.js | 28 +++++++++++++++++++++++++ 7 files changed, 92 insertions(+), 2 deletions(-) create mode 100644 js/web/test/e2e/src/cjs-js/vite-main.js create mode 100644 js/web/test/e2e/src/esm-js/vite-main.js create mode 100644 js/web/test/e2e/vite.config.esm-js.js create mode 100644 js/web/test/e2e/vite.config.umd-js.js diff --git a/js/web/package.json b/js/web/package.json index d86bd9b383dd8..85b1deeec8490 100644 --- a/js/web/package.json +++ b/js/web/package.json @@ -115,7 +115,15 @@ "default": "./dist/ort.jspi.bundle.min.mjs" }, "require": "./dist/ort.jspi.min.js" - } + }, + "./ort-wasm-simd-threaded.wasm": "./dist/ort-wasm-simd-threaded.wasm", + "./ort-wasm-simd-threaded.jsep.wasm": "./dist/ort-wasm-simd-threaded.jsep.wasm", + "./ort-wasm-simd-threaded.jspi.wasm": "./dist/ort-wasm-simd-threaded.jspi.wasm", + "./ort-wasm-simd-threaded.asyncify.wasm": "./dist/ort-wasm-simd-threaded.asyncify.wasm", + "./ort-wasm-simd-threaded.mjs": "./dist/ort-wasm-simd-threaded.mjs", + "./ort-wasm-simd-threaded.jsep.mjs": "./dist/ort-wasm-simd-threaded.jsep.mjs", + "./ort-wasm-simd-threaded.jspi.mjs": "./dist/ort-wasm-simd-threaded.jspi.mjs", + "./ort-wasm-simd-threaded.asyncify.mjs": "./dist/ort-wasm-simd-threaded.asyncify.mjs" }, "types": "./types.d.ts", "description": "A Javascript library for running ONNX models on browsers" diff --git a/js/web/test/e2e/package.json b/js/web/test/e2e/package.json index 318fd5a6196d5..e315be1ab8353 100644 --- a/js/web/test/e2e/package.json +++ b/js/web/test/e2e/package.json @@ -20,6 +20,7 @@ "rollup": "^4.13.2", "rollup-plugin-copy": "^3.5.0", "tree-kill": "^1.2.2", + "vite": "^7.1.12", "webpack-cli": "^5.1.4" }, "scripts": { @@ -32,7 +33,10 @@ "build:p:esmjs": "parcel build --no-autoinstall --target esm && node ./bundler.esm.postprocess.js ./dist/parcel_esm_js/main.js", "build:p:umdjs": "parcel build --no-autoinstall --target umd", "build:p": "npm run build:p:esmjs && npm run build:p:umdjs", - "build": "npm run build:w && npm run build:r && npm run build:p" + "build:v:esmjs": "vite build -c vite.config.esm-js.js", + "build:v:umdjs": "vite build -c vite.config.umd-js.js", + "build:v": "npm run build:v:esmjs && npm run build:v:umdjs", + "build": "npm run build:v && npm run build:w && npm run build:r && npm run build:p" }, "@parcel/resolver-default": { "packageExports": true diff --git a/js/web/test/e2e/run-data.js b/js/web/test/e2e/run-data.js index 1db04095497c6..92aaecc1398a2 100644 --- a/js/web/test/e2e/run-data.js +++ b/js/web/test/e2e/run-data.js @@ -77,6 +77,8 @@ const BUNDLER_TEST_CASES = [ ['./dist/rollup_umd_js/ort-test-e2e.bundle.js', 'iife'], ['./dist/parcel_esm_js/main.js', 'esm'], ['./dist/parcel_umd_js/main.js', 'iife'], + ['./dist/vite_esm_js/ort-test-e2e.bundle.mjs', 'esm'], + ['./dist/vite_umd_js/ort-test-e2e.bundle.js', 'iife'], ]; module.exports = { diff --git a/js/web/test/e2e/src/cjs-js/vite-main.js b/js/web/test/e2e/src/cjs-js/vite-main.js new file mode 100644 index 0000000000000..415a7585d56e6 --- /dev/null +++ b/js/web/test/e2e/src/cjs-js/vite-main.js @@ -0,0 +1,13 @@ +require('onnxruntime-web/ort-wasm-simd-threaded.wasm?url&no-inline'); +require('onnxruntime-web/ort-wasm-simd-threaded.mjs?url&no-inline'); + +require('onnxruntime-web/ort-wasm-simd-threaded.jsep.wasm?url&no-inline'); +require('onnxruntime-web/ort-wasm-simd-threaded.jsep.mjs?url&no-inline'); + +require('onnxruntime-web/ort-wasm-simd-threaded.jspi.wasm?url&no-inline'); +require('onnxruntime-web/ort-wasm-simd-threaded.jspi.mjs?url&no-inline'); + +require('onnxruntime-web/ort-wasm-simd-threaded.asyncify.wasm?url&no-inline'); +require('onnxruntime-web/ort-wasm-simd-threaded.asyncify.mjs?url&no-inline'); + +require('./main'); diff --git a/js/web/test/e2e/src/esm-js/vite-main.js b/js/web/test/e2e/src/esm-js/vite-main.js new file mode 100644 index 0000000000000..b85bf3c287a6e --- /dev/null +++ b/js/web/test/e2e/src/esm-js/vite-main.js @@ -0,0 +1,13 @@ +import 'onnxruntime-web/ort-wasm-simd-threaded.wasm?url&no-inline'; +import 'onnxruntime-web/ort-wasm-simd-threaded.mjs?url&no-inline'; + +import 'onnxruntime-web/ort-wasm-simd-threaded.jsep.wasm?url&no-inline'; +import 'onnxruntime-web/ort-wasm-simd-threaded.jsep.mjs?url&no-inline'; + +import 'onnxruntime-web/ort-wasm-simd-threaded.jspi.wasm?url&no-inline'; +import 'onnxruntime-web/ort-wasm-simd-threaded.jspi.mjs?url&no-inline'; + +import 'onnxruntime-web/ort-wasm-simd-threaded.asyncify.wasm?url&no-inline'; +import 'onnxruntime-web/ort-wasm-simd-threaded.asyncify.mjs?url&no-inline'; + +import './main.js'; diff --git a/js/web/test/e2e/vite.config.esm-js.js b/js/web/test/e2e/vite.config.esm-js.js new file mode 100644 index 0000000000000..a6c7c7a8dc801 --- /dev/null +++ b/js/web/test/e2e/vite.config.esm-js.js @@ -0,0 +1,22 @@ +// Copyright (c) Microsoft Corporation. +// Licensed under the MIT license. + +const path = require('node:path'); +const { defineConfig } = require('vite'); + +module.exports = defineConfig({ + build: { + outDir: path.resolve(__dirname, 'dist/vite_esm_js'), + emptyOutDir: true, + sourcemap: false, + lib: { + name: 'testPackageConsuming', + entry: path.resolve(__dirname, 'src/esm-js/vite-main.js'), + fileName: () => 'ort-test-e2e.bundle.mjs', + formats: ['es'], + }, + minify: false, + assetsDir: './', + assetsInlineLimit: 0, + }, +}); diff --git a/js/web/test/e2e/vite.config.umd-js.js b/js/web/test/e2e/vite.config.umd-js.js new file mode 100644 index 0000000000000..9e2698b5e55df --- /dev/null +++ b/js/web/test/e2e/vite.config.umd-js.js @@ -0,0 +1,28 @@ +// Copyright (c) Microsoft Corporation. +// Licensed under the MIT license. + +const path = require('node:path'); +const { defineConfig } = require('vite'); + +module.exports = defineConfig({ + build: { + outDir: path.resolve(__dirname, 'dist/vite_umd_js'), + emptyOutDir: true, + sourcemap: false, + lib: { + name: 'testPackageConsuming', + entry: path.resolve(__dirname, 'src/esm-js/vite-main.js'), + fileName: () => 'ort-test-e2e.bundle.js', + formats: ['umd'], + }, + minify: false, + assetsDir: './', + assetsInlineLimit: 0, + commonjsOptions: { + include: ['**/*.js'], + exclude: [], + transformMixedEsModules: true, + ignoreDynamicRequires: true, + }, + }, +}); From e8b054ca8129b9efda086a9bd9496ad17107d67b Mon Sep 17 00:00:00 2001 From: Adrian Lizarraga Date: Tue, 28 Oct 2025 08:34:52 -0700 Subject: [PATCH 08/33] Update ORT_API_VERSION to 24 (#26418) ### Description - Updates the `ORT_API_VERSION` value in onnxruntime_c_api.h to `24`. - Edit documentation for the `TensorTypeAndShape_HasShape` API function to indicate the correct API version (1.24). - Adds `static_assert` to ensure that API functions for 1.23 are not added or removed. ### Motivation and Context The version of ORT was previously updated to 1.24.0 but we forgot to update `ORT_API_VERSION`. --- include/onnxruntime/core/session/onnxruntime_c_api.h | 4 ++-- onnxruntime/core/session/compile_api.cc | 3 +++ onnxruntime/core/session/model_editor_c_api.cc | 1 + onnxruntime/core/session/onnxruntime_c_api.cc | 3 +++ onnxruntime/core/session/plugin_ep/ep_api.cc | 3 +++ 5 files changed, 12 insertions(+), 2 deletions(-) diff --git a/include/onnxruntime/core/session/onnxruntime_c_api.h b/include/onnxruntime/core/session/onnxruntime_c_api.h index e6bbebdbf3ab8..d5f45343c1a97 100644 --- a/include/onnxruntime/core/session/onnxruntime_c_api.h +++ b/include/onnxruntime/core/session/onnxruntime_c_api.h @@ -38,7 +38,7 @@ * * This value is used by some API functions to behave as this version of the header expects. */ -#define ORT_API_VERSION 23 +#define ORT_API_VERSION 24 #ifdef __cplusplus extern "C" { @@ -6584,7 +6584,7 @@ struct OrtApi { * \param[in] info The OrtTensorTypeAndShapeInfo instance. * \return true if the tensor has shape information, false otherwise. * - * \since Version 1.23 + * \since Version 1.24 */ ORT_API_T(bool, TensorTypeAndShape_HasShape, _In_ const OrtTensorTypeAndShapeInfo* info); }; diff --git a/onnxruntime/core/session/compile_api.cc b/onnxruntime/core/session/compile_api.cc index b9a54ea7104e1..12127e9708255 100644 --- a/onnxruntime/core/session/compile_api.cc +++ b/onnxruntime/core/session/compile_api.cc @@ -342,11 +342,14 @@ static constexpr OrtCompileApi ort_compile_api = { &OrtCompileAPI::ModelCompilationOptions_SetGraphOptimizationLevel, &OrtCompileAPI::ModelCompilationOptions_SetOutputModelWriteFunc, &OrtCompileAPI::ModelCompilationOptions_SetOutputModelGetInitializerLocationFunc, + // End of Version 23 - DO NOT MODIFY ABOVE }; // checks that we don't violate the rule that the functions must remain in the slots they were originally assigned static_assert(offsetof(OrtCompileApi, CompileModel) / sizeof(void*) == 8, "Size of version 22 Api cannot change"); // initial version in ORT 1.22 +static_assert(offsetof(OrtCompileApi, ModelCompilationOptions_SetOutputModelGetInitializerLocationFunc) / sizeof(void*) == 13, + "Size of version 23 of Api cannot change"); ORT_API(const OrtCompileApi*, OrtCompileAPI::GetCompileApi) { return &ort_compile_api; diff --git a/onnxruntime/core/session/model_editor_c_api.cc b/onnxruntime/core/session/model_editor_c_api.cc index 4f74e258cc943..487d5c818f9bc 100644 --- a/onnxruntime/core/session/model_editor_c_api.cc +++ b/onnxruntime/core/session/model_editor_c_api.cc @@ -393,6 +393,7 @@ static constexpr OrtModelEditorApi ort_model_editor_api = { &OrtModelEditorAPI::SessionGetOpsetForDomain, &OrtModelEditorAPI::ApplyModelToModelEditorSession, &OrtModelEditorAPI::FinalizeModelEditorSession, + // End of Version 22 - DO NOT MODIFY ABOVE }; // checks that we don't violate the rule that the functions must remain in the slots they were originally assigned diff --git a/onnxruntime/core/session/onnxruntime_c_api.cc b/onnxruntime/core/session/onnxruntime_c_api.cc index 7603397ea9cad..546b11ae580d5 100644 --- a/onnxruntime/core/session/onnxruntime_c_api.cc +++ b/onnxruntime/core/session/onnxruntime_c_api.cc @@ -4228,6 +4228,8 @@ static constexpr OrtApi ort_api_1_to_24 = { &OrtApis::Graph_GetModelMetadata, &OrtApis::GetModelCompatibilityForEpDevices, &OrtApis::CreateExternalInitializerInfo, + // End of Version 23 - DO NOT MODIFY ABOVE (see above text for more information) + &OrtApis::TensorTypeAndShape_HasShape, }; @@ -4264,6 +4266,7 @@ static_assert(offsetof(OrtApi, AddExternalInitializersFromFilesInMemory) / sizeo static_assert(offsetof(OrtApi, SetEpDynamicOptions) / sizeof(void*) == 284, "Size of version 20 API cannot change"); static_assert(offsetof(OrtApi, GetEpApi) / sizeof(void*) == 317, "Size of version 22 API cannot change"); +static_assert(offsetof(OrtApi, CreateExternalInitializerInfo) / sizeof(void*) == 389, "Size of version 23 API cannot change"); // So that nobody forgets to finish an API version, this check will serve as a reminder: static_assert(std::string_view(ORT_VERSION) == "1.24.0", diff --git a/onnxruntime/core/session/plugin_ep/ep_api.cc b/onnxruntime/core/session/plugin_ep/ep_api.cc index cae0b086af66c..366f96e585918 100644 --- a/onnxruntime/core/session/plugin_ep/ep_api.cc +++ b/onnxruntime/core/session/plugin_ep/ep_api.cc @@ -230,11 +230,14 @@ static constexpr OrtEpApi ort_ep_api = { &OrtExecutionProviderApi::SyncStream_GetImpl, &OrtExecutionProviderApi::SyncStream_GetSyncId, &OrtExecutionProviderApi::GetSyncIdForLastWaitOnSyncStream, + // End of Version 23 - DO NOT MODIFY ABOVE }; // checks that we don't violate the rule that the functions must remain in the slots they were originally assigned static_assert(offsetof(OrtEpApi, ReleaseEpDevice) / sizeof(void*) == 1, "Size of version 22 API cannot change"); // initial version in ORT 1.22 +static_assert(offsetof(OrtEpApi, GetSyncIdForLastWaitOnSyncStream) / sizeof(void*) == 15, + "Size of version 23 API cannot change"); } // namespace OrtExecutionProviderApi From 16332991580377aa9ff3f29087fda0a75ed480f6 Mon Sep 17 00:00:00 2001 From: Tianlei Wu Date: Tue, 28 Oct 2025 09:28:45 -0700 Subject: [PATCH 09/33] [CUDA] Add nightly gpu package and publish pipelines for CUDA 13 (#26420) Add nightly gpu pipelines for CUDA 13. --- cmake/onnxruntime_providers_cuda.cmake | 1 + .../py-cuda13-packaging-pipeline.yml | 52 ++++++++++++++ .../py-cuda13-publishing-pipeline.yml | 40 +++++++++++ .../stages/py-gpu-packaging-stage.yml | 32 ++++++--- .../stages/py-linux-gpu-stage.yml | 2 + .../stages/py-win-gpu-stage.yml | 2 + .../templates/common-variables.yml | 2 +- .../jobs/download_win_gpu_library.yml | 72 ++++++++++--------- .../py-packaging-linux-test-cuda.yml | 1 + 9 files changed, 163 insertions(+), 41 deletions(-) create mode 100644 tools/ci_build/github/azure-pipelines/py-cuda13-packaging-pipeline.yml create mode 100644 tools/ci_build/github/azure-pipelines/py-cuda13-publishing-pipeline.yml diff --git a/cmake/onnxruntime_providers_cuda.cmake b/cmake/onnxruntime_providers_cuda.cmake index 1d31eb1fbd207..9e754e4a67d40 100644 --- a/cmake/onnxruntime_providers_cuda.cmake +++ b/cmake/onnxruntime_providers_cuda.cmake @@ -222,6 +222,7 @@ if(MSVC) target_compile_options(${target} PRIVATE "$<$:SHELL:-Xcompiler /Zc:__cplusplus>") + target_compile_options(${target} PRIVATE "$<$:SHELL:-Xcompiler /bigobj>") endif() onnxruntime_add_include_to_target(${target} onnxruntime_common onnxruntime_framework onnx onnx_proto ${PROTOBUF_LIB} flatbuffers::flatbuffers) diff --git a/tools/ci_build/github/azure-pipelines/py-cuda13-packaging-pipeline.yml b/tools/ci_build/github/azure-pipelines/py-cuda13-packaging-pipeline.yml new file mode 100644 index 0000000000000..8debb4437797a --- /dev/null +++ b/tools/ci_build/github/azure-pipelines/py-cuda13-packaging-pipeline.yml @@ -0,0 +1,52 @@ +trigger: none +# The `resources` specify the location and version of the 1ES PT. +resources: + repositories: + - repository: 1esPipelines + type: git + name: 1ESPipelineTemplates/1ESPipelineTemplates + ref: refs/tags/release +parameters: + - name: cmake_build_type + type: string + default: 'Release' + values: + - Debug + - Release + - RelWithDebInfo + - MinSizeRel + +extends: + # The pipeline extends the 1ES PT which will inject different SDL and compliance tasks. + # For non-production pipelines, use "Unofficial" as defined below. + # For productions pipelines, use "Official". + template: v1/1ES.Official.PipelineTemplate.yml@1esPipelines + parameters: + sdl: + componentgovernance: + ignoreDirectories: '$(Build.Repository.LocalPath)/cmake/external/emsdk/upstream/emscripten/tests,$(Build.Repository.LocalPath)/cmake/external/onnx/third_party/benchmark,$(Build.Repository.LocalPath)/cmake/external/onnx/third_party/pybind11,$(Build.Repository.LocalPath)/cmake/external/onnx/third_party/pybind11/tests,$(Build.Repository.LocalPath)/cmake/external/onnxruntime-extensions,$(Build.Repository.LocalPath)/js/react_native/e2e/node_modules,$(Build.Repository.LocalPath)/js/node_modules,$(Build.Repository.LocalPath)/onnxruntime-inference-examples,$(Build.SourcesDirectory)/cmake/external/emsdk/upstream/emscripten/tests,$(Build.SourcesDirectory)/cmake/external/onnx/third_party/benchmark,$(Build.SourcesDirectory)/cmake/external/onnx/third_party/pybind11,$(Build.SourcesDirectory)/cmake/external/onnx/third_party/pybind11/tests,$(Build.SourcesDirectory)/cmake/external/onnxruntime-extensions,$(Build.SourcesDirectory)/js/react_native/e2e/node_modules,$(Build.SourcesDirectory)/js/node_modules,$(Build.SourcesDirectory)/onnxruntime-inference-examples,$(Build.BinariesDirectory)' + alertWarningLevel: High + failOnAlert: false + verbosity: Normal + timeout: 3600 + tsa: + enabled: true + codeSignValidation: + enabled: true + break: true + policheck: + enabled: true + exclusionsFile: '$(Build.SourcesDirectory)\tools\ci_build\policheck_exclusions.xml' + codeql: + compiled: + enabled: false + justificationForDisabling: 'CodeQL is taking nearly 6 hours resulting in timeouts in our production pipelines' + pool: + name: 'onnxruntime-Win-CPU-VS2022-Latest' # Name of your hosted pool + os: windows # OS of the image. This value cannot be a variable. Allowed values: windows, linux, macOS + + stages: + - template: stages/py-gpu-packaging-stage.yml + parameters: + cmake_build_type: ${{ parameters.cmake_build_type }} + cuda_version: '13.0' diff --git a/tools/ci_build/github/azure-pipelines/py-cuda13-publishing-pipeline.yml b/tools/ci_build/github/azure-pipelines/py-cuda13-publishing-pipeline.yml new file mode 100644 index 0000000000000..5bbfd67623c3a --- /dev/null +++ b/tools/ci_build/github/azure-pipelines/py-cuda13-publishing-pipeline.yml @@ -0,0 +1,40 @@ +resources: + pipelines: + - pipeline: build + source: 'Python CUDA Package Test Pipeline' + trigger: + branches: + include: + - main + branch: main + repositories: + - repository: 1esPipelines + type: git + name: 1ESPipelineTemplates/1ESPipelineTemplates + ref: refs/tags/release +parameters: + - name: isReleaseBuild + type: boolean + default: false + +variables: + - name: ArtifactFeed + ${{ if eq(parameters.isReleaseBuild, false) }}: + value: ort-cuda-13-nightly + ${{ else }}: + value: onnxruntime-cuda-13 + +extends: + # The pipeline extends the 1ES PT which will inject different SDL and compliance tasks. + # For non-production pipelines, use "Unofficial" as defined below. + # For productions pipelines, use "Official". + template: v1/1ES.Official.PipelineTemplate.yml@1esPipelines + parameters: + sdl: + sourceAnalysisPool: + name: onnxruntime-Win-CPU-VS2022-Latest + os: windows + stages: + - template: stages/py-cuda-publishing-stage.yml + parameters: + artifact_feed: $(ArtifactFeed) diff --git a/tools/ci_build/github/azure-pipelines/stages/py-gpu-packaging-stage.yml b/tools/ci_build/github/azure-pipelines/stages/py-gpu-packaging-stage.yml index 755c6e0e88bd6..35d559c871ab8 100644 --- a/tools/ci_build/github/azure-pipelines/stages/py-gpu-packaging-stage.yml +++ b/tools/ci_build/github/azure-pipelines/stages/py-gpu-packaging-stage.yml @@ -22,6 +22,11 @@ parameters: default: '12.8' values: - 12.8 + - 13.0 + +- name: cudnn_folder + type: string + default: '9.13.0.50_cuda13' - name: PythonVersions type: object @@ -32,14 +37,25 @@ parameters: - '3.13' stages: - - ${{ each python_version in parameters.PythonVersions }}: - - template: py-win-gpu-stage.yml - parameters: - PYTHON_VERSION: ${{ python_version }} - EP_NAME: gpu - CudaVersion: ${{ parameters.cuda_version }} - EP_BUILD_FLAGS: --enable_lto --use_cuda --cuda_home=$(Agent.TempDirectory)\v${{ parameters.cuda_version }} --cmake_extra_defines "CMAKE_CUDA_ARCHITECTURES=52-real;61-real;75-real;86-real;89-real;90-virtual" - use_tensorrt: True + - ${{ if eq(parameters.cuda_version, '12.8') }}: + - ${{ each python_version in parameters.PythonVersions }}: + - template: py-win-gpu-stage.yml + parameters: + PYTHON_VERSION: ${{ python_version }} + EP_NAME: gpu + CudaVersion: ${{ parameters.cuda_version }} + EP_BUILD_FLAGS: --enable_lto --use_cuda --cuda_home=$(Agent.TempDirectory)\v${{ parameters.cuda_version }} --cmake_extra_defines "CMAKE_CUDA_ARCHITECTURES=52-real;61-real;75-real;86-real;89-real;90-virtual" + use_tensorrt: True + + - ${{ if eq(parameters.cuda_version, '13.0') }}: + - ${{ each python_version in parameters.PythonVersions }}: + - template: py-win-gpu-stage.yml + parameters: + PYTHON_VERSION: ${{ python_version }} + EP_NAME: gpu + CudaVersion: ${{ parameters.cuda_version }} + EP_BUILD_FLAGS: --enable_lto --use_cuda --cuda_home=$(Agent.TempDirectory)\v${{ parameters.cuda_version }} --cudnn_home=$(Agent.TempDirectory)\${{ parameters.cudnn_folder }} --cmake_extra_defines "CMAKE_CUDA_ARCHITECTURES=75-real;86-real;89-real;90-virtual" + use_tensorrt: True - template: py-linux-gpu-stage.yml parameters: diff --git a/tools/ci_build/github/azure-pipelines/stages/py-linux-gpu-stage.yml b/tools/ci_build/github/azure-pipelines/stages/py-linux-gpu-stage.yml index f5b2c05931808..8b09e60d5aa89 100644 --- a/tools/ci_build/github/azure-pipelines/stages/py-linux-gpu-stage.yml +++ b/tools/ci_build/github/azure-pipelines/stages/py-linux-gpu-stage.yml @@ -17,6 +17,7 @@ parameters: - Release - RelWithDebInfo - MinSizeRel + - name: docker_base_image type: string @@ -25,6 +26,7 @@ parameters: default: '12.8' values: - 12.8 + - 13.0 stages: - stage: Linux_py_GPU_Wheels_${{ parameters.arch }} diff --git a/tools/ci_build/github/azure-pipelines/stages/py-win-gpu-stage.yml b/tools/ci_build/github/azure-pipelines/stages/py-win-gpu-stage.yml index 0c163f74768ca..4472e3185ad40 100644 --- a/tools/ci_build/github/azure-pipelines/stages/py-win-gpu-stage.yml +++ b/tools/ci_build/github/azure-pipelines/stages/py-win-gpu-stage.yml @@ -18,11 +18,13 @@ parameters: Extra parameters to pass to build.py. Don't put newlines in here. type: string default: '' + - name: CudaVersion type: string default: '12.8' values: - 12.8 + - 13.0 - name: cmake_build_type type: string diff --git a/tools/ci_build/github/azure-pipelines/templates/common-variables.yml b/tools/ci_build/github/azure-pipelines/templates/common-variables.yml index a0ac2cfad1a93..32b9d1aa75a3b 100644 --- a/tools/ci_build/github/azure-pipelines/templates/common-variables.yml +++ b/tools/ci_build/github/azure-pipelines/templates/common-variables.yml @@ -4,5 +4,5 @@ variables: # As for Debian installation, replace '-1.' by '-1+' when assigning trt version below linux_trt_version_cuda13: ${{ variables.cuda13_trt_version }}-1.cuda13.0 linux_trt_version_cuda12: ${{ variables.cuda12_trt_version }}-1.cuda12.8 - win_trt_folder_cuda13: TensorRT-${{ variables.cuda13_trt_version }}.Windows10.win10.cuda-13.0 + win_trt_folder_cuda13: TensorRT-${{ variables.cuda13_trt_version }}.Windows.win10.cuda-13.0 win_trt_folder_cuda12: TensorRT-${{ variables.cuda12_trt_version }}.Windows10.x86_64.cuda-12.8 diff --git a/tools/ci_build/github/azure-pipelines/templates/jobs/download_win_gpu_library.yml b/tools/ci_build/github/azure-pipelines/templates/jobs/download_win_gpu_library.yml index 631f40bcdd22a..daef2638aa3ff 100644 --- a/tools/ci_build/github/azure-pipelines/templates/jobs/download_win_gpu_library.yml +++ b/tools/ci_build/github/azure-pipelines/templates/jobs/download_win_gpu_library.yml @@ -11,12 +11,9 @@ parameters: values: - 13.0 - 12.8 - - name: TrtVersion + - name: CudnnFolder type: string - default: '10.9.0.34' - values: - - 10.9.0.34 - - 10.13.3.9 + default: '9.13.0.50_cuda13' steps: - ${{ if eq(parameters.DownloadCUDA, true) }}: @@ -41,49 +38,60 @@ steps: dir $(Agent.TempDirectory) displayName: 'Print PATH after download CUDA SDK' - - ${{ if eq(parameters.DownloadTRT, true) }}: - ${{ if eq(parameters.CudaVersion, '13.0') }}: - - powershell: | - Write-Host "##vso[task.setvariable variable=trtCudaVersion;]13.0" - displayName: Set trtCudaVersion - - ${{ if and(eq(parameters.CudaVersion, '12.8'), eq(parameters.TrtVersion, '10.13.3.9')) }}: - - powershell: | - Write-Host "##vso[task.setvariable variable=trtCudaVersion;]12.9" - displayName: Set trtCudaVersion - - ${{ if and(eq(parameters.CudaVersion, '12.8'), eq(parameters.TrtVersion, '10.9.0.34')) }}: - - powershell: | - Write-Host "##vso[task.setvariable variable=trtCudaVersion;]12.8" - displayName: Set trtCudaVersion + - task: AzureCLI@2 + displayName: 'Download CUDNN ${{ parameters.CudnnFolder }}' + inputs: + azureSubscription: AIInfraBuildOnnxRuntimeOSS + scriptType: 'batch' + scriptLocation: 'inlineScript' + inlineScript: | + set AZCOPY_AUTO_LOGIN_TYPE=AZCLI + azcopy.exe cp --recursive https://lotusscus.blob.core.windows.net/models/cudnn_sdk/${{ parameters.CudnnFolder }} $(Agent.TempDirectory) - - ${{ if eq(parameters.TrtVersion, '10.9.0.34') }}: - powershell: | - Write-Host "##vso[task.setvariable variable=trtPlatformString;]Windows10.x86_64" - displayName: 'Set TRT platform string for 10.9.0.34' + Write-Host "##vso[task.prependpath]$(Agent.TempDirectory)\${{ parameters.CudnnFolder }}\bin" + displayName: 'Append CUDNN Directory to PATH' - - ${{ if eq(parameters.TrtVersion, '10.13.3.9') }}: - - powershell: | - Write-Host "##vso[task.setvariable variable=trtPlatformString;]Windows.win10" - displayName: 'Set TRT platform string for 10.13.3.9' + - task: CmdLine@2 + inputs: + script: | + echo %PATH% + dir $(Agent.TempDirectory) + displayName: 'Print PATH after download CUDNN SDK' + - ${{ if eq(parameters.DownloadTRT, true) }}: - powershell: | - $trtDirName = "TensorRT-${{ parameters.TrtVersion }}.$(trtPlatformString).cuda-$(trtCudaVersion)" - Write-Host "TensorRT Directory Name: $trtDirName" - Write-Host "##vso[task.setvariable variable=trtDirName;]$trtDirName" - displayName: 'Construct TensorRT Directory Name' + # These values are copied from common-variables.yml + $cuda12_trt_version = '10.9.0.34' + $cuda13_trt_version = '10.13.3.9' + + $trtFolder = "" + if ("${{ parameters.CudaVersion }}" -eq "13.0") { + $trtFolder = "TensorRT-$cuda13_trt_version.Windows.win10.cuda-13.0" + } + elseif ("${{ parameters.CudaVersion }}" -eq "12.8") { + $trtFolder = "TensorRT-$cuda12_trt_version.Windows10.x86_64.cuda-12.8" + } + + Write-Host "Setting TrtFolderRuntime variable to: $trtFolder" + # This makes the variable available to subsequent steps in this job + Write-Host "##vso[task.setvariable variable=TrtFolderRuntime;]$trtFolder" + displayName: 'Set TensorRT Folder Variable' - task: AzureCLI@2 - displayName: 'Download $(trtDirName)' + displayName: 'Download TensorRT Directory' inputs: azureSubscription: AIInfraBuildOnnxRuntimeOSS scriptType: 'batch' scriptLocation: 'inlineScript' inlineScript: | set AZCOPY_AUTO_LOGIN_TYPE=AZCLI - azcopy.exe cp --recursive https://lotusscus.blob.core.windows.net/models/local/$(trtDirName) $(Agent.TempDirectory) + azcopy.exe cp --recursive https://lotusscus.blob.core.windows.net/models/local/$(TrtFolderRuntime) $(Agent.TempDirectory) - powershell: | - Write-Host "##vso[task.prependpath]$(Agent.TempDirectory)\$(trtDirName)\lib" - displayName: 'Append $(trtDirName) Directory to PATH' + Write-Host "##vso[task.prependpath]$(Agent.TempDirectory)\$(TrtFolderRuntime)\lib" + displayName: 'Append TensorRT Directory to PATH' - task: CmdLine@2 inputs: diff --git a/tools/ci_build/github/azure-pipelines/templates/py-packaging-linux-test-cuda.yml b/tools/ci_build/github/azure-pipelines/templates/py-packaging-linux-test-cuda.yml index 3244008eb281a..a10ea02542908 100644 --- a/tools/ci_build/github/azure-pipelines/templates/py-packaging-linux-test-cuda.yml +++ b/tools/ci_build/github/azure-pipelines/templates/py-packaging-linux-test-cuda.yml @@ -21,6 +21,7 @@ parameters: default: '12.8' values: - 12.8 + - 13.0 # TODO: Ideally it should fetch information from the build that triggers it - name: cmake_build_type From c6c6d784458e882de81b0ea719a58bc10f0afe98 Mon Sep 17 00:00:00 2001 From: Yulong Wang <7679871+fs-eire@users.noreply.github.com> Date: Tue, 28 Oct 2025 10:22:50 -0700 Subject: [PATCH 10/33] [js] Upgrade ESLint from v8 to v9 for subfolder /js/ (#26419) ### Description [js] Upgrade ESLint from v8 to v9 for subfolder /js/ ### Motivation and Context --- js/.eslintrc.js | 266 - js/common/lib/tensor-conversion-impl.ts | 2 +- js/common/package-lock.json | 519 ++ js/common/package.json | 1 + js/common/test/type-tests.ts | 4 +- js/eslint.config.mjs | 364 ++ js/node/test/test-utils.ts | 2 +- js/node/test/unittests/lib/tensor.ts | 30 +- js/package-lock.json | 5617 ++++++++++------- js/package.json | 18 +- js/react_native/e2e/src/App.tsx | 5 +- js/react_native/lib/binding.ts | 2 - js/web/lib/backend-onnxjs.ts | 1 - .../backends/webgl/webgl-context-factory.ts | 2 +- js/web/lib/onnxjs/execution-plan.ts | 3 +- js/web/lib/onnxjs/graph.ts | 2 +- js/web/lib/onnxjs/util.ts | 1 - js/web/lib/wasm/jsep/util.ts | 1 - js/web/lib/wasm/jsep/webgpu/ops/binary-op.ts | 4 +- js/web/lib/wasm/jsep/webgpu/ops/where.ts | 1 - js/web/lib/wasm/jsep/webnn/tensor-manager.ts | 1 - js/web/lib/wasm/jsep/webnn/webnn.d.ts | 97 +- js/web/lib/wasm/wasm-factory.ts | 6 +- js/web/lib/wasm/wasm-utils-load-file.ts | 1 - js/web/script/generate-webgl-operator-md.ts | 2 +- js/web/script/generate-webgpu-operator-md.ts | 2 - js/web/script/parse-profiler.ts | 2 - js/web/script/pull-prebuilt-wasm-artifacts.ts | 2 +- js/web/script/test-runner-cli-args.ts | 2 - js/web/script/test-runner-cli.ts | 1 - js/web/test/test-runner.ts | 2 +- js/web/test/test-types.ts | 1 - js/web/test/unittests/opset.ts | 4 +- 33 files changed, 4335 insertions(+), 2633 deletions(-) delete mode 100644 js/.eslintrc.js create mode 100644 js/eslint.config.mjs diff --git a/js/.eslintrc.js b/js/.eslintrc.js deleted file mode 100644 index f20adcb0eaa52..0000000000000 --- a/js/.eslintrc.js +++ /dev/null @@ -1,266 +0,0 @@ -// Copyright (c) Microsoft Corporation. All rights reserved. -// Licensed under the MIT License. - -'use strict'; - -module.exports = { - root: true, - ignorePatterns: [ - '**/*.js', - 'node_modules/', - 'ort-schema/', - 'common/test/type-tests/', - 'web/types.d.ts', - 'test/data/', - 'dist/', - ], - env: { es6: true }, - parser: '@typescript-eslint/parser', - parserOptions: { project: true, sourceType: 'module' }, - plugins: ['@typescript-eslint', 'prefer-arrow', 'header', 'import', 'unicorn', 'jsdoc'], - rules: { - 'unicorn/filename-case': 'error', - 'header/header': [ - 2, - 'line', - [' Copyright (c) Microsoft Corporation. All rights reserved.', ' Licensed under the MIT License.'], - 2, - ], - 'import/no-extraneous-dependencies': ['error', { devDependencies: false }], - 'import/no-internal-modules': [ - 'error', - { - allow: ['**/lib/**'], - }, - ], - 'import/no-unassigned-import': 'error', - '@typescript-eslint/array-type': ['error', { default: 'array-simple' }], - '@typescript-eslint/await-thenable': 'error', - '@typescript-eslint/ban-types': [ - 'error', - { - types: { - Object: { message: 'Use {} instead.' }, - String: { message: "Use 'string' instead." }, - Number: { message: "Use 'number' instead." }, - Boolean: { message: "Use 'boolean' instead." }, - }, - }, - ], - '@typescript-eslint/naming-convention': 'error', - '@typescript-eslint/consistent-type-assertions': 'error', - '@typescript-eslint/member-delimiter-style': [ - 'error', - { - multiline: { delimiter: 'semi', requireLast: true }, - singleline: { delimiter: 'semi', requireLast: false }, - }, - ], - '@typescript-eslint/no-empty-function': 'error', - '@typescript-eslint/no-explicit-any': 'error', - '@typescript-eslint/no-floating-promises': 'error', - '@typescript-eslint/no-for-in-array': 'error', - '@typescript-eslint/no-inferrable-types': 'error', - '@typescript-eslint/no-misused-new': 'error', - '@typescript-eslint/no-namespace': ['error', { allowDeclarations: true }], - '@typescript-eslint/no-non-null-assertion': 'off', - '@typescript-eslint/no-require-imports': ['error', { allow: ['^node:'] }], - '@typescript-eslint/no-var-requires': ['error', { allow: ['^node:'] }], - '@typescript-eslint/no-unnecessary-type-assertion': 'error', - '@typescript-eslint/no-unused-vars': ['error', { argsIgnorePattern: '^_' }], - '@typescript-eslint/promise-function-async': 'error', - '@typescript-eslint/restrict-plus-operands': 'error', - '@typescript-eslint/semi': ['error', 'always'], - '@typescript-eslint/triple-slash-reference': ['error', { path: 'always', types: 'prefer-import', lib: 'always' }], - 'arrow-body-style': 'error', - camelcase: 'error', - 'constructor-super': 'error', - curly: 'error', - 'default-case': 'error', - 'dot-notation': 'error', - eqeqeq: ['error', 'smart'], - 'guard-for-in': 'error', - 'id-match': 'error', - 'new-parens': 'error', - 'no-bitwise': 'error', - 'no-caller': 'error', - 'no-cond-assign': 'error', - 'no-console': 'error', - 'no-constant-condition': 'error', - 'no-control-regex': 'error', - 'no-debugger': 'error', - 'no-duplicate-case': 'error', - 'no-empty': 'error', - 'no-eval': 'error', - 'no-extra-bind': 'error', - 'no-invalid-regexp': 'error', - 'no-invalid-this': 'error', - 'no-multiple-empty-lines': 'error', - 'no-new-func': 'error', - 'no-new-wrappers': 'error', - 'no-octal': 'error', - 'no-octal-escape': 'error', - 'no-param-reassign': 'error', - 'no-redeclare': 'off', - '@typescript-eslint/no-redeclare': ['error'], - 'no-regex-spaces': 'error', - 'no-return-await': 'error', - 'no-sparse-arrays': 'error', - 'no-template-curly-in-string': 'error', - 'no-throw-literal': 'error', - 'no-undef-init': 'error', - 'no-underscore-dangle': 'error', - 'no-unsafe-finally': 'error', - 'no-unused-expressions': 'error', - 'no-unused-labels': 'error', - 'no-use-before-define': 'off', - '@typescript-eslint/no-use-before-define': 'error', - 'no-var': 'error', - 'object-shorthand': 'error', - 'prefer-arrow/prefer-arrow-functions': 'error', - 'prefer-const': 'error', - radix: 'error', - 'use-isnan': 'error', - }, - overrides: [ - { - files: ['node/**/*.ts'], - env: { es6: true, node: true }, - }, - { - files: ['common/lib/**/*.ts', 'node/lib/**/*.ts'], - rules: { - 'jsdoc/check-alignment': 'error', - 'jsdoc/check-indentation': 'error', - }, - }, - { - files: ['common/test/**/*.ts'], - rules: { - '@typescript-eslint/naming-convention': 'off', - 'import/no-extraneous-dependencies': 'off', - }, - }, - { - files: ['node/script/**/*.ts', 'node/test/**/*.ts', 'web/script/**/*.ts', 'web/test/**/*.ts'], - rules: { - '@typescript-eslint/naming-convention': 'off', - '@typescript-eslint/no-empty-function': 'off', - '@typescript-eslint/no-explicit-any': 'off', - '@typescript-eslint/no-require-imports': 'off', - '@typescript-eslint/no-var-requires': 'off', - '@typescript-eslint/no-unnecessary-type-assertion': 'off', - camelcase: 'off', - 'prefer-arrow/prefer-arrow-functions': 'off', - 'import/no-extraneous-dependencies': 'off', - 'import/no-unassigned-import': 'off', - 'import/no-internal-modules': 'off', - 'no-console': 'off', - 'no-empty': 'off', - 'no-unused-expressions': 'off', - }, - }, - { - files: ['web/lib/**/*.ts'], - rules: { - 'no-underscore-dangle': [ - 'error', - { - allow: [ - '_free', - '_malloc', - '_JsepGetNodeName', - '_JsepOutput', - '_OrtAddFreeDimensionOverride', - '_OrtAddRunConfigEntry', - '_OrtAddSessionConfigEntry', - '_OrtAppendExecutionProvider', - '_OrtBindInput', - '_OrtBindOutput', - '_OrtClearBoundOutputs', - '_OrtCreateBinding', - '_OrtCreateRunOptions', - '_OrtCreateSession', - '_OrtCreateSessionOptions', - '_OrtCreateTensor', - '_OrtEndProfiling', - '_OrtFree', - '_OrtGetInputOutputCount', - '_OrtGetInputOutputMetadata', - '_OrtGetLastError', - '_OrtGetTensorData', - '_OrtInit', - '_OrtReleaseBinding', - '_OrtReleaseRunOptions', - '_OrtReleaseSession', - '_OrtReleaseSessionOptions', - '_OrtReleaseTensor', - '_OrtRun', - '_OrtRunWithBinding', - ], - }, - ], - }, - }, - { - files: ['web/lib/onnxjs/**/*.ts'], - rules: { - // TODO: those rules are useful. should turn on them in future (webgl refactor) - '@typescript-eslint/no-empty-function': 'off', - '@typescript-eslint/explicit-module-boundary-types': 'off', - '@typescript-eslint/no-use-before-define': 'off', - '@typescript-eslint/no-unnecessary-type-assertion': 'off', - '@typescript-eslint/restrict-plus-operands': 'off', - 'import/no-internal-modules': 'off', - 'prefer-arrow/prefer-arrow-functions': 'off', - 'no-param-reassign': 'off', - 'no-underscore-dangle': 'off', - 'guard-for-in': 'off', - }, - }, - { - files: ['react_native/e2e/src/**/*.ts', 'react_native/e2e/src/**/*.tsx'], - rules: { - '@typescript-eslint/no-non-null-assertion': 'off', - '@typescript-eslint/no-unnecessary-type-assertion': 'off', - 'unicorn/filename-case': 'off', - 'no-invalid-this': 'off', - 'no-console': 'off', - }, - }, - { - files: ['react_native/lib/**/*.ts'], - rules: { - '@typescript-eslint/naming-convention': 'off', - }, - }, - { - files: ['react_native/scripts/**/*.ts'], - rules: { - 'import/no-extraneous-dependencies': 'off', - 'prefer-arrow/prefer-arrow-functions': 'off', - 'no-console': 'off', - }, - }, - { - files: ['scripts/**/*.ts'], - rules: { - 'import/no-extraneous-dependencies': 'off', - 'no-console': 'off', - }, - }, - { - files: ['web/lib/**/3rd-party/**/*.ts'], - rules: { - 'header/header': 'off', - 'unicorn/filename-case': 'off', - '@typescript-eslint/explicit-module-boundary-types': 'off', - }, - }, - ], - extends: [ - 'eslint:recommended', - 'plugin:@typescript-eslint/eslint-recommended', - 'plugin:@typescript-eslint/recommended', - ], -}; diff --git a/js/common/lib/tensor-conversion-impl.ts b/js/common/lib/tensor-conversion-impl.ts index 743d0e6b352c6..7d34fc723a43d 100644 --- a/js/common/lib/tensor-conversion-impl.ts +++ b/js/common/lib/tensor-conversion-impl.ts @@ -88,7 +88,7 @@ export const tensorToDataURL = (tensor: Tensor, options?: TensorToDataUrlOptions const G = ((tensor.data[gTensorPointer++] as number) - normBias[1]) * normMean[1]; // G value const B = ((tensor.data[bTensorPointer++] as number) - normBias[2]) * normMean[2]; // B value const A = aTensorPointer === -1 ? 255 : ((tensor.data[aTensorPointer++] as number) - normBias[3]) * normMean[3]; // A value - // eslint-disable-next-line @typescript-eslint/restrict-plus-operands + pixels2DContext.fillStyle = 'rgba(' + R + ',' + G + ',' + B + ',' + A + ')'; pixels2DContext.fillRect(j, i, 1, 1); } diff --git a/js/common/package-lock.json b/js/common/package-lock.json index 8b8fe876a16d1..fca226a2962a7 100644 --- a/js/common/package-lock.json +++ b/js/common/package-lock.json @@ -9,9 +9,61 @@ "version": "1.24.0", "license": "MIT", "devDependencies": { + "globby": "^15.0.0", "typedoc": "^0.25.7" } }, + "node_modules/@nodelib/fs.scandir": { + "version": "2.1.5", + "resolved": "https://registry.npmjs.org/@nodelib/fs.scandir/-/fs.scandir-2.1.5.tgz", + "integrity": "sha512-vq24Bq3ym5HEQm2NKCr3yXDwjc7vTsEThRDnkp2DK9p1uqLR+DHurm/NOTo0KG7HYHU7eppKZj3MyqYuMBf62g==", + "dev": true, + "license": "MIT", + "dependencies": { + "@nodelib/fs.stat": "2.0.5", + "run-parallel": "^1.1.9" + }, + "engines": { + "node": ">= 8" + } + }, + "node_modules/@nodelib/fs.stat": { + "version": "2.0.5", + "resolved": "https://registry.npmjs.org/@nodelib/fs.stat/-/fs.stat-2.0.5.tgz", + "integrity": "sha512-RkhPPp2zrqDAQA/2jNhnztcPAlv64XdhIp7a7454A5ovI7Bukxgt7MX7udwAu3zg1DcpPU0rz3VV1SeaqvY4+A==", + "dev": true, + "license": "MIT", + "engines": { + "node": ">= 8" + } + }, + "node_modules/@nodelib/fs.walk": { + "version": "1.2.8", 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"funding": [ + { + "type": "github", + "url": "https://github.com/sponsors/feross" + }, + { + "type": "patreon", + "url": "https://www.patreon.com/feross" + }, + { + "type": "consulting", + "url": "https://feross.org/support" + } + ], + "license": "MIT" + }, + "node_modules/reusify": { + "version": "1.1.0", + "resolved": "https://registry.npmjs.org/reusify/-/reusify-1.1.0.tgz", + "integrity": "sha512-g6QUff04oZpHs0eG5p83rFLhHeV00ug/Yf9nZM6fLeUrPguBTkTQOdpAWWspMh55TZfVQDPaN3NQJfbVRAxdIw==", + "dev": true, + "license": "MIT", + "engines": { + "iojs": ">=1.0.0", + "node": ">=0.10.0" + } + }, + "node_modules/run-parallel": { + "version": "1.2.0", + "resolved": "https://registry.npmjs.org/run-parallel/-/run-parallel-1.2.0.tgz", + "integrity": "sha512-5l4VyZR86LZ/lDxZTR6jqL8AFE2S0IFLMP26AbjsLVADxHdhB/c0GUsH+y39UfCi3dzz8OlQuPmnaJOMoDHQBA==", + "dev": true, + "funding": [ + { + "type": "github", + "url": "https://github.com/sponsors/feross" + }, + { + "type": "patreon", + "url": 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"dev": true, + "license": "MIT", + "dependencies": { + "is-number": "^7.0.0" + }, + "engines": { + "node": ">=8.0" + } + }, "node_modules/typedoc": { "version": "0.25.7", "resolved": "https://registry.npmjs.org/typedoc/-/typedoc-0.25.7.tgz", @@ -120,6 +434,19 @@ "node": ">=14.17" } }, + "node_modules/unicorn-magic": { + "version": "0.3.0", + "resolved": "https://registry.npmjs.org/unicorn-magic/-/unicorn-magic-0.3.0.tgz", + "integrity": "sha512-+QBBXBCvifc56fsbuxZQ6Sic3wqqc3WWaqxs58gvJrcOuN83HGTCwz3oS5phzU9LthRNE9VrJCFCLUgHeeFnfA==", + "dev": true, + "license": "MIT", + "engines": { + "node": ">=18" + }, + "funding": { + "url": "https://github.com/sponsors/sindresorhus" + } + }, "node_modules/vscode-oniguruma": { "version": "1.7.0", "resolved": "https://registry.npmjs.org/vscode-oniguruma/-/vscode-oniguruma-1.7.0.tgz", @@ -134,6 +461,38 @@ } }, "dependencies": { + "@nodelib/fs.scandir": { + "version": "2.1.5", + "resolved": "https://registry.npmjs.org/@nodelib/fs.scandir/-/fs.scandir-2.1.5.tgz", + "integrity": "sha512-vq24Bq3ym5HEQm2NKCr3yXDwjc7vTsEThRDnkp2DK9p1uqLR+DHurm/NOTo0KG7HYHU7eppKZj3MyqYuMBf62g==", + "dev": true, + "requires": { + "@nodelib/fs.stat": "2.0.5", + "run-parallel": "^1.1.9" + } + }, + "@nodelib/fs.stat": { + "version": "2.0.5", + "resolved": "https://registry.npmjs.org/@nodelib/fs.stat/-/fs.stat-2.0.5.tgz", + "integrity": "sha512-RkhPPp2zrqDAQA/2jNhnztcPAlv64XdhIp7a7454A5ovI7Bukxgt7MX7udwAu3zg1DcpPU0rz3VV1SeaqvY4+A==", + "dev": true + }, + "@nodelib/fs.walk": { + "version": "1.2.8", + "resolved": "https://registry.npmjs.org/@nodelib/fs.walk/-/fs.walk-1.2.8.tgz", + "integrity": "sha512-oGB+UxlgWcgQkgwo8GcEGwemoTFt3FIO9ababBmaGwXIoBKZ+GTy0pP185beGg7Llih/NSHSV2XAs1lnznocSg==", + "dev": true, + "requires": { + "@nodelib/fs.scandir": "2.1.5", + "fastq": "^1.6.0" + } + }, + "@sindresorhus/merge-streams": { + "version": "4.0.0", + "resolved": "https://registry.npmjs.org/@sindresorhus/merge-streams/-/merge-streams-4.0.0.tgz", + "integrity": "sha512-tlqY9xq5ukxTUZBmoOp+m61cqwQD5pHJtFY3Mn8CA8ps6yghLH/Hw8UPdqg4OLmFW3IFlcXnQNmo/dh8HzXYIQ==", + "dev": true + }, "ansi-sequence-parser": { "version": "1.1.1", "resolved": "https://registry.npmjs.org/ansi-sequence-parser/-/ansi-sequence-parser-1.1.1.tgz", @@ -155,6 +514,96 @@ "balanced-match": "^1.0.0" } }, + "braces": { + "version": "3.0.3", + "resolved": "https://registry.npmjs.org/braces/-/braces-3.0.3.tgz", + "integrity": "sha512-yQbXgO/OSZVD2IsiLlro+7Hf6Q18EJrKSEsdoMzKePKXct3gvD8oLcOQdIzGupr5Fj+EDe8gO/lxc1BzfMpxvA==", + "dev": true, + "requires": { + "fill-range": "^7.1.1" + } + }, + "fast-glob": { + "version": "3.3.3", + "resolved": "https://registry.npmjs.org/fast-glob/-/fast-glob-3.3.3.tgz", + "integrity": "sha512-7MptL8U0cqcFdzIzwOTHoilX9x5BrNqye7Z/LuC7kCMRio1EMSyqRK3BEAUD7sXRq4iT4AzTVuZdhgQ2TCvYLg==", + "dev": true, + "requires": { + "@nodelib/fs.stat": "^2.0.2", + "@nodelib/fs.walk": "^1.2.3", + "glob-parent": "^5.1.2", + "merge2": "^1.3.0", + "micromatch": "^4.0.8" + } + }, + "fastq": { + "version": "1.19.1", + "resolved": "https://registry.npmjs.org/fastq/-/fastq-1.19.1.tgz", + "integrity": "sha512-GwLTyxkCXjXbxqIhTsMI2Nui8huMPtnxg7krajPJAjnEG/iiOS7i+zCtWGZR9G0NBKbXKh6X9m9UIsYX/N6vvQ==", + "dev": true, + "requires": { + "reusify": "^1.0.4" + } + }, + "fill-range": { + "version": "7.1.1", + "resolved": "https://registry.npmjs.org/fill-range/-/fill-range-7.1.1.tgz", + "integrity": "sha512-YsGpe3WHLK8ZYi4tWDg2Jy3ebRz2rXowDxnld4bkQB00cc/1Zw9AWnC0i9ztDJitivtQvaI9KaLyKrc+hBW0yg==", + "dev": true, + "requires": { + "to-regex-range": "^5.0.1" + } + }, + "glob-parent": { + "version": "5.1.2", + "resolved": "https://registry.npmjs.org/glob-parent/-/glob-parent-5.1.2.tgz", + "integrity": "sha512-AOIgSQCepiJYwP3ARnGx+5VnTu2HBYdzbGP45eLw1vr3zB3vZLeyed1sC9hnbcOc9/SrMyM5RPQrkGz4aS9Zow==", + "dev": true, + "requires": { + "is-glob": "^4.0.1" + } + }, + "globby": { + "version": "15.0.0", + "resolved": "https://registry.npmjs.org/globby/-/globby-15.0.0.tgz", + "integrity": "sha512-oB4vkQGqlMl682wL1IlWd02tXCbquGWM4voPEI85QmNKCaw8zGTm1f1rubFgkg3Eli2PtKlFgrnmUqasbQWlkw==", + "dev": true, + "requires": { + "@sindresorhus/merge-streams": "^4.0.0", + "fast-glob": "^3.3.3", + "ignore": "^7.0.5", + "path-type": "^6.0.0", + "slash": "^5.1.0", + "unicorn-magic": "^0.3.0" + } + }, + "ignore": { + "version": "7.0.5", + "resolved": "https://registry.npmjs.org/ignore/-/ignore-7.0.5.tgz", + "integrity": "sha512-Hs59xBNfUIunMFgWAbGX5cq6893IbWg4KnrjbYwX3tx0ztorVgTDA6B2sxf8ejHJ4wz8BqGUMYlnzNBer5NvGg==", + "dev": true + }, + "is-extglob": { + "version": "2.1.1", + "resolved": "https://registry.npmjs.org/is-extglob/-/is-extglob-2.1.1.tgz", + "integrity": "sha512-SbKbANkN603Vi4jEZv49LeVJMn4yGwsbzZworEoyEiutsN3nJYdbO36zfhGJ6QEDpOZIFkDtnq5JRxmvl3jsoQ==", + "dev": true + }, + "is-glob": { + "version": "4.0.3", + "resolved": "https://registry.npmjs.org/is-glob/-/is-glob-4.0.3.tgz", + "integrity": "sha512-xelSayHH36ZgE7ZWhli7pW34hNbNl8Ojv5KVmkJD4hBdD3th8Tfk9vYasLM+mXWOZhFkgZfxhLSnrwRr4elSSg==", + "dev": true, + "requires": { + "is-extglob": "^2.1.1" + } + }, + "is-number": { + "version": "7.0.0", + "resolved": "https://registry.npmjs.org/is-number/-/is-number-7.0.0.tgz", + "integrity": "sha512-41Cifkg6e8TylSpdtTpeLVMqvSBEVzTttHvERD741+pnZ8ANv0004MRL43QKPDlK9cGvNp6NZWZUBlbGXYxxng==", + "dev": true + }, "jsonc-parser": { "version": "3.2.1", "resolved": "https://registry.npmjs.org/jsonc-parser/-/jsonc-parser-3.2.1.tgz", @@ -173,6 +622,22 @@ "integrity": "sha512-PRsaiG84bK+AMvxziE/lCFss8juXjNaWzVbN5tXAm4XjeaS9NAHhop+PjQxz2A9h8Q4M/xGmzP8vqNwy6JeK0A==", "dev": true }, + "merge2": { + "version": "1.4.1", + "resolved": "https://registry.npmjs.org/merge2/-/merge2-1.4.1.tgz", + "integrity": "sha512-8q7VEgMJW4J8tcfVPy8g09NcQwZdbwFEqhe/WZkoIzjn/3TGDwtOCYtXGxA3O8tPzpczCCDgv+P2P5y00ZJOOg==", + "dev": true + }, + "micromatch": { + "version": "4.0.8", + "resolved": "https://registry.npmjs.org/micromatch/-/micromatch-4.0.8.tgz", + "integrity": "sha512-PXwfBhYu0hBCPw8Dn0E+WDYb7af3dSLVWKi3HGv84IdF4TyFoC0ysxFd0Goxw7nSv4T/PzEJQxsYsEiFCKo2BA==", + "dev": true, + "requires": { + "braces": "^3.0.3", + "picomatch": "^2.3.1" + } + }, "minimatch": { "version": "9.0.3", "resolved": "https://registry.npmjs.org/minimatch/-/minimatch-9.0.3.tgz", @@ -182,6 +647,39 @@ "brace-expansion": "^2.0.1" } }, + "path-type": { + "version": "6.0.0", + "resolved": "https://registry.npmjs.org/path-type/-/path-type-6.0.0.tgz", + "integrity": "sha512-Vj7sf++t5pBD637NSfkxpHSMfWaeig5+DKWLhcqIYx6mWQz5hdJTGDVMQiJcw1ZYkhs7AazKDGpRVji1LJCZUQ==", + "dev": true + }, + "picomatch": { + "version": "2.3.1", + "resolved": "https://registry.npmjs.org/picomatch/-/picomatch-2.3.1.tgz", + "integrity": "sha512-JU3teHTNjmE2VCGFzuY8EXzCDVwEqB2a8fsIvwaStHhAWJEeVd1o1QD80CU6+ZdEXXSLbSsuLwJjkCBWqRQUVA==", + "dev": true + }, + "queue-microtask": { + "version": "1.2.3", + "resolved": "https://registry.npmjs.org/queue-microtask/-/queue-microtask-1.2.3.tgz", + "integrity": "sha512-NuaNSa6flKT5JaSYQzJok04JzTL1CA6aGhv5rfLW3PgqA+M2ChpZQnAC8h8i4ZFkBS8X5RqkDBHA7r4hej3K9A==", + "dev": true + }, + "reusify": { + "version": "1.1.0", + "resolved": "https://registry.npmjs.org/reusify/-/reusify-1.1.0.tgz", + "integrity": "sha512-g6QUff04oZpHs0eG5p83rFLhHeV00ug/Yf9nZM6fLeUrPguBTkTQOdpAWWspMh55TZfVQDPaN3NQJfbVRAxdIw==", + "dev": true + }, + "run-parallel": { + "version": "1.2.0", + "resolved": "https://registry.npmjs.org/run-parallel/-/run-parallel-1.2.0.tgz", + "integrity": "sha512-5l4VyZR86LZ/lDxZTR6jqL8AFE2S0IFLMP26AbjsLVADxHdhB/c0GUsH+y39UfCi3dzz8OlQuPmnaJOMoDHQBA==", + "dev": true, + "requires": { + "queue-microtask": "^1.2.2" + } + }, "shiki": { "version": "0.14.7", "resolved": "https://registry.npmjs.org/shiki/-/shiki-0.14.7.tgz", @@ -194,6 +692,21 @@ "vscode-textmate": "^8.0.0" } }, + "slash": { + "version": "5.1.0", + "resolved": "https://registry.npmjs.org/slash/-/slash-5.1.0.tgz", + "integrity": "sha512-ZA6oR3T/pEyuqwMgAKT0/hAv8oAXckzbkmR0UkUosQ+Mc4RxGoJkRmwHgHufaenlyAgE1Mxgpdcrf75y6XcnDg==", + "dev": true + }, + "to-regex-range": { + "version": "5.0.1", + "resolved": "https://registry.npmjs.org/to-regex-range/-/to-regex-range-5.0.1.tgz", + "integrity": "sha512-65P7iz6X5yEr1cwcgvQxbbIw7Uk3gOy5dIdtZ4rDveLqhrdJP+Li/Hx6tyK0NEb+2GCyneCMJiGqrADCSNk8sQ==", + "dev": true, + "requires": { + "is-number": "^7.0.0" + } + }, "typedoc": { "version": "0.25.7", "resolved": "https://registry.npmjs.org/typedoc/-/typedoc-0.25.7.tgz", @@ -213,6 +726,12 @@ "dev": true, "peer": true }, + "unicorn-magic": { + "version": "0.3.0", + "resolved": "https://registry.npmjs.org/unicorn-magic/-/unicorn-magic-0.3.0.tgz", + "integrity": "sha512-+QBBXBCvifc56fsbuxZQ6Sic3wqqc3WWaqxs58gvJrcOuN83HGTCwz3oS5phzU9LthRNE9VrJCFCLUgHeeFnfA==", + "dev": true + }, "vscode-oniguruma": { "version": "1.7.0", "resolved": "https://registry.npmjs.org/vscode-oniguruma/-/vscode-oniguruma-1.7.0.tgz", diff --git a/js/common/package.json b/js/common/package.json index df1e50f995390..c96a750530d4a 100644 --- a/js/common/package.json +++ b/js/common/package.json @@ -19,6 +19,7 @@ "test:f16": "mocha -n js-float16array \"./test/**/*.js\" --timeout 30000" }, "devDependencies": { + "globby": "^15.0.0", "typedoc": "^0.25.7" }, "main": "dist/cjs/index.js", diff --git a/js/common/test/type-tests.ts b/js/common/test/type-tests.ts index 70681bb420e5f..a4bab8a804eeb 100644 --- a/js/common/test/type-tests.ts +++ b/js/common/test/type-tests.ts @@ -1,7 +1,7 @@ // Copyright (c) Microsoft Corporation. All rights reserved. // Licensed under the MIT License. -import globby from 'globby'; +import { globbySync } from 'globby'; import assert from 'node:assert'; import { readFileSync } from 'node:fs'; import { dirname, join, normalize, relative } from 'node:path'; @@ -47,7 +47,7 @@ const TYPE_TESTS_DIR = join(dirname(fileURLToPath(import.meta.url)), './type-tes */ const prepareTestFileList = () => // - globby.sync('**/*.ts', { + globbySync('**/*.ts', { cwd: TYPE_TESTS_DIR, absolute: true, }); diff --git a/js/eslint.config.mjs b/js/eslint.config.mjs new file mode 100644 index 0000000000000..dde4a4dd76eca --- /dev/null +++ b/js/eslint.config.mjs @@ -0,0 +1,364 @@ +// Copyright (c) Microsoft Corporation. All rights reserved. +// Licensed under the MIT License. + +import typescriptEslint from '@typescript-eslint/eslint-plugin'; +import preferArrow from 'eslint-plugin-prefer-arrow'; +import header from 'eslint-plugin-header'; +import _import from 'eslint-plugin-import'; +import unicorn from 'eslint-plugin-unicorn'; +import jsdoc from 'eslint-plugin-jsdoc'; +import { fixupPluginRules } from '@eslint/compat'; +import tsParser from '@typescript-eslint/parser'; +import globals from 'globals'; +import path from 'node:path'; +import { fileURLToPath } from 'node:url'; +import js from '@eslint/js'; +import { FlatCompat } from '@eslint/eslintrc'; + +const __filename = fileURLToPath(import.meta.url); +const __dirname = path.dirname(__filename); +const compat = new FlatCompat({ + baseDirectory: __dirname, + recommendedConfig: js.configs.recommended, + allConfig: js.configs.all, +}); + +// eslint-plugin-header does not support ESLint 9 yet, but the following workaround is available: +// https://github.com/Stuk/eslint-plugin-header/issues/57#issuecomment-2378485611 +header.rules.header.meta.schema = false; + +export default [ + { + ignores: [ + '**/*.js', + '**/*.mjs', + 'eslint.config.mjs', + '**/node_modules/', + '**/ort-schema/', + 'common/test/type-tests/', + 'web/types.d.ts', + 'test/data/', + '**/dist/', + ], + }, + ...compat.extends( + 'eslint:recommended', + 'plugin:@typescript-eslint/eslint-recommended', + 'plugin:@typescript-eslint/recommended', + ), + { + plugins: { + '@typescript-eslint': typescriptEslint, + 'prefer-arrow': preferArrow, + header, + import: fixupPluginRules(_import), + unicorn, + jsdoc, + }, + + languageOptions: { + globals: {}, + parser: tsParser, + ecmaVersion: 5, + sourceType: 'module', + + parserOptions: { + project: true, + }, + }, + + rules: { + 'unicorn/filename-case': 'error', + + 'header/header': [ + 2, + 'line', + [' Copyright (c) Microsoft Corporation. All rights reserved.', ' Licensed under the MIT License.'], + 2, + ], + + 'import/no-extraneous-dependencies': [ + 'error', + { + devDependencies: false, + }, + ], + + 'import/no-internal-modules': [ + 'error', + { + allow: ['**/lib/**'], + }, + ], + + 'import/no-unassigned-import': 'error', + + '@typescript-eslint/array-type': [ + 'error', + { + default: 'array-simple', + }, + ], + + '@typescript-eslint/await-thenable': 'error', + + '@typescript-eslint/no-empty-object-type': 'error', + + '@typescript-eslint/no-wrapper-object-types': 'error', + + '@typescript-eslint/naming-convention': 'error', + '@typescript-eslint/consistent-type-assertions': 'error', + + '@typescript-eslint/no-empty-function': 'error', + '@typescript-eslint/no-explicit-any': 'error', + '@typescript-eslint/no-floating-promises': 'error', + '@typescript-eslint/no-for-in-array': 'error', + '@typescript-eslint/no-inferrable-types': 'error', + '@typescript-eslint/no-misused-new': 'error', + + '@typescript-eslint/no-namespace': [ + 'error', + { + allowDeclarations: true, + }, + ], + + '@typescript-eslint/no-non-null-assertion': 'off', + + '@typescript-eslint/no-require-imports': [ + 'error', + { + allow: ['^node:'], + }, + ], + + '@typescript-eslint/no-var-requires': [ + 'error', + { + allow: ['^node:'], + }, + ], + + '@typescript-eslint/no-unnecessary-type-assertion': 'error', + + '@typescript-eslint/no-unused-vars': [ + 'error', + { + argsIgnorePattern: '^_', + }, + ], + + '@typescript-eslint/promise-function-async': 'error', + '@typescript-eslint/restrict-plus-operands': 'error', + + '@typescript-eslint/triple-slash-reference': [ + 'error', + { + path: 'always', + types: 'prefer-import', + lib: 'always', + }, + ], + + 'arrow-body-style': 'error', + camelcase: 'error', + 'constructor-super': 'error', + curly: 'error', + 'default-case': 'error', + 'dot-notation': 'error', + eqeqeq: ['error', 'smart'], + 'guard-for-in': 'error', + 'id-match': 'error', + 'new-parens': 'error', + 'no-bitwise': 'error', + 'no-caller': 'error', + 'no-cond-assign': 'error', + 'no-console': 'error', + 'no-constant-condition': 'error', + 'no-control-regex': 'error', + 'no-debugger': 'error', + 'no-duplicate-case': 'error', + 'no-empty': 'error', + 'no-eval': 'error', + 'no-extra-bind': 'error', + 'no-invalid-regexp': 'error', + 'no-invalid-this': 'error', + 'no-multiple-empty-lines': 'error', + 'no-new-func': 'error', + 'no-new-wrappers': 'error', + 'no-octal': 'error', + 'no-octal-escape': 'error', + 'no-param-reassign': 'error', + 'no-redeclare': 'off', + '@typescript-eslint/no-redeclare': ['error'], + 'no-regex-spaces': 'error', + 'no-return-await': 'error', + 'no-sparse-arrays': 'error', + 'no-template-curly-in-string': 'error', + 'no-throw-literal': 'error', + 'no-undef-init': 'error', + 'no-underscore-dangle': 'error', + 'no-unsafe-finally': 'error', + 'no-unused-expressions': 'error', + 'no-unused-labels': 'error', + 'no-use-before-define': 'off', + '@typescript-eslint/no-use-before-define': 'error', + 'no-var': 'error', + 'object-shorthand': 'error', + 'prefer-arrow/prefer-arrow-functions': 'error', + 'prefer-const': 'error', + radix: 'error', + 'use-isnan': 'error', + }, + }, + { + files: ['node/**/*.ts'], + + languageOptions: { + globals: { + ...globals.node, + }, + }, + }, + { + files: ['common/lib/**/*.ts', 'node/lib/**/*.ts'], + + rules: { + 'jsdoc/check-alignment': 'error', + 'jsdoc/check-indentation': 'error', + }, + }, + { + files: ['common/test/**/*.ts'], + + rules: { + '@typescript-eslint/naming-convention': 'off', + 'import/no-extraneous-dependencies': 'off', + }, + }, + { + files: ['node/script/**/*.ts', 'node/test/**/*.ts', 'web/script/**/*.ts', 'web/test/**/*.ts'], + + rules: { + '@typescript-eslint/naming-convention': 'off', + '@typescript-eslint/no-empty-function': 'off', + '@typescript-eslint/no-explicit-any': 'off', + '@typescript-eslint/no-require-imports': 'off', + '@typescript-eslint/no-var-requires': 'off', + '@typescript-eslint/no-unnecessary-type-assertion': 'off', + camelcase: 'off', + 'prefer-arrow/prefer-arrow-functions': 'off', + 'import/no-extraneous-dependencies': 'off', + 'import/no-unassigned-import': 'off', + 'import/no-internal-modules': 'off', + 'no-console': 'off', + 'no-empty': 'off', + 'no-unused-expressions': 'off', + }, + }, + { + files: ['web/lib/**/*.ts'], + + rules: { + 'no-underscore-dangle': [ + 'error', + { + allow: [ + '_free', + '_malloc', + '_JsepGetNodeName', + '_JsepOutput', + '_OrtAddFreeDimensionOverride', + '_OrtAddRunConfigEntry', + '_OrtAddSessionConfigEntry', + '_OrtAppendExecutionProvider', + '_OrtBindInput', + '_OrtBindOutput', + '_OrtClearBoundOutputs', + '_OrtCreateBinding', + '_OrtCreateRunOptions', + '_OrtCreateSession', + '_OrtCreateSessionOptions', + '_OrtCreateTensor', + '_OrtEndProfiling', + '_OrtFree', + '_OrtGetInputName', + '_OrtGetInputOutputCount', + '_OrtGetInputOutputMetadata', + '_OrtGetLastError', + '_OrtGetOutputName', + '_OrtGetTensorData', + '_OrtInit', + '_OrtReleaseBinding', + '_OrtReleaseRunOptions', + '_OrtReleaseSession', + '_OrtReleaseSessionOptions', + '_OrtReleaseTensor', + '_OrtRun', + '_OrtRunWithBinding', + ], + }, + ], + }, + }, + { + files: ['web/lib/onnxjs/**/*.ts'], + + rules: { + '@typescript-eslint/no-empty-function': 'off', + '@typescript-eslint/explicit-module-boundary-types': 'off', + '@typescript-eslint/no-use-before-define': 'off', + '@typescript-eslint/no-unnecessary-type-assertion': 'off', + '@typescript-eslint/restrict-plus-operands': 'off', + 'import/no-internal-modules': 'off', + 'prefer-arrow/prefer-arrow-functions': 'off', + 'no-param-reassign': 'off', + 'no-underscore-dangle': 'off', + 'guard-for-in': 'off', + }, + }, + { + files: ['react_native/e2e/src/**/*.ts', 'react_native/e2e/src/**/*.tsx'], + + rules: { + '@typescript-eslint/no-non-null-assertion': 'off', + '@typescript-eslint/no-unnecessary-type-assertion': 'off', + 'unicorn/filename-case': 'off', + 'no-invalid-this': 'off', + 'no-console': 'off', + }, + }, + { + files: ['react_native/lib/**/*.ts'], + + rules: { + '@typescript-eslint/naming-convention': 'off', + }, + }, + { + files: ['react_native/scripts/**/*.ts'], + + rules: { + 'import/no-extraneous-dependencies': 'off', + 'prefer-arrow/prefer-arrow-functions': 'off', + 'no-console': 'off', + }, + }, + { + files: ['scripts/**/*.ts'], + + rules: { + 'import/no-extraneous-dependencies': 'off', + 'no-console': 'off', + }, + }, + { + files: ['web/lib/**/3rd-party/**/*.ts'], + + rules: { + 'header/header': 'off', + 'unicorn/filename-case': 'off', + '@typescript-eslint/explicit-module-boundary-types': 'off', + }, + }, +]; diff --git a/js/node/test/test-utils.ts b/js/node/test/test-utils.ts index 72ed2c3db2b6e..eecb8f1da0133 100644 --- a/js/node/test/test-utils.ts +++ b/js/node/test/test-utils.ts @@ -88,7 +88,7 @@ export function warmup(): void { try { const session = await InferenceSession.create(path.join(TEST_DATA_ROOT, 'test_types_int32.onnx')); await session.run({ input: new Tensor(new Float32Array(5), [1, 5]) }, { output: null }, {}); - } catch (e) {} + } catch {} }); } diff --git a/js/node/test/unittests/lib/tensor.ts b/js/node/test/unittests/lib/tensor.ts index 9e09c4e816fba..844292df076a2 100644 --- a/js/node/test/unittests/lib/tensor.ts +++ b/js/node/test/unittests/lib/tensor.ts @@ -72,7 +72,11 @@ describe('UnitTests - tensor', () => { assert.throws( () => { const badDims = {}; - passtypeParam ? new TensorAny(type, data, badDims) : new TensorAny(data, badDims); + if (passtypeParam) { + new TensorAny(type, data, badDims); + } else { + new TensorAny(data, badDims); + } }, { name: 'TypeError', message: /must be a number array/ }, ); @@ -82,7 +86,11 @@ describe('UnitTests - tensor', () => { assert.throws( () => { const badDims = [1, 2, '']; - passtypeParam ? new TensorAny(type, data, badDims) : new TensorAny(data, badDims); + if (passtypeParam) { + new TensorAny(type, data, badDims); + } else { + new TensorAny(data, badDims); + } }, { name: 'TypeError', message: /must be an integer/ }, ); @@ -92,7 +100,11 @@ describe('UnitTests - tensor', () => { assert.throws( () => { const badDims = [1, 2, -1]; - passtypeParam ? new TensorAny(type, data, badDims) : new TensorAny(data, badDims); + if (passtypeParam) { + new TensorAny(type, data, badDims); + } else { + new TensorAny(data, badDims); + } }, { name: 'RangeError', message: /must be a non-negative integer/ }, ); @@ -102,7 +114,11 @@ describe('UnitTests - tensor', () => { assert.throws( () => { const badDims = [1, 2, 1.5]; - passtypeParam ? new TensorAny(type, data, badDims) : new TensorAny(data, badDims); + if (passtypeParam) { + new TensorAny(type, data, badDims); + } else { + new TensorAny(data, badDims); + } }, { name: 'TypeError', message: /must be an integer/ }, ); @@ -113,7 +129,11 @@ describe('UnitTests - tensor', () => { assert.throws( () => { const badDims = [10, 8]; - passtypeParam ? new TensorAny(type, data, badDims) : new TensorAny(data, badDims); + if (passtypeParam) { + new TensorAny(type, data, badDims); + } else { + new TensorAny(data, badDims); + } }, { name: 'Error', message: /does not match data length/ }, ); diff --git a/js/package-lock.json b/js/package-lock.json index 76f5bd57d0fdf..a13f1ae373f4b 100644 --- a/js/package-lock.json +++ b/js/package-lock.json @@ -4,28 +4,31 @@ "requires": true, "packages": { "": { - "name": "js", "license": "MIT", "devDependencies": { + "@eslint/compat": "^1.4.0", + "@eslint/eslintrc": "^3.3.1", + "@eslint/js": "^9.38.0", "@types/fs-extra": "^11.0.4", "@types/global-agent": "^2.1.3", "@types/mocha": "^10.0.2", - "@types/node": "^18.14.6", + "@types/node": "^20.10.0", "@types/npmlog": "^4.1.4", - "@typescript-eslint/eslint-plugin": "^7.4.0", - "@typescript-eslint/parser": "^7.4.0", + "@typescript-eslint/eslint-plugin": "^8.46.2", + "@typescript-eslint/parser": "^8.46.2", "dir-compare": "^4.2.0", "esbuild": "^0.25.0", "esbuild-plugin-polyfill-node": "^0.3.0", - "eslint": "^8.51.0", + "eslint": "^9.38.0", "eslint-config-prettier": "^9.1.0", "eslint-plugin-header": "^3.1.1", - "eslint-plugin-import": "^2.28.1", - "eslint-plugin-jsdoc": "^46.8.2", + "eslint-plugin-import": "^2.32.0", + "eslint-plugin-jsdoc": "^61.1.9", "eslint-plugin-prefer-arrow": "^1.2.3", - "eslint-plugin-unicorn": "^48.0.1", + "eslint-plugin-unicorn": "^62.0.0", "fs-extra": "^11.2.0", "global-agent": "^3.0", + "globals": "^16.4.0", "jszip": "^3.10.1", "mocha": "^11.0.1", "npmlog": "^7.0.1", @@ -43,124 +46,41 @@ "node": ">=0.10.0" } }, - "node_modules/@babel/code-frame": { - "version": "7.18.6", - "resolved": "https://registry.npmjs.org/@babel/code-frame/-/code-frame-7.18.6.tgz", - "integrity": "sha512-TDCmlK5eOvH+eH7cdAFlNXeVJqWIQ7gW9tY1GJIpUtFb6CmjVyq2VM3u71bOyR8CRihcCgMUYoDNyLXao3+70Q==", - "dev": true, - "dependencies": { - "@babel/highlight": "^7.18.6" - }, - "engines": { - "node": ">=6.9.0" - } - }, "node_modules/@babel/helper-validator-identifier": { - "version": 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"get-proto": "^1.0.1", + "gopd": "^1.2.0", + "has-tostringtag": "^1.0.2" } }, "wide-align": { @@ -8850,24 +9899,12 @@ "strip-ansi": "^6.0.0" } }, - "wrappy": { - "version": "1.0.2", - "resolved": "https://registry.npmjs.org/wrappy/-/wrappy-1.0.2.tgz", - "integrity": "sha512-l4Sp/DRseor9wL6EvV2+TuQn63dMkPjZ/sp9XkghTEbV9KlPS1xUsZ3u7/IQO4wxtcFB4bgpQPRcR3QCvezPcQ==", - "dev": true - }, "y18n": { "version": "5.0.8", "resolved": "https://registry.npmjs.org/y18n/-/y18n-5.0.8.tgz", "integrity": "sha512-0pfFzegeDWJHJIAmTLRP2DwHjdF5s7jo9tuztdQxAhINCdvS+3nGINqPd00AphqJR/0LhANUS6/+7SCb98YOfA==", "dev": true }, - "yallist": { - "version": "4.0.0", - "resolved": "https://registry.npmjs.org/yallist/-/yallist-4.0.0.tgz", - "integrity": "sha512-3wdGidZyq5PB084XLES5TpOSRA3wjXAlIWMhum2kRcv/41Sn2emQ0dycQW4uZXLejwKvg6EsvbdlVL+FYEct7A==", - "dev": true - }, "yargs": { "version": "16.2.0", "resolved": "https://registry.npmjs.org/yargs/-/yargs-16.2.0.tgz", diff --git a/js/package.json b/js/package.json index 11bed50375b95..cb8b09f4247a6 100644 --- a/js/package.json +++ b/js/package.json @@ -1,24 +1,28 @@ { "devDependencies": { + "@eslint/compat": "^1.4.0", + "@eslint/eslintrc": "^3.3.1", + "@eslint/js": "^9.38.0", "@types/fs-extra": "^11.0.4", "@types/global-agent": "^2.1.3", "@types/mocha": "^10.0.2", - "@types/node": "^18.14.6", + "@types/node": "^20.10.0", "@types/npmlog": "^4.1.4", - "@typescript-eslint/eslint-plugin": "^7.4.0", - "@typescript-eslint/parser": "^7.4.0", + "@typescript-eslint/eslint-plugin": "^8.46.2", + "@typescript-eslint/parser": "^8.46.2", "dir-compare": "^4.2.0", "esbuild": "^0.25.0", "esbuild-plugin-polyfill-node": "^0.3.0", - "eslint": "^8.51.0", + "eslint": "^9.38.0", "eslint-config-prettier": "^9.1.0", "eslint-plugin-header": "^3.1.1", - "eslint-plugin-import": "^2.28.1", - "eslint-plugin-jsdoc": "^46.8.2", + "eslint-plugin-import": "^2.32.0", + "eslint-plugin-jsdoc": "^61.1.9", "eslint-plugin-prefer-arrow": "^1.2.3", - "eslint-plugin-unicorn": "^48.0.1", + "eslint-plugin-unicorn": "^62.0.0", "fs-extra": "^11.2.0", "global-agent": "^3.0", + "globals": "^16.4.0", "jszip": "^3.10.1", "mocha": "^11.0.1", "npmlog": "^7.0.1", diff --git a/js/react_native/e2e/src/App.tsx b/js/react_native/e2e/src/App.tsx index 2d8d57b576991..39c496062f665 100644 --- a/js/react_native/e2e/src/App.tsx +++ b/js/react_native/e2e/src/App.tsx @@ -4,7 +4,6 @@ import * as React from 'react'; import { Image, Text, TextInput, View } from 'react-native'; // onnxruntime-react-native package is installed when bootstraping -// eslint-disable-next-line import/no-extraneous-dependencies import { InferenceSession, Tensor } from 'onnxruntime-react-native'; import MNIST, { MNISTInput, MNISTOutput, MNISTResult, } from './mnist-data-handler'; import { Buffer } from 'buffer'; @@ -19,9 +18,9 @@ interface State { string | null; } -// eslint-disable-next-line @typescript-eslint/ban-types +// eslint-disable-next-line @typescript-eslint/no-empty-object-type export default class App extends React.PureComponent<{}, State> { - // eslint-disable-next-line @typescript-eslint/ban-types + // eslint-disable-next-line @typescript-eslint/no-empty-object-type constructor(props: {} | Readonly<{}>) { super(props); diff --git a/js/react_native/lib/binding.ts b/js/react_native/lib/binding.ts index 9537b47f58fbe..91c65b1eb69e4 100644 --- a/js/react_native/lib/binding.ts +++ b/js/react_native/lib/binding.ts @@ -87,9 +87,7 @@ export const binding = Onnxruntime as Binding.InferenceSession; OnnxruntimeJSIHelper.install(); declare global { - // eslint-disable-next-line no-var var jsiOnnxruntimeStoreArrayBuffer: ((buffer: ArrayBuffer) => JSIBlob) | undefined; - // eslint-disable-next-line no-var var jsiOnnxruntimeResolveArrayBuffer: ((blob: JSIBlob) => ArrayBuffer) | undefined; } diff --git a/js/web/lib/backend-onnxjs.ts b/js/web/lib/backend-onnxjs.ts index 5aa799161f4bf..cc0ee01144728 100644 --- a/js/web/lib/backend-onnxjs.ts +++ b/js/web/lib/backend-onnxjs.ts @@ -1,7 +1,6 @@ // Copyright (c) Microsoft Corporation. All rights reserved. // Licensed under the MIT License. -/* eslint-disable import/no-internal-modules */ import { Backend, InferenceSession, InferenceSessionHandler } from 'onnxruntime-common'; import { Session } from './onnxjs/session'; diff --git a/js/web/lib/onnxjs/backends/webgl/webgl-context-factory.ts b/js/web/lib/onnxjs/backends/webgl/webgl-context-factory.ts index bbf05a7b75a28..ea6169578e32e 100644 --- a/js/web/lib/onnxjs/backends/webgl/webgl-context-factory.ts +++ b/js/web/lib/onnxjs/backends/webgl/webgl-context-factory.ts @@ -25,7 +25,7 @@ export function createWebGLContext(contextId?: 'webgl' | 'webgl2'): WebGLContext // try to create webgl context from an offscreen canvas const offscreenCanvas = createOffscreenCanvas(); context = createNewWebGLContext(offscreenCanvas, contextId); - } catch (e) { + } catch { // if failed, fallback to try to use a normal canvas element const canvas = createCanvas(); context = createNewWebGLContext(canvas, contextId); diff --git a/js/web/lib/onnxjs/execution-plan.ts b/js/web/lib/onnxjs/execution-plan.ts index 40d6417b22d3a..8847fa99ec498 100644 --- a/js/web/lib/onnxjs/execution-plan.ts +++ b/js/web/lib/onnxjs/execution-plan.ts @@ -156,8 +156,7 @@ export class ExecutionPlan { if (outputIndex === 0) { await outputTensor.getData(); } else { - // eslint-disable-next-line no-unused-expressions - outputTensor.data; + void outputTensor.data; } output.push(outputTensor); } diff --git a/js/web/lib/onnxjs/graph.ts b/js/web/lib/onnxjs/graph.ts index ec7e5b0b2748b..86d66c6c48aef 100644 --- a/js/web/lib/onnxjs/graph.ts +++ b/js/web/lib/onnxjs/graph.ts @@ -785,7 +785,7 @@ class GraphImpl implements Graph, Graph.Transformer { child.attributes.getFloat('min'), child.attributes.getFloat('max'), ]); - } catch (e) { + } catch { node.attributes.set('activation_params', 'floats', [MIN_CLIP, MAX_CLIP]); } } else if ( diff --git a/js/web/lib/onnxjs/util.ts b/js/web/lib/onnxjs/util.ts index b25e9ef33b38a..a2e048680a6ef 100644 --- a/js/web/lib/onnxjs/util.ts +++ b/js/web/lib/onnxjs/util.ts @@ -553,7 +553,6 @@ export class ShapeUtil { // size cannot be 0 or negative. if (dims[i] <= 0) { throw new Error( - // eslint-disable-next-line max-len 'cannot get valid size from specified dimension range. Most likely the range contains 0 or negative values in them.', ); } diff --git a/js/web/lib/wasm/jsep/util.ts b/js/web/lib/wasm/jsep/util.ts index 7f87a2475ac16..27a718ac2fcd6 100644 --- a/js/web/lib/wasm/jsep/util.ts +++ b/js/web/lib/wasm/jsep/util.ts @@ -163,7 +163,6 @@ export class ShapeUtil { // size cannot be negative. if (dims[i] < 0) { throw new Error( - // eslint-disable-next-line max-len 'cannot get valid size from specified dimension range. Most likely the range contains negative values in them.', ); } diff --git a/js/web/lib/wasm/jsep/webgpu/ops/binary-op.ts b/js/web/lib/wasm/jsep/webgpu/ops/binary-op.ts index c695a71568c97..bae737140466b 100644 --- a/js/web/lib/wasm/jsep/webgpu/ops/binary-op.ts +++ b/js/web/lib/wasm/jsep/webgpu/ops/binary-op.ts @@ -143,8 +143,8 @@ const createBinaryOpProgramInfo = ( additionalImplementation?: string, outputDataType: number = a.dataType, ): ProgramInfo => { - const aDims = a.dims.map((x) => Number(x) ?? 1); - const bDims = b.dims.map((x) => Number(x) ?? 1); + const aDims = a.dims.map(Number); + const bDims = b.dims.map(Number); const isBroadcast = !ShapeUtil.areEqual(aDims, bDims); let outputShape = aDims; let outputSize = ShapeUtil.size(aDims); diff --git a/js/web/lib/wasm/jsep/webgpu/ops/where.ts b/js/web/lib/wasm/jsep/webgpu/ops/where.ts index 30ea6d011b7d0..85caf7b69dd7c 100644 --- a/js/web/lib/wasm/jsep/webgpu/ops/where.ts +++ b/js/web/lib/wasm/jsep/webgpu/ops/where.ts @@ -31,7 +31,6 @@ const createWhereOpProgramShader = ( const singleAssignment = (resStr: string, x: number, typeCast = '') => { const expressionA = `a_data[index_a${x}][component_a${x}]`; const expressionB = `b_data[index_b${x}][component_b${x}]`; - // eslint-disable-next-line no-bitwise const expressionC = `bool(c_data[index_c${x}] & (0xffu << (component_c${x} * 8)))`; return ` let output_indices${x} = ${output.offsetToIndices(`global_idx * 4u + ${x}u`)}; diff --git a/js/web/lib/wasm/jsep/webnn/tensor-manager.ts b/js/web/lib/wasm/jsep/webnn/tensor-manager.ts index 70a2a9a892470..17a45fe9ae9c3 100644 --- a/js/web/lib/wasm/jsep/webnn/tensor-manager.ts +++ b/js/web/lib/wasm/jsep/webnn/tensor-manager.ts @@ -543,7 +543,6 @@ class TensorManagerImpl implements TensorManager { const context = this.getMLContext(sessionId); const tensorId = createNewTensorId(); // Defaulting to READ | WRITE if usage is not provided. - // eslint-disable-next-line no-bitwise const wrapper = new TensorWrapper({ sessionId, context, diff --git a/js/web/lib/wasm/jsep/webnn/webnn.d.ts b/js/web/lib/wasm/jsep/webnn/webnn.d.ts index 45485db3b5d9b..8a45a47a5b041 100644 --- a/js/web/lib/wasm/jsep/webnn/webnn.d.ts +++ b/js/web/lib/wasm/jsep/webnn/webnn.d.ts @@ -1,15 +1,15 @@ // Copyright (c) Microsoft Corporation. All rights reserved. // Licensed under the MIT License. -/* eslint-disable @typescript-eslint/naming-convention */ +/* eslint-disable @typescript-eslint/naming-convention, @typescript-eslint/no-empty-object-type */ interface NavigatorML { readonly ml: ML; } interface Navigator extends NavigatorML {} interface WorkerNavigator extends NavigatorML {} -type MLDeviceType = 'cpu'|'gpu'|'npu'; -type MLPowerPreference = 'default'|'high-performance'|'low-power'; +type MLDeviceType = 'cpu' | 'gpu' | 'npu'; +type MLPowerPreference = 'default' | 'high-performance' | 'low-power'; interface MLContextOptions { deviceType?: MLDeviceType; powerPreference?: MLPowerPreference; @@ -27,8 +27,18 @@ interface MLContext { compute(graph: MLGraph, inputs: MLNamedArrayBufferViews, outputs: MLNamedArrayBufferViews): Promise; } interface MLGraph {} -type MLInputOperandLayout = 'nchw'|'nhwc'; -type MLOperandDataType = 'float32'|'float16'|'int32'|'uint32'|'int64'|'uint64'|'int8'|'uint8'|'int4'|'uint4'; +type MLInputOperandLayout = 'nchw' | 'nhwc'; +type MLOperandDataType = + | 'float32' + | 'float16' + | 'int32' + | 'uint32' + | 'int64' + | 'uint64' + | 'int8' + | 'uint8' + | 'int4' + | 'uint4'; interface MLOperandDescriptor { dataType: MLOperandDataType; shape?: readonly number[]; @@ -43,7 +53,7 @@ interface MLActivation {} type MLNamedOperands = Record; interface MLGraphBuilder { // eslint-disable-next-line @typescript-eslint/no-misused-new - new(context: MLContext): MLGraphBuilder; + new (context: MLContext): MLGraphBuilder; input(name: string, descriptor: MLOperandDescriptor): MLOperand; constant(descriptor: MLOperandDescriptor, bufferView: ArrayBufferView): MLOperand; constant(type: MLOperandDataType, value: number): MLOperand; @@ -65,8 +75,12 @@ interface MLBatchNormalizationOptions { epsilon?: number; } interface MLGraphBuilder { - batchNormalization(input: MLOperand, mean: MLOperand, variance: MLOperand, options?: MLBatchNormalizationOptions): - MLOperand; + batchNormalization( + input: MLOperand, + mean: MLOperand, + variance: MLOperand, + options?: MLBatchNormalizationOptions, + ): MLOperand; } interface MLGraphBuilder { cast(input: MLOperand, type: MLOperandDataType): MLOperand; @@ -82,7 +96,7 @@ interface MLGraphBuilder { interface MLGraphBuilder { concat(inputs: MLOperand[], axis: number): MLOperand; } -type MLConv2dFilterOperandLayout = 'oihw'|'hwio'|'ohwi'|'ihwo'; +type MLConv2dFilterOperandLayout = 'oihw' | 'hwio' | 'ohwi' | 'ihwo'; interface MLConv2dOptions { padding?: number[]; strides?: number[]; @@ -95,7 +109,7 @@ interface MLConv2dOptions { interface MLGraphBuilder { conv2d(input: MLOperand, filter: MLOperand, options?: MLConv2dOptions): MLOperand; } -type MLConvTranspose2dFilterOperandLayout = 'iohw'|'hwoi'|'ohwi'; +type MLConvTranspose2dFilterOperandLayout = 'iohw' | 'hwoi' | 'ohwi'; interface MLConvTranspose2dOptions { padding?: number[]; strides?: number[]; @@ -172,8 +186,8 @@ interface MLGemmOptions { interface MLGraphBuilder { gemm(a: MLOperand, b: MLOperand, options?: MLGemmOptions): MLOperand; } -type MLGruWeightLayout = 'zrn'|'rzn'; -type MLRecurrentNetworkDirection = 'forward'|'backward'|'both'; +type MLGruWeightLayout = 'zrn' | 'rzn'; +type MLRecurrentNetworkDirection = 'forward' | 'backward' | 'both'; interface MLGruOptions { bias?: MLOperand; recurrentBias?: MLOperand; @@ -185,8 +199,14 @@ interface MLGruOptions { activations?: MLActivation[]; } interface MLGraphBuilder { - gru(input: MLOperand, weight: MLOperand, recurrentWeight: MLOperand, steps: number, hiddenSize: number, - options?: MLGruOptions): MLOperand[]; + gru( + input: MLOperand, + weight: MLOperand, + recurrentWeight: MLOperand, + steps: number, + hiddenSize: number, + options?: MLGruOptions, + ): MLOperand[]; } interface MLGruCellOptions { bias?: MLOperand; @@ -197,8 +217,13 @@ interface MLGruCellOptions { } interface MLGraphBuilder { gruCell( - input: MLOperand, weight: MLOperand, recurrentWeight: MLOperand, hiddenState: MLOperand, hiddenSize: number, - options?: MLGruCellOptions): MLOperand; + input: MLOperand, + weight: MLOperand, + recurrentWeight: MLOperand, + hiddenState: MLOperand, + hiddenSize: number, + options?: MLGruCellOptions, + ): MLOperand; } interface MLHardSigmoidOptions { alpha?: number; @@ -245,7 +270,7 @@ interface MLGraphBuilder { linear(input: MLOperand, options?: MLLinearOptions): MLOperand; linear(options?: MLLinearOptions): MLActivation; } -type MLLstmWeightLayout = 'iofg'|'ifgo'; +type MLLstmWeightLayout = 'iofg' | 'ifgo'; interface MLLstmOptions { bias?: MLOperand; recurrentBias?: MLOperand; @@ -259,8 +284,13 @@ interface MLLstmOptions { } interface MLGraphBuilder { lstm( - input: MLOperand, weight: MLOperand, recurrentWeight: MLOperand, steps: number, hiddenSize: number, - options?: MLLstmOptions): MLOperand[]; + input: MLOperand, + weight: MLOperand, + recurrentWeight: MLOperand, + steps: number, + hiddenSize: number, + options?: MLLstmOptions, + ): MLOperand[]; } interface MLLstmCellOptions { bias?: MLOperand; @@ -271,13 +301,19 @@ interface MLLstmCellOptions { } interface MLGraphBuilder { lstmCell( - input: MLOperand, weight: MLOperand, recurrentWeight: MLOperand, hiddenState: MLOperand, cellState: MLOperand, - hiddenSize: number, options?: MLLstmCellOptions): MLOperand[]; + input: MLOperand, + weight: MLOperand, + recurrentWeight: MLOperand, + hiddenState: MLOperand, + cellState: MLOperand, + hiddenSize: number, + options?: MLLstmCellOptions, + ): MLOperand[]; } interface MLGraphBuilder { matmul(a: MLOperand, b: MLOperand): MLOperand; } -type MLPaddingMode = 'constant'|'edge'|'reflection'|'symmetric'; +type MLPaddingMode = 'constant' | 'edge' | 'reflection' | 'symmetric'; interface MLPadOptions { mode?: MLPaddingMode; value?: number; @@ -285,7 +321,7 @@ interface MLPadOptions { interface MLGraphBuilder { pad(input: MLOperand, beginningPadding: number[], endingPadding: number[], options?: MLPadOptions): MLOperand; } -type MLRoundingType = 'floor'|'ceil'; +type MLRoundingType = 'floor' | 'ceil'; interface MLPool2dOptions { windowDimensions?: number[]; padding?: number[]; @@ -323,7 +359,7 @@ interface MLGraphBuilder { relu(input: MLOperand): MLOperand; relu(): MLActivation; } -type MLInterpolationMode = 'nearest-neighbor'|'linear'; +type MLInterpolationMode = 'nearest-neighbor' | 'linear'; interface MLResample2dOptions { mode?: MLInterpolationMode; scales?: number[]; @@ -359,7 +395,7 @@ interface MLSplitOptions { axis?: number; } interface MLGraphBuilder { - split(input: MLOperand, splits: number|number[], options?: MLSplitOptions): MLOperand[]; + split(input: MLOperand, splits: number | number[], options?: MLSplitOptions): MLOperand[]; } interface MLGraphBuilder { tanh(input: MLOperand): MLOperand; @@ -410,12 +446,15 @@ interface MLTensorDescriptor extends MLOperandDescriptor { interface MLContext { createTensor(descriptor: MLTensorDescriptor): Promise; writeTensor( - destinationTensor: MLTensor, sourceData: ArrayBufferView|ArrayBuffer, sourceElementOffset?: number, - sourceElementSize?: number): void; + destinationTensor: MLTensor, + sourceData: ArrayBufferView | ArrayBuffer, + sourceElementOffset?: number, + sourceElementSize?: number, + ): void; readTensor(sourceTensor: MLTensor): Promise; - readTensor(sourceTensor: MLTensor, destinationData: ArrayBufferView|ArrayBuffer): Promise; + readTensor(sourceTensor: MLTensor, destinationData: ArrayBufferView | ArrayBuffer): Promise; dispatch(graph: MLGraph, inputs: MLNamedTensor, outputs: MLNamedTensor): void; - opSupportLimits() : MLOpSupportLimits; + opSupportLimits(): MLOpSupportLimits; } interface MLOpSupportLimits { diff --git a/js/web/lib/wasm/wasm-factory.ts b/js/web/lib/wasm/wasm-factory.ts index 13bb9f9fbbc93..a9ef6c72314dd 100644 --- a/js/web/lib/wasm/wasm-factory.ts +++ b/js/web/lib/wasm/wasm-factory.ts @@ -32,7 +32,7 @@ const isMultiThreadSupported = (): boolean => { 2, 0, 26, 11, ]), ); - } catch (e) { + } catch { return false; } }; @@ -59,7 +59,7 @@ const isSimdSupported = (): boolean => { 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 253, 186, 1, 26, 11, ]), ); - } catch (e) { + } catch { return false; } }; @@ -87,7 +87,7 @@ const isRelaxedSimdSupported = (): boolean => { 15, 65, 3, 253, 15, 253, 147, 2, 11, ]), ); - } catch (e) { + } catch { return false; } }; diff --git a/js/web/lib/wasm/wasm-utils-load-file.ts b/js/web/lib/wasm/wasm-utils-load-file.ts index 53cba46eeac2b..575262bfbe155 100644 --- a/js/web/lib/wasm/wasm-utils-load-file.ts +++ b/js/web/lib/wasm/wasm-utils-load-file.ts @@ -63,7 +63,6 @@ export const loadFile = async (file: string | Blob | ArrayBufferLike | Uint8Arra } let offset = 0; - // eslint-disable-next-line no-constant-condition while (true) { const { done, value } = await reader.read(); if (done) { diff --git a/js/web/script/generate-webgl-operator-md.ts b/js/web/script/generate-webgl-operator-md.ts index 2bba6cc271068..0776e8b0ad474 100644 --- a/js/web/script/generate-webgl-operator-md.ts +++ b/js/web/script/generate-webgl-operator-md.ts @@ -16,7 +16,7 @@ function checkSupport(type: string, range: [number, number], rules: readonly OpS for (let i = range[0]; i <= range[1]; i++) { try { resolveOperator(node, [{ domain: '', version: i }], rules); - } catch (_e) { + } catch { return false; } } diff --git a/js/web/script/generate-webgpu-operator-md.ts b/js/web/script/generate-webgpu-operator-md.ts index 26640749defc2..26be10f211aaa 100644 --- a/js/web/script/generate-webgpu-operator-md.ts +++ b/js/web/script/generate-webgpu-operator-md.ts @@ -20,7 +20,6 @@ const COMMENTS: Record = { MultiHeadAttention: 'need implementing mask and past/present', }; -/* eslint-disable max-len */ const MATCHERS = [ /class ONNX_OPERATOR_VERSIONED_KERNEL_CLASS_NAME\(\s*(?\w+),\s*(?\w+),\s*(?\d+),\s*(?\d+),\s*(?\w+)\)/g, /class ONNX_OPERATOR_KERNEL_CLASS_NAME\(\s*(?\w+),\s*(?\w+),\s*(?\d+),\s*(?\w+)\)/g, @@ -28,7 +27,6 @@ const MATCHERS = [ /class ONNX_OPERATOR_TYPED_KERNEL_CLASS_NAME\(\s*(?\w+),\s*(?\w+),\s*(?\d+),\s*(?\w+),\s*(?\w+)\)/g, /class ONNX_OPERATOR_TWO_TYPED_KERNEL_CLASS_NAME\(\s*(?\w+),\s*(?\w+),\s*(?\d+),\s*(?\w+),\s*(?\w+),\s*(?\w+)\)/g, ]; -/* eslint-enable max-len */ const ALL_REGISTERED_OPERATORS: Map< string, diff --git a/js/web/script/parse-profiler.ts b/js/web/script/parse-profiler.ts index 95053bab161bd..a587d580edb44 100644 --- a/js/web/script/parse-profiler.ts +++ b/js/web/script/parse-profiler.ts @@ -1,8 +1,6 @@ // Copyright (c) Microsoft Corporation. All rights reserved. // Licensed under the MIT License. -/* eslint-disable @typescript-eslint/restrict-plus-operands */ - // parse-profiler // // this script is used to parse performance profiling result. diff --git a/js/web/script/pull-prebuilt-wasm-artifacts.ts b/js/web/script/pull-prebuilt-wasm-artifacts.ts index 6dce99147abab..413f779dc908c 100644 --- a/js/web/script/pull-prebuilt-wasm-artifacts.ts +++ b/js/web/script/pull-prebuilt-wasm-artifacts.ts @@ -57,7 +57,7 @@ if (args.help || args.h) { // Check if GitHub CLI (gh) is installed and available in PATH try { execSync('gh --version', { stdio: 'pipe' }).toString().trim(); -} catch (e) { +} catch { console.error('Error: GitHub CLI (gh) is not installed or not in PATH.'); console.error('Please install it from https://cli.github.com/ and try again.'); process.exit(1); diff --git a/js/web/script/test-runner-cli-args.ts b/js/web/script/test-runner-cli-args.ts index 3bfb89164393e..6fafd6616785c 100644 --- a/js/web/script/test-runner-cli-args.ts +++ b/js/web/script/test-runner-cli-args.ts @@ -8,7 +8,6 @@ import { Env, InferenceSession } from 'onnxruntime-common'; import { Logger } from '../lib/onnxjs/instrument'; import { Test } from '../test/test-types'; -/* eslint-disable max-len */ const HELP_MESSAGE = ` test-runner-cli @@ -129,7 +128,6 @@ Examples: Run perf testing of an ONNX model on WebGL backend > test-runner-cli model -b=webgl -P `; -/* eslint-enable max-len */ export declare namespace TestRunnerCliArgs { type Mode = 'suite0' | 'suite1' | 'model' | 'unittest' | 'op'; diff --git a/js/web/script/test-runner-cli.ts b/js/web/script/test-runner-cli.ts index a0e93a70fb2ff..a1f764ed68340 100644 --- a/js/web/script/test-runner-cli.ts +++ b/js/web/script/test-runner-cli.ts @@ -658,7 +658,6 @@ async function main() { // delete the files stores in the specific folder to clean up the recovery page list. // see also: https://www.laptopmag.com/articles/edge-browser-stop-tab-restore const deleteEdgeActiveRecoveryCommand = - // eslint-disable-next-line max-len 'del /F /Q % LOCALAPPDATA %\\Packages\\Microsoft.MicrosoftEdge_8wekyb3d8bbwe\\AC\\MicrosoftEdge\\User\\Default\\Recovery\\Active\\*'; npmlog.info('TestRunnerCli.Run', `CMD: ${deleteEdgeActiveRecoveryCommand}`); spawnSync(deleteEdgeActiveRecoveryCommand, { shell: true, stdio: 'inherit' }); diff --git a/js/web/test/test-runner.ts b/js/web/test/test-runner.ts index 6fbce114093c0..7ac772ee0304f 100644 --- a/js/web/test/test-runner.ts +++ b/js/web/test/test-runner.ts @@ -405,8 +405,8 @@ export class TensorResultValidator { 'TestRunner', `Tensor mismatch: \nACTUAL: type=${actual[i].type}; dims=[${actual[i].dims}]; data=[${actual[i].data}]\nEXPECT: type=${expected[i].type}; dims=[${expected[i].dims}]; data=[${expected[i].data}]`, ); + throw new Error('tensor data should match'); } - expect(match, 'tensor data should match').to.be.true; } } diff --git a/js/web/test/test-types.ts b/js/web/test/test-types.ts index 91fc93244640e..eb3c5ab1e38d4 100644 --- a/js/web/test/test-types.ts +++ b/js/web/test/test-types.ts @@ -111,7 +111,6 @@ export declare namespace Test { tests: readonly OperatorTest[]; } - // eslint-disable-next-line @typescript-eslint/no-namespace export namespace TestList { export type TestName = string; export interface TestDescription { diff --git a/js/web/test/unittests/opset.ts b/js/web/test/unittests/opset.ts index a4bd0a079cdda..57433c68a6381 100644 --- a/js/web/test/unittests/opset.ts +++ b/js/web/test/unittests/opset.ts @@ -39,7 +39,9 @@ function checkConsistency(rules: readonly OpSet.ResolveRule[]) { } catch { continue; } - expect(match, `multiple rules overlapped: opType='${type}', domain='', version=${i}`).to.be.false; + if (match) { + throw new Error(`multiple rules overlapped: opType='${type}', domain='', version=${i}`); + } match = true; } } From 852f0902b497ea3cfba0afda45018204356cb79c Mon Sep 17 00:00:00 2001 From: mingyue <131847423+mingyueliuh@users.noreply.github.com> Date: Wed, 29 Oct 2025 01:25:21 +0800 Subject: [PATCH 11/33] use std::move(model_proto) to avoid extra copy (#26372) Previously, model_proto was passed by name, which triggered a copy constructor call instead of move construction. Using std::move(model_proto) ensures that the object is constructed via move semantics, reducing unnecessary memory allocation and copy overhead. Co-authored-by: liumingyue --- onnxruntime/core/session/provider_bridge_ort.cc | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/onnxruntime/core/session/provider_bridge_ort.cc b/onnxruntime/core/session/provider_bridge_ort.cc index 960b9eff051be..40ab0de5abace 100644 --- a/onnxruntime/core/session/provider_bridge_ort.cc +++ b/onnxruntime/core/session/provider_bridge_ort.cc @@ -1239,7 +1239,7 @@ struct ProviderHostImpl : ProviderHost { std::unique_ptr Model__construct(ONNX_NAMESPACE::ModelProto&& model_proto, const PathString& model_path, const IOnnxRuntimeOpSchemaRegistryList* local_registries, const logging::Logger& logger) override { - return std::make_unique(model_proto, model_path, local_registries, logger); + return std::make_unique(std::move(model_proto), model_path, local_registries, logger); } std::unique_ptr Model__construct(const std::string& graph_name, bool is_onnx_domain_only, From 0f6cffc140211dd5766aff1c052e8bc57e3f954e Mon Sep 17 00:00:00 2001 From: Edward Chen <18449977+edgchen1@users.noreply.github.com> Date: Tue, 28 Oct 2025 13:17:55 -0700 Subject: [PATCH 12/33] Fix iOS packaging pipeline (#26426) ### Description Change Xcode version from 16.4 to 16.2, according to what's available on the build agent image. Adjust casing in `xcodebuild -destination` argument. ### Motivation and Context Fix iOS packaging pipeline issues. --- tools/ci_build/github/apple/test_apple_packages.py | 2 +- .../templates/stages/mac-ios-packaging-build-stage.yml | 4 ++-- 2 files changed, 3 insertions(+), 3 deletions(-) diff --git a/tools/ci_build/github/apple/test_apple_packages.py b/tools/ci_build/github/apple/test_apple_packages.py index 6a935e2fc167d..b27309d865482 100644 --- a/tools/ci_build/github/apple/test_apple_packages.py +++ b/tools/ci_build/github/apple/test_apple_packages.py @@ -206,7 +206,7 @@ def _test_apple_packages(args): "-scheme", "macos_package_test", "-destination", - "platform=macos", + "platform=macOS", ], shell=False, check=True, diff --git a/tools/ci_build/github/azure-pipelines/templates/stages/mac-ios-packaging-build-stage.yml b/tools/ci_build/github/azure-pipelines/templates/stages/mac-ios-packaging-build-stage.yml index e9f170ff60301..7d6e272533696 100644 --- a/tools/ci_build/github/azure-pipelines/templates/stages/mac-ios-packaging-build-stage.yml +++ b/tools/ci_build/github/azure-pipelines/templates/stages/mac-ios-packaging-build-stage.yml @@ -17,8 +17,8 @@ stages: # Note: Keep the Xcode version and iOS simulator version compatible. # Check the table here to see what iOS simulator versions are supported by a particular Xcode version: # https://developer.apple.com/support/xcode/ - xcodeVersion: "16.4" - iosSimulatorRuntimeVersion: "18.5" + xcodeVersion: "16.2" + iosSimulatorRuntimeVersion: "18.2" buildSettingsFile: "tools/ci_build/github/apple/default_full_apple_framework_build_settings.json" cPodName: onnxruntime-c objcPodName: onnxruntime-objc From d85627aec9da1b7efbb8e26dc82414bfce116115 Mon Sep 17 00:00:00 2001 From: Hariharan Seshadri Date: Tue, 28 Oct 2025 18:10:26 -0700 Subject: [PATCH 13/33] [CPU] Use MayInPlace kernel def hint for FusedConv kernel (#26422) ### Description Use MayInPlace hint for the FusedConv NCHW CPU kernel that allows for the allocation planner to re-use the optional "sum" input buffer as the kernel's output buffer. It will potentially save [this copy](https://github.com/microsoft/onnxruntime/blob/06004826cc99dd8b8b92dbf000db3d3525716f22/onnxruntime/core/providers/cpu/nn/conv.cc#L209) if the buffers can be shared (in most cases the buffers can be shared) ### Motivation and Context The kernel already had logic to save the copy but the kernel def was missing the hint to the allocation planner. Found while investigating improvements to a Conv model's performance on ARM64 --- onnxruntime/contrib_ops/cpu/fused_conv.cc | 4 ++++ 1 file changed, 4 insertions(+) diff --git a/onnxruntime/contrib_ops/cpu/fused_conv.cc b/onnxruntime/contrib_ops/cpu/fused_conv.cc index 2e07fa27d7cbb..5374222dbabcc 100644 --- a/onnxruntime/contrib_ops/cpu/fused_conv.cc +++ b/onnxruntime/contrib_ops/cpu/fused_conv.cc @@ -19,6 +19,10 @@ ONNX_CPU_OPERATOR_TYPED_MS_KERNEL( 1, float, KernelDefBuilder() + // If the fused "sum" input is available to the FusedConv node, + // provide a hint to the allocation planner that it can re-use the + // "sum"'s input as the output buffer of the FusedConv node. + .MayInplace(3, 0) .TypeConstraint("T", DataTypeImpl::GetTensorType()), FusedConvFloat); From 41429ed9c940c92a08b05cf7835018fe826f71d6 Mon Sep 17 00:00:00 2001 From: Yulong Wang <7679871+fs-eire@users.noreply.github.com> Date: Tue, 28 Oct 2025 18:29:22 -0700 Subject: [PATCH 14/33] [WebGPU] add unidirectional support for MHA (#26071) ### Description Add unidirectional support for MHA. Also updated `GetCapability` to make sure only run Attention on WebGPU under certain conditions --- .../contrib_ops/webgpu/bert/attention.cc | 204 +++++++++++++++++- .../contrib_ops/webgpu/bert/attention.h | 12 +- .../webgpu/bert/multihead_attention.cc | 2 +- .../webgpu/webgpu_contrib_kernels.cc | 2 +- .../webgpu/webgpu_execution_provider.cc | 36 ++++ .../test/contrib_ops/attention_op_test.cc | 47 ++-- .../multihead_attention_op_test.cc | 31 +-- 7 files changed, 295 insertions(+), 39 deletions(-) diff --git a/onnxruntime/contrib_ops/webgpu/bert/attention.cc b/onnxruntime/contrib_ops/webgpu/bert/attention.cc index 11479f7c5e984..ca20845a8184d 100644 --- a/onnxruntime/contrib_ops/webgpu/bert/attention.cc +++ b/onnxruntime/contrib_ops/webgpu/bert/attention.cc @@ -159,6 +159,16 @@ Status AttentionProbsProgram::GenerateShaderCode(ShaderHelper& shader) const { << " let outputIdx = headOffset + (m + local_id.y) * uniforms.N + n + local_id.x;\n" << " var sum: f32 = " << (components_ == 4 ? "value.x + value.y + value.z + value.w" : (components_ == 2 ? "value.x + value.y" : "value")) << ";\n"; + // Add causal masking for unidirectional attention + if (is_unidirectional_) { + shader.MainFunctionBody() << " // Apply causal masking for unidirectional attention\n" + << " let query_pos = m + local_id.y + past_sequence_length;\n" + << " let key_pos = n + local_id.x;\n" + << " if (key_pos > query_pos) {\n" + << " sum = -3.40282e+38; // Set to very negative value for masking\n" + << " }\n"; + } + shader.MainFunctionBody() << " output[outputIdx] = output_value_t(sum * uniforms.alpha)"; if (has_attention_bias_) { shader.MainFunctionBody() << " + attention_bias[outputIdx]"; @@ -183,7 +193,7 @@ Status ComputeAttentionProbs(onnxruntime::webgpu::ComputeContext& context, int o const int components = parameters.head_size_ % 4 == 0 ? 4 : (parameters.head_size_ % 2 == 0 ? 2 : 1); AttentionProbsProgram program{"AttentionProbs", feed_past_key, has_present_key, has_attention_bias, tile_size, - components, parameters.is_first_prompt_, seqlen_k != nullptr, parameters.past_present_share_buffer_}; + components, parameters.is_first_prompt_, seqlen_k != nullptr, parameters.past_present_share_buffer_, parameters.is_unidirectional_}; program.AddInputs({{Q, ProgramTensorMetadataDependency::TypeAndRank, components}, {K, ProgramTensorMetadataDependency::TypeAndRank, components}}); if (feed_past_key) { @@ -205,7 +215,7 @@ Status ComputeAttentionProbs(onnxruntime::webgpu::ComputeContext& context, int o const uint32_t num_seq_length_tile = (parameters.sequence_length_ + tile_size - 1) / tile_size; program.SetDispatchGroupSize(parameters.batch_size_ * parameters.num_heads_ * num_seq_length_tile * num_total_seq_length_tile) .SetWorkgroupSize(tile_size, tile_size) - .CacheHint(std::to_string(tile_size), parameters.past_present_share_buffer_, feed_past_key, has_present_key, has_attention_bias, seqlen_k != nullptr, components, parameters.is_first_prompt_) + .CacheHint(std::to_string(tile_size), parameters.past_present_share_buffer_, feed_past_key, has_present_key, has_attention_bias, seqlen_k != nullptr, components, parameters.is_first_prompt_, parameters.is_unidirectional_) .AddUniformVariables({{static_cast(parameters.sequence_length_)}, {static_cast(vectorized_head_size)}, {static_cast(total_sequence_length)}, @@ -533,6 +543,196 @@ Status ApplyAttention(const Tensor* Q, const Tensor* K, const Tensor* V, const T return Status::OK(); } +ONNX_OPERATOR_KERNEL_EX( + Attention, + kMSDomain, + 1, + kWebGpuExecutionProvider, + (*KernelDefBuilder::Create()) + .TypeConstraint("T", WebGpuSupportedFloatTypes()), + Attention); + +Attention::Attention(const OpKernelInfo& info) + : WebGpuKernel(info), + onnxruntime::contrib::AttentionBase(info, false) { +} + +// QKV preparation program - computes Q, K, V from input, weights, and bias +class AttentionPrepareProgram final : public Program { + public: + AttentionPrepareProgram() : Program{"AttentionPrepare"} {} + + Status GenerateShaderCode(ShaderHelper& shader) const override { + shader.AddInput("input", ShaderUsage::UseUniform | ShaderUsage::UseValueTypeAlias); + shader.AddInput("weight", ShaderUsage::UseUniform | ShaderUsage::UseValueTypeAlias); + shader.AddInput("bias", ShaderUsage::UseUniform | ShaderUsage::UseValueTypeAlias); + shader.AddOutput("output_q", ShaderUsage::UseUniform | ShaderUsage::UseValueTypeAlias); + shader.AddOutput("output_k", ShaderUsage::UseUniform | ShaderUsage::UseValueTypeAlias); + shader.AddOutput("output_v", ShaderUsage::UseUniform | ShaderUsage::UseValueTypeAlias); + + constexpr int TILE_SIZE = 12; + + shader.AdditionalImplementation() << "const TILE_SIZE = " << TILE_SIZE << "u;\n" + << "var tileInput: array;\n" + << "var tileWeightQ: array;\n" + << "var tileWeightK: array;\n" + << "var tileWeightV: array;\n"; + + shader.MainFunctionBody() //<< shader.GuardAgainstOutOfBoundsWorkgroupSizes("uniforms.M * uniforms.N") + << "let batchIndex = workgroup_id.z / uniforms.num_heads;\n" + << "let headNumber = workgroup_id.z % uniforms.num_heads;\n" + << "let m = global_id.y;\n" + << "let n = global_id.x;\n" + << "let inputOffset = batchIndex * (uniforms.M * uniforms.K) + m * uniforms.K;\n" + << "let biasOffsetQ = headNumber * uniforms.head_size;\n" + << "let biasOffsetK = uniforms.hidden_size + biasOffsetQ;\n" + << "let biasOffsetV = uniforms.hidden_size + biasOffsetK;\n" + << "var valueQ = input_value_t(0);\n" + << "var valueK = input_value_t(0);\n" + << "var valueV = input_value_t(0);\n" + << "for (var w: u32 = 0u; w < uniforms.K; w += TILE_SIZE) {\n" + << " if (m < uniforms.M && w + local_id.x < uniforms.K) {\n" + << " tileInput[TILE_SIZE * local_id.y + local_id.x] = input[inputOffset + w + local_id.x];\n" + << " }\n" + << " if (n < uniforms.N && w + local_id.y < uniforms.K) {\n" + << " let offset = n + (w + local_id.y) * uniforms.ldb;\n" + << " tileWeightQ[TILE_SIZE * local_id.y + local_id.x] = weight[biasOffsetQ + offset];\n" + << " tileWeightK[TILE_SIZE * local_id.y + local_id.x] = weight[biasOffsetK + offset];\n" + << " tileWeightV[TILE_SIZE * local_id.y + local_id.x] = weight[biasOffsetV + offset];\n" + << " }\n" + << " workgroupBarrier();\n" + << " for (var k: u32 = 0u; k(M)}, + {static_cast(K)}, + {static_cast(N)}, + {static_cast(parameters.num_heads_)}, + {static_cast(parameters.head_size_)}, + {static_cast(parameters.hidden_size_)}, + {static_cast(parameters.hidden_size_ + parameters.hidden_size_ + parameters.v_hidden_size_)}}); + + return context.RunProgram(program); +} + +Status Attention::ComputeInternal(onnxruntime::webgpu::ComputeContext& context) const { + const Tensor* input = context.Input(0); + const Tensor* weights = context.Input(1); + const Tensor* bias = context.Input(2); + const Tensor* mask_index = context.Input(3); + const Tensor* past = context.Input(4); + const Tensor* attention_bias = context.Input(5); + const Tensor* past_seq_len = context.Input(6); + + if (past) { + ORT_NOT_IMPLEMENTED("past tensor not implemented for webgpu Attention"); + } + if (mask_index) { + ORT_NOT_IMPLEMENTED("mask_index tensor not implemented for webgpu Attention"); + } + + AttentionParameters params; + // Use the second dimension from weight for bias to get q_hidden_size when bias is nullptr + std::vector bias_dims{weights->Shape().GetDims()[1]}; + const TensorShape bias_shape{bias_dims}; + ORT_RETURN_IF_ERROR(CheckInputs(input->Shape(), + weights->Shape(), + bias != nullptr ? bias->Shape() : bias_shape, + mask_index, + past, + attention_bias, + ¶ms, + context.DeviceLimits().maxComputeInvocationsPerWorkgroup, + past_seq_len)); + + WebgpuAttentionParameters parameters(params); + + TensorShapeVector output_shape(3); + output_shape[0] = static_cast(parameters.batch_size_); + output_shape[1] = static_cast(parameters.sequence_length_); + output_shape[2] = static_cast(parameters.v_hidden_size_); + Tensor* output = context.Output(0, output_shape); + + // If optional outputs aren't needed, present_key and present_value will be null + std::vector present_dims{ + 2, + parameters.batch_size_, + parameters.num_heads_, + parameters.total_sequence_length_, + parameters.head_size_, + }; + TensorShape present_shape(present_dims); + Tensor* present = context.Output(1, present_shape); + if (present) { + ORT_NOT_IMPLEMENTED("present tensor not implemented for webgpu Attention"); + } + + // Create Q, K, V tensors by computing input * weights + bias + TensorShapeVector qkv_shape({parameters.batch_size_, parameters.num_heads_, + parameters.sequence_length_, parameters.head_size_}); + Tensor Q = context.CreateGPUTensor(input->DataType(), qkv_shape); + Tensor K = context.CreateGPUTensor(input->DataType(), qkv_shape); + Tensor V = context.CreateGPUTensor(input->DataType(), qkv_shape); + + // Compute Q, K, V from input, weights, and bias + ORT_RETURN_IF_ERROR(PrepareQKV(context, parameters, input, weights, bias, &Q, &K, &V)); + + // Apply the actual attention computation + return ApplyAttention(&Q, &K, &V, attention_bias, nullptr, nullptr, output, /* present_key */ nullptr, + /* present_value */ nullptr, parameters, context, nullptr, nullptr, -1); +} + } // namespace webgpu } // namespace contrib } // namespace onnxruntime diff --git a/onnxruntime/contrib_ops/webgpu/bert/attention.h b/onnxruntime/contrib_ops/webgpu/bert/attention.h index 3450705b04908..feaee1df7f6fc 100644 --- a/onnxruntime/contrib_ops/webgpu/bert/attention.h +++ b/onnxruntime/contrib_ops/webgpu/bert/attention.h @@ -7,6 +7,7 @@ #include "core/providers/webgpu/program.h" #include "core/providers/webgpu/shader_helper.h" #include "core/providers/webgpu/webgpu_kernel.h" +#include "contrib_ops/cpu/bert/attention_base.h" #include "contrib_ops/webgpu/bert/attention_common.h" namespace onnxruntime { @@ -34,8 +35,8 @@ class TransferBSDToBNSHProgram final : public Program class AttentionProbsProgram final : public Program { public: AttentionProbsProgram(const std::string& kernel_name, bool feed_past_key, bool has_present_key, - bool has_attention_bias, int tile_size, int components, bool is_first_prompt, bool has_seqlen_k = false, bool past_present_share_buffer = false) - : Program{kernel_name}, feed_past_key_(feed_past_key), has_present_key_(has_present_key), has_attention_bias_(has_attention_bias), tile_size_(tile_size), components_(components), has_seqlen_k_(has_seqlen_k), past_present_share_buffer_(past_present_share_buffer), is_first_prompt_(is_first_prompt) { + bool has_attention_bias, int tile_size, int components, bool is_first_prompt, bool has_seqlen_k = false, bool past_present_share_buffer = false, bool is_unidirectional = false) + : Program{kernel_name}, feed_past_key_(feed_past_key), has_present_key_(has_present_key), has_attention_bias_(has_attention_bias), tile_size_(tile_size), components_(components), has_seqlen_k_(has_seqlen_k), past_present_share_buffer_(past_present_share_buffer), is_first_prompt_(is_first_prompt), is_unidirectional_(is_unidirectional) { } Status GenerateShaderCode(ShaderHelper& sh) const override; @@ -65,6 +66,7 @@ class AttentionProbsProgram final : public Program { bool has_seqlen_k_; bool past_present_share_buffer_; bool is_first_prompt_; + bool is_unidirectional_; }; class InPlaceSoftmaxProgram final : public Program { @@ -126,6 +128,12 @@ class VxAttentionScoreProgram final : public Program { bool is_first_prompt_; }; +class Attention final : public WebGpuKernel, public onnxruntime::contrib::AttentionBase { + public: + Attention(const OpKernelInfo& info); + Status ComputeInternal(onnxruntime::webgpu::ComputeContext& context) const override; +}; + } // namespace webgpu } // namespace contrib } // namespace onnxruntime diff --git a/onnxruntime/contrib_ops/webgpu/bert/multihead_attention.cc b/onnxruntime/contrib_ops/webgpu/bert/multihead_attention.cc index f218b1f0a51ff..f72f5ab9c2ab4 100644 --- a/onnxruntime/contrib_ops/webgpu/bert/multihead_attention.cc +++ b/onnxruntime/contrib_ops/webgpu/bert/multihead_attention.cc @@ -29,7 +29,7 @@ ONNX_OPERATOR_KERNEL_EX( MultiHeadAttention::MultiHeadAttention(const OpKernelInfo& info) : WebGpuKernel(info), AttentionBase(info, false) { - ORT_ENFORCE(!is_unidirectional_, "Unidirectional MHA does not support webgpu kernel"); + // Unidirectional attention is now supported for both flash attention and normal attention paths } Status MultiHeadAttention::ComputeInternal(onnxruntime::webgpu::ComputeContext& context) const { diff --git a/onnxruntime/contrib_ops/webgpu/webgpu_contrib_kernels.cc b/onnxruntime/contrib_ops/webgpu/webgpu_contrib_kernels.cc index 25cc13b3ea1df..728be355a2679 100644 --- a/onnxruntime/contrib_ops/webgpu/webgpu_contrib_kernels.cc +++ b/onnxruntime/contrib_ops/webgpu/webgpu_contrib_kernels.cc @@ -37,7 +37,7 @@ KernelCreateInfo BuildKernelCreateInfo() { Status RegisterWebGpuContribKernels(KernelRegistry& kernel_registry) { static const BuildKernelCreateInfoFn function_table[] = { BuildKernelCreateInfo, // default entry to avoid the list become empty after ops-reducing - // BuildKernelCreateInfo, + BuildKernelCreateInfo, BuildKernelCreateInfo, BuildKernelCreateInfo, BuildKernelCreateInfo, diff --git a/onnxruntime/core/providers/webgpu/webgpu_execution_provider.cc b/onnxruntime/core/providers/webgpu/webgpu_execution_provider.cc index 135782ad577c4..89fc13d26269f 100644 --- a/onnxruntime/core/providers/webgpu/webgpu_execution_provider.cc +++ b/onnxruntime/core/providers/webgpu/webgpu_execution_provider.cc @@ -858,6 +858,42 @@ std::vector> WebGpuExecutionProvider::GetCapa LOGS(*GetLogger(), INFO) << "Force CPU execution for node: " << node.Name(); continue; } + + // + // The following code checks if the node is really supported by webgpu EP + // + +#define FALLBACK_TO_CPU_IF_EXIST_INPUT(idx) \ + if (inputs.size() > idx && inputs[idx]->Exists()) { \ + continue; \ + } + +#define FALLBACK_TO_CPU_IF_EXIST_OUTPUT(idx) \ + if (outputs.size() > idx && outputs[idx]->Exists()) { \ + continue; \ + } + + // Check for Attention + if (node.OpType() == "Attention" && node.Domain() == kMSDomain) { + const auto& inputs = node.InputDefs(); + const auto& outputs = node.OutputDefs(); + + // Current implementation does not support mask_index(input[3]), past(input[5]) and past_seq_len(input[6]) + FALLBACK_TO_CPU_IF_EXIST_INPUT(3); + FALLBACK_TO_CPU_IF_EXIST_INPUT(5); + FALLBACK_TO_CPU_IF_EXIST_INPUT(6); + + // Current implementation does not support present(output[1]) + FALLBACK_TO_CPU_IF_EXIST_OUTPUT(1); + + // If attribute past_present_share_buffer is set, fallback to CPU + const auto& past_present_share_buffer = node.GetAttributes().find("past_present_share_buffer"); + if (past_present_share_buffer != node.GetAttributes().end() && + past_present_share_buffer->second.i() != 0) { + continue; + } + } + candidates.push_back(node.Index()); tenative_candidates.push_back(node.Index()); } diff --git a/onnxruntime/test/contrib_ops/attention_op_test.cc b/onnxruntime/test/contrib_ops/attention_op_test.cc index 4245c4bbb1b0a..99fd3c18e94ef 100644 --- a/onnxruntime/test/contrib_ops/attention_op_test.cc +++ b/onnxruntime/test/contrib_ops/attention_op_test.cc @@ -59,6 +59,7 @@ static void RunAttentionTest( const bool disable_cuda = false, const bool disable_rocm = false, const bool disable_dml = false, + const bool disable_webgpu = false, std::vector qkv_sizes = {}, const std::vector& attention_bias_data = {}, int kv_sequence_length = 0, @@ -74,9 +75,10 @@ static void RunAttentionTest( bool enable_rocm = (nullptr != DefaultRocmExecutionProvider().get()) && !is_weights_constant && !disable_rocm; bool enable_cpu = (nullptr != DefaultCpuExecutionProvider().get()) && !use_float16 && !disable_cpu; bool enable_dml = (nullptr != DefaultDmlExecutionProvider().get()) && !disable_dml; + bool enable_webgpu = (nullptr != DefaultWebGpuExecutionProvider().get()) && !disable_webgpu; int head_size = hidden_size / number_of_heads; - if (enable_cpu || enable_cuda || enable_rocm || enable_dml) { + if (enable_cpu || enable_cuda || enable_rocm || enable_dml || enable_webgpu) { OpTester tester("Attention", 1, onnxruntime::kMSDomain); tester.AddAttribute("num_heads", static_cast(number_of_heads)); tester.AddAttribute("unidirectional", static_cast(is_unidirectional ? 1 : 0)); @@ -265,6 +267,12 @@ static void RunAttentionTest( } tester.Run(OpTester::ExpectResult::kExpectSuccess, "", {}, nullptr, &execution_providers); } + + if (enable_webgpu) { + std::vector> execution_providers; + execution_providers.push_back(DefaultWebGpuExecutionProvider()); + tester.Run(OpTester::ExpectResult::kExpectSuccess, "", {}, nullptr, &execution_providers); + } } } @@ -291,6 +299,7 @@ static void RunAttentionTest( const bool disable_cuda = false, const bool disable_rocm = false, const bool disable_dml = false, + const bool disable_webgpu = false, const std::vector qkv_sizes = {}, const std::vector& attention_bias_data = {}, int kv_sequence_length = 0, @@ -301,13 +310,13 @@ static void RunAttentionTest( batch_size, sequence_length, hidden_size, number_of_heads, use_float16, is_unidirectional, use_past_state, past_sequence_length, past_data, present_data, mask_type, input_hidden_size, max_sequence_length, - disable_cpu, disable_cuda, disable_rocm, disable_dml, qkv_sizes, attention_bias_data, + disable_cpu, disable_cuda, disable_rocm, disable_dml, disable_webgpu, qkv_sizes, attention_bias_data, kv_sequence_length, past_present_share_buffer, use_scale, do_neox_rotary); RunAttentionTest(input_data, weights_data, true, bias_data, mask_index_data, output_data, batch_size, sequence_length, hidden_size, number_of_heads, use_float16, is_unidirectional, use_past_state, past_sequence_length, past_data, present_data, mask_type, input_hidden_size, max_sequence_length, - disable_cpu, disable_cuda, disable_rocm, disable_dml, qkv_sizes, attention_bias_data, + disable_cpu, disable_cuda, disable_rocm, disable_dml, disable_webgpu, qkv_sizes, attention_bias_data, kv_sequence_length, past_present_share_buffer, use_scale, do_neox_rotary); } @@ -378,7 +387,7 @@ TEST(ContribOpAttentionTest, AttentionBatch1WithQKVAttr1) { RunAttentionTest(input_data, weight_data, bias_data, mask_index_data, output_data, batch_size, sequence_length, hidden_size, number_of_heads, false, false, false, 0, nullptr, nullptr, AttentionMaskType::MASK_1D_KEY_SEQ_LEN, 0, - 0, false, false, disable_rocm, false, qkv_sizes); + 0, false, false, disable_rocm, false, false, qkv_sizes); } TEST(ContribOpAttentionTest, AttentionBatch1WithQKVAttr2) { @@ -416,7 +425,7 @@ TEST(ContribOpAttentionTest, AttentionBatch1WithQKVAttr2) { RunAttentionTest(input_data, weight_data, bias_data, mask_index_data, output_data, batch_size, sequence_length, hidden_size, number_of_heads, false, false, false, 0, nullptr, nullptr, AttentionMaskType::MASK_1D_KEY_SEQ_LEN, 0, - 0, false, false, disable_rocm, false, qkv_sizes); + 0, false, false, disable_rocm, false, false, qkv_sizes); } TEST(ContribOpAttentionTest, AttentionBatch1AttentionBias) { @@ -457,7 +466,7 @@ TEST(ContribOpAttentionTest, AttentionBatch1AttentionBias) { RunAttentionTest(input_data, weight_data, bias_data, mask_index_data, output_data, batch_size, sequence_length, hidden_size, number_of_heads, false, false, false, 0, nullptr, nullptr, AttentionMaskType::MASK_1D_KEY_SEQ_LEN, 0, - 0, disable_cpu, disable_cuda, disable_rocm, disable_dml, qkv_sizes, attention_bias); + 0, disable_cpu, disable_cuda, disable_rocm, disable_dml, false, qkv_sizes, attention_bias); } TEST(ContribOpAttentionTest, AttentionBatch2AttentionBias) { @@ -503,7 +512,7 @@ TEST(ContribOpAttentionTest, AttentionBatch2AttentionBias) { RunAttentionTest(input_data, weight_data, bias_data, mask_index_data, output_data, batch_size, sequence_length, hidden_size, number_of_heads, false, false, false, 0, nullptr, nullptr, AttentionMaskType::MASK_1D_KEY_SEQ_LEN, 0, - 0, disable_cpu, disable_cuda, disable_rocm, disable_dml, qkv_sizes, attention_bias); + 0, disable_cpu, disable_cuda, disable_rocm, disable_dml, false, qkv_sizes, attention_bias); } TEST(ContribOpAttentionTest, AttentionBatch1_Float16) { @@ -850,8 +859,8 @@ void RawAttentionEmptyPastState(bool past_present_share_buffer) { RunAttentionTest(input_data, weight_data, bias_data, mask_index_data, output_data, batch_size, sequence_length, hidden_size, number_of_heads, false, is_unidirectional, use_past_state, past_sequence_length, &past_data, &present_data, - AttentionMaskType::MASK_1D_KEY_SEQ_LEN, 0, sequence_length, true, false, true, disable_dml, {}, {}, 0, - true); + AttentionMaskType::MASK_1D_KEY_SEQ_LEN, 0, sequence_length, true, false, true, disable_dml, true, + {}, {}, 0, true); } } @@ -1033,7 +1042,7 @@ void RawAttentionPastStateBatch1(bool past_present_share_buffer) { batch_size, sequence_length, hidden_size, number_of_heads, false, is_unidirectional, use_past_state, past_sequence_length, &past_data, &present_data, AttentionMaskType::MASK_1D_KEY_SEQ_LEN, 0, past_sequence_length + sequence_length + 4, - true, false, true, disable_dml, {}, {}, 0, true); + true, false, true, disable_dml, true, {}, {}, 0, true); } } @@ -1166,7 +1175,7 @@ void RawAttentionPastStateBatch2(bool past_present_share_buffer) { batch_size, sequence_length, hidden_size, number_of_heads, false, is_unidirectional, use_past_state, past_sequence_length, &past_data, &present_data, AttentionMaskType::MASK_1D_KEY_SEQ_LEN, 0, past_sequence_length + sequence_length, - true, false, true, disable_dml, {}, {}, 0, true); + true, false, true, disable_dml, true, {}, {}, 0, true); } } @@ -1291,7 +1300,7 @@ void RawAttentionPastStateBatch2WithPadding(bool past_present_share_buffer) { use_past_state, past_sequence_length, &past_data, &present_data, AttentionMaskType::MASK_1D_END_START, 0, past_sequence_length + sequence_length + 4, - true, false, true, disable_dml, {}, {}, 0, true); + true, false, true, disable_dml, true, {}, {}, 0, true); } } @@ -1678,9 +1687,9 @@ TEST(ContribOpAttentionTest, AttentionWithNormFactor) { batch_size, sequence_length, hidden_size, number_of_heads, use_float16, is_unidirectional, use_past_state, past_sequence_length, past_data, present_data, AttentionMaskType::MASK_2D_KEY_PADDING, 0 /*input_hidden_size*/, 0 /*max_sequence_length*/, - false /*disable_cpu*/, false /*disable_cuda*/, true /*disable_rocm*/, false /*disable_dml*/, {} /*qkv_sizes*/, - {} /*attention_bias_data*/, 0 /*kv_sequence_length*/, false /*past_present_share_buffer*/, - true /*use_scale*/); + false /*disable_cpu*/, false /*disable_cuda*/, true /*disable_rocm*/, false /*disable_dml*/, + false /*disable_webgpu*/, {} /*qkv_sizes*/, {} /*attention_bias_data*/, 0 /*kv_sequence_length*/, + false /*past_present_share_buffer*/, true /*use_scale*/); } TEST(ContribOpAttentionTest, AttentionWithNeoXRotaryEmbedding) { @@ -1712,9 +1721,9 @@ TEST(ContribOpAttentionTest, AttentionWithNeoXRotaryEmbedding) { batch_size, sequence_length, hidden_size, number_of_heads, use_float16, is_unidirectional, use_past_state, past_sequence_length, past_data, present_data, AttentionMaskType::MASK_2D_KEY_PADDING, 0 /*input_hidden_size*/, 0 /*max_sequence_length*/, - true /*disable_cpu*/, false /*disable_cuda*/, true /*disable_rocm*/, disable_dml, {} /*qkv_sizes*/, - {} /*attention_bias_data*/, 0 /*kv_sequence_length*/, false /*past_present_share_buffer*/, - true /*use_scale*/, true /*use_neox_rotary_embedding*/); + true /*disable_cpu*/, false /*disable_cuda*/, true /*disable_rocm*/, disable_dml, + true /*disable_webgpu*/, {} /*qkv_sizes*/, {} /*attention_bias_data*/, 0 /*kv_sequence_length*/, + false /*past_present_share_buffer*/, true /*use_scale*/, true /*use_neox_rotary_embedding*/); } TEST(ContribOpAttentionTest, AttentionMask1DEndNoWord) { @@ -1974,7 +1983,7 @@ TEST(ContribOpAttentionTest, Attention4DMask) { batch_size, sequence_length, hidden_size, number_of_heads, use_float16, is_unidirectional, use_past_state, past_sequence_length, past_data, present_data, AttentionMaskType::MASK_4D_MEGATRON, input_hidden_size, max_sequence_length, - disable_cpu); + disable_cpu, /* disable_cuda */ false, /* disable_rocm */ false, /* disable_dml */ false, /* disable_webgpu */ true); } TEST(ContribOpAttentionTest, AttentionMaskIndexOutOfRange) { diff --git a/onnxruntime/test/contrib_ops/multihead_attention_op_test.cc b/onnxruntime/test/contrib_ops/multihead_attention_op_test.cc index 2104f7a35c078..a7d5f15698f0c 100644 --- a/onnxruntime/test/contrib_ops/multihead_attention_op_test.cc +++ b/onnxruntime/test/contrib_ops/multihead_attention_op_test.cc @@ -53,6 +53,7 @@ static void RunMultiHeadAttentionTest( bool is_static_kv = true, bool buffer_share = false, bool use_float16 = false, + bool is_unidirectional = false, bool disable_cpu = false, // some cases not supported in cpu right now. bool disable_cuda = false, bool disable_webgpu = false, @@ -82,6 +83,7 @@ static void RunMultiHeadAttentionTest( if (enable_cpu || enable_cuda || enable_rocm || enable_dml || enable_webgpu) { OpTester tester("MultiHeadAttention", 1, onnxruntime::kMSDomain); tester.AddAttribute("num_heads", static_cast(num_heads)); + tester.AddAttribute("unidirectional", static_cast(is_unidirectional ? 1 : 0)); tester.AddAttribute("mask_filter_value", static_cast(-10000.0f)); std::vector query_dims = {batch_size, sequence_length, hidden_size}; @@ -355,6 +357,7 @@ static void RunMultiHeadAttentionKernel( bool is_static_kv = true, bool buffer_share = false, bool use_float16 = true, + bool is_unidirectional = false, bool disable_cpu = false, // some cases not supported in cpu right now. bool disable_cuda = false, bool disable_webgpu = false, @@ -374,7 +377,7 @@ static void RunMultiHeadAttentionKernel( present_key_data, present_value_data, key_padding_mask_data, mask_type, output_data, output_qk_data, num_heads, batch_size, sequence_length, kv_sequence_length, hidden_size, v_hidden_size, num_beams, max_sequence_length, is_static_kv, buffer_share, use_float16, - disable_cpu, disable_cuda, disable_webgpu, disable_rocm, disable_dml); + is_unidirectional, disable_cpu, disable_cuda, disable_webgpu, disable_rocm, disable_dml); return; } @@ -392,7 +395,7 @@ static void RunMultiHeadAttentionKernel( present_key_data, present_value_data, key_padding_mask_data, mask_type, output_data, output_qk_data, num_heads, batch_size, sequence_length, kv_sequence_length, hidden_size, v_hidden_size, num_beams, max_sequence_length, is_static_kv, buffer_share, use_float16, - disable_cpu, disable_cuda, disable_webgpu, disable_rocm, disable_dml); + is_unidirectional, disable_cpu, disable_cuda, disable_webgpu, disable_rocm, disable_dml); return; } @@ -410,7 +413,7 @@ static void RunMultiHeadAttentionKernel( present_key_data, present_value_data, key_padding_mask_data, mask_type, output_data, output_qk_data, num_heads, batch_size, sequence_length, kv_sequence_length, hidden_size, v_hidden_size, num_beams, max_sequence_length, is_static_kv, buffer_share, use_float16, - disable_cpu, disable_cuda, disable_webgpu, disable_rocm, disable_dml); + is_unidirectional, disable_cpu, disable_cuda, disable_webgpu, disable_rocm, disable_dml); return; } @@ -429,7 +432,7 @@ static void RunMultiHeadAttentionKernel( present_key_data, present_value_data, key_padding_mask_data, mask_type, output_data, output_qk_data, num_heads, batch_size, sequence_length, kv_sequence_length, hidden_size, v_hidden_size, num_beams, max_sequence_length, is_static_kv, buffer_share, use_float16, - disable_cpu, disable_cuda, disable_webgpu, disable_rocm, disable_dml); + is_unidirectional, disable_cpu, disable_cuda, disable_webgpu, disable_rocm, disable_dml); return; } #endif @@ -449,7 +452,7 @@ static void RunMultiHeadAttentionKernel( present_key_data, present_value_data, key_padding_mask_data, mask_type, output_data, output_qk_data, num_heads, batch_size, sequence_length, kv_sequence_length, hidden_size, v_hidden_size, num_beams, max_sequence_length, is_static_kv, buffer_share, use_float16, - disable_cpu, disable_cuda, disable_webgpu, disable_rocm, disable_dml); + is_unidirectional, disable_cpu, disable_cuda, disable_webgpu, disable_rocm, disable_dml); } if (kernel_type == AttentionKernelType::AttentionKernel_CudnnFlashAttention) { @@ -467,7 +470,7 @@ static void RunMultiHeadAttentionKernel( present_key_data, present_value_data, key_padding_mask_data, mask_type, output_data, output_qk_data, num_heads, batch_size, sequence_length, kv_sequence_length, hidden_size, v_hidden_size, num_beams, max_sequence_length, is_static_kv, buffer_share, use_float16, - disable_cpu, disable_cuda, disable_webgpu, disable_rocm, disable_dml); + is_unidirectional, disable_cpu, disable_cuda, disable_webgpu, disable_rocm, disable_dml); } } @@ -505,7 +508,7 @@ static void RunMultiHeadAttentionTests(AttentionTestData& data, data.present_key_data, data.present_value_data, data.key_padding_mask_data, data.mask_type, data.fp32_output_data, data.fp32_output_qk_data, kernel_type, data.num_heads, data.batch_size, data.sequence_length, data.kv_sequence_length, data.hidden_size, data.v_hidden_size, data.num_beams, data.max_sequence_length, data.is_static_kv, data.buffer_share, use_float16, - disable_cpu, disable_cuda, disable_webgpu, disable_rocm, disable_dml); + false, disable_cpu, disable_cuda, disable_webgpu, disable_rocm, disable_dml); } #if USE_MEMORY_EFFICIENT_ATTENTION @@ -519,7 +522,7 @@ static void RunMultiHeadAttentionTests(AttentionTestData& data, data.present_key_data, data.present_value_data, data.key_padding_mask_data, data.mask_type, data.fp32_output_data, data.fp32_output_qk_data, kernel_type, data.num_heads, data.batch_size, data.sequence_length, data.kv_sequence_length, data.hidden_size, data.v_hidden_size, data.num_beams, data.max_sequence_length, data.is_static_kv, data.buffer_share, use_float16, - disable_cpu, disable_cuda, disable_webgpu, disable_rocm, disable_dml); + false, disable_cpu, disable_cuda, disable_webgpu, disable_rocm, disable_dml); } } #endif @@ -531,7 +534,7 @@ static void RunMultiHeadAttentionTests(AttentionTestData& data, data.present_key_data, data.present_value_data, data.key_padding_mask_data, data.mask_type, data.fp32_output_data, data.fp32_output_qk_data, kernel_type, data.num_heads, data.batch_size, data.sequence_length, data.kv_sequence_length, data.hidden_size, data.v_hidden_size, data.num_beams, data.max_sequence_length, data.is_static_kv, data.buffer_share, use_float16, - disable_cpu, disable_cuda, disable_webgpu, disable_rocm, disable_dml); + false, disable_cpu, disable_cuda, disable_webgpu, disable_rocm, disable_dml); } if (data.fp16_output_data.size() > 0) { @@ -544,7 +547,7 @@ static void RunMultiHeadAttentionTests(AttentionTestData& data, data.present_key_data, data.present_value_data, data.key_padding_mask_data, data.mask_type, data.fp16_output_data, data.fp16_output_qk_data, kernel_type, data.num_heads, data.batch_size, data.sequence_length, data.kv_sequence_length, data.hidden_size, data.v_hidden_size, data.num_beams, data.max_sequence_length, data.is_static_kv, data.buffer_share, use_float16, - disable_cpu, disable_cuda, disable_webgpu, disable_rocm, disable_dml); + false, disable_cpu, disable_cuda, disable_webgpu, disable_rocm, disable_dml); } kernel_type = AttentionKernelType::AttentionKernel_TrtFusedAttention; @@ -555,7 +558,7 @@ static void RunMultiHeadAttentionTests(AttentionTestData& data, data.present_key_data, data.present_value_data, data.key_padding_mask_data, data.mask_type, data.fp16_output_data, data.fp16_output_qk_data, kernel_type, data.num_heads, data.batch_size, data.sequence_length, data.kv_sequence_length, data.hidden_size, data.v_hidden_size, data.num_beams, data.max_sequence_length, data.is_static_kv, data.buffer_share, use_float16, - disable_cpu, disable_cuda, disable_webgpu, disable_rocm, disable_dml); + false, disable_cpu, disable_cuda, disable_webgpu, disable_rocm, disable_dml); } #if USE_MEMORY_EFFICIENT_ATTENTION @@ -567,7 +570,7 @@ static void RunMultiHeadAttentionTests(AttentionTestData& data, data.present_key_data, data.present_value_data, data.key_padding_mask_data, data.mask_type, data.fp16_output_data, data.fp16_output_qk_data, kernel_type, data.num_heads, data.batch_size, data.sequence_length, data.kv_sequence_length, data.hidden_size, data.v_hidden_size, data.num_beams, data.max_sequence_length, data.is_static_kv, data.buffer_share, use_float16, - disable_cpu, disable_cuda, disable_webgpu, disable_rocm, disable_dml); + false, disable_cpu, disable_cuda, disable_webgpu, disable_rocm, disable_dml); } #endif @@ -579,7 +582,7 @@ static void RunMultiHeadAttentionTests(AttentionTestData& data, data.present_key_data, data.present_value_data, data.key_padding_mask_data, data.mask_type, data.fp16_output_data, data.fp16_output_qk_data, kernel_type, data.num_heads, data.batch_size, data.sequence_length, data.kv_sequence_length, data.hidden_size, data.v_hidden_size, data.num_beams, data.max_sequence_length, data.is_static_kv, data.buffer_share, use_float16, - disable_cpu, disable_cuda, disable_webgpu, disable_rocm, disable_dml); + false, disable_cpu, disable_cuda, disable_webgpu, disable_rocm, disable_dml); } kernel_type = AttentionKernelType::AttentionKernel_Default; @@ -589,7 +592,7 @@ static void RunMultiHeadAttentionTests(AttentionTestData& data, data.present_key_data, data.present_value_data, data.key_padding_mask_data, data.mask_type, data.fp16_output_data, data.fp16_output_qk_data, kernel_type, data.num_heads, data.batch_size, data.sequence_length, data.kv_sequence_length, data.hidden_size, data.v_hidden_size, data.num_beams, data.max_sequence_length, data.is_static_kv, data.buffer_share, use_float16, - disable_cpu, disable_cuda, disable_webgpu, disable_rocm, disable_dml); + false, disable_cpu, disable_cuda, disable_webgpu, disable_rocm, disable_dml); } } From 3862fe54e345079df66ea18bf5caed9bfdef3992 Mon Sep 17 00:00:00 2001 From: "dependabot[bot]" <49699333+dependabot[bot]@users.noreply.github.com> Date: Wed, 29 Oct 2025 02:11:55 +0000 Subject: [PATCH 15/33] Bump actions/download-artifact from 5 to 6 (#26409) --- .github/workflows/linux_cuda_ci.yml | 2 +- .github/workflows/linux_minimal_build.yml | 2 +- .github/workflows/linux_tensorrt_ci.yml | 2 +- .github/workflows/react_native.yml | 6 +++--- .github/workflows/windows-web-ci-workflow.yml | 2 +- .github/workflows/windows_cuda.yml | 2 +- .github/workflows/windows_tensorrt.yml | 2 +- 7 files changed, 9 insertions(+), 9 deletions(-) diff --git a/.github/workflows/linux_cuda_ci.yml b/.github/workflows/linux_cuda_ci.yml index 9ec5ea47fbf0c..886705471b7de 100644 --- a/.github/workflows/linux_cuda_ci.yml +++ b/.github/workflows/linux_cuda_ci.yml @@ -63,7 +63,7 @@ jobs: # --- Download Build Artifact to Runner Temp Directory --- - name: Download Build Artifact - uses: actions/download-artifact@v5 + uses: actions/download-artifact@v6 with: name: build-output-x64-Release # Must match the upload name path: ${{ runner.temp }}/Release # Download contents into temp dir structure diff --git a/.github/workflows/linux_minimal_build.yml b/.github/workflows/linux_minimal_build.yml index d7b6303d3cdc9..07d1314507fd9 100644 --- a/.github/workflows/linux_minimal_build.yml +++ b/.github/workflows/linux_minimal_build.yml @@ -512,7 +512,7 @@ jobs: with: node-version: 20 - name: Download Test Data Artifact - uses: actions/download-artifact@v5 + uses: actions/download-artifact@v6 with: name: test_data path: ${{ runner.temp }}/.test_data/ diff --git a/.github/workflows/linux_tensorrt_ci.yml b/.github/workflows/linux_tensorrt_ci.yml index 064ad87794cdd..0e26576829e94 100644 --- a/.github/workflows/linux_tensorrt_ci.yml +++ b/.github/workflows/linux_tensorrt_ci.yml @@ -65,7 +65,7 @@ jobs: # --- Download Build Artifact to Runner Temp Directory --- - name: Download Build Artifact - uses: actions/download-artifact@v5 + uses: actions/download-artifact@v6 with: name: build-output-x64-Release # Must match the upload name path: ${{ runner.temp }}/Release # Download contents into temp dir structure diff --git a/.github/workflows/react_native.yml b/.github/workflows/react_native.yml index 04f40c58868ca..c853e7158bacc 100644 --- a/.github/workflows/react_native.yml +++ b/.github/workflows/react_native.yml @@ -102,7 +102,7 @@ jobs: run: sudo apt-get update && sudo apt-get install -y ninja-build - name: Download Android AAR artifacts - uses: actions/download-artifact@v5 + uses: actions/download-artifact@v6 with: name: onnxruntime-android-full-aar path: ${{ runner.temp }}/android-full-aar @@ -221,7 +221,7 @@ jobs: uses: actions/checkout@v5 - name: Download iOS pod artifact - uses: actions/download-artifact@v5 + uses: actions/download-artifact@v6 with: name: ios_pod path: ${{ runner.temp }}/ios_pod @@ -277,7 +277,7 @@ jobs: uses: actions/checkout@v5 - name: Download iOS pod artifact - uses: actions/download-artifact@v5 + uses: actions/download-artifact@v6 with: name: ios_pod path: ${{ runner.temp }}/ios_pod diff --git a/.github/workflows/windows-web-ci-workflow.yml b/.github/workflows/windows-web-ci-workflow.yml index 6ebc6bd7fea43..89e87632a0ba7 100644 --- a/.github/workflows/windows-web-ci-workflow.yml +++ b/.github/workflows/windows-web-ci-workflow.yml @@ -67,7 +67,7 @@ jobs: node-version: "20.x" - name: Download WebAssembly artifacts - uses: actions/download-artifact@v5 + uses: actions/download-artifact@v6 with: name: ${{ inputs.build_config }}_wasm path: ${{ github.workspace }}/artifacts_wasm diff --git a/.github/workflows/windows_cuda.yml b/.github/workflows/windows_cuda.yml index ae23902a015ab..c241eac20165f 100644 --- a/.github/workflows/windows_cuda.yml +++ b/.github/workflows/windows_cuda.yml @@ -158,7 +158,7 @@ jobs: submodules: 'none' - name: Download build artifacts - uses: actions/download-artifact@v5 + uses: actions/download-artifact@v6 with: name: build-artifacts path: ${{ runner.temp }}\build diff --git a/.github/workflows/windows_tensorrt.yml b/.github/workflows/windows_tensorrt.yml index f8c6471b412c0..77cd8ec501b66 100644 --- a/.github/workflows/windows_tensorrt.yml +++ b/.github/workflows/windows_tensorrt.yml @@ -163,7 +163,7 @@ jobs: submodules: 'none' - name: Download build artifacts - uses: actions/download-artifact@v5 + uses: actions/download-artifact@v6 with: name: build-artifacts path: ${{ runner.temp }}\build From 3a6a4c2a3718dd773dacbf3625a101d19302115a Mon Sep 17 00:00:00 2001 From: "dependabot[bot]" <49699333+dependabot[bot]@users.noreply.github.com> Date: Wed, 29 Oct 2025 02:12:41 +0000 Subject: [PATCH 16/33] Bump actions/upload-artifact from 4 to 5 (#26411) --- .github/workflows/linux-wasm-ci-build-and-test-workflow.yml | 4 ++-- .github/workflows/linux_minimal_build.yml | 2 +- .github/workflows/publish-c-apidocs.yml | 2 +- .github/workflows/publish-csharp-apidocs.yml | 2 +- .github/workflows/publish-java-apidocs.yml | 2 +- .github/workflows/publish-js-apidocs.yml | 2 +- .github/workflows/publish-objectivec-apidocs.yml | 2 +- .github/workflows/publish-python-apidocs.yml | 2 +- .github/workflows/react_native.yml | 4 ++-- .github/workflows/reusable_linux_build.yml | 4 ++-- .github/workflows/windows-web-ci-workflow.yml | 4 ++-- .github/workflows/windows_cuda.yml | 2 +- .github/workflows/windows_tensorrt.yml | 2 +- .github/workflows/windows_x64_debug_build_x64_debug.yml | 4 ++-- .github/workflows/windows_x64_release_build_x64_release.yml | 4 ++-- ...neric_interface_build_x64_release_ep_generic_interface.yml | 4 ++-- .github/workflows/windows_x64_release_xnnpack.yml | 4 ++-- .github/workflows/windows_x86.yml | 4 ++-- 18 files changed, 27 insertions(+), 27 deletions(-) diff --git a/.github/workflows/linux-wasm-ci-build-and-test-workflow.yml b/.github/workflows/linux-wasm-ci-build-and-test-workflow.yml index cf3bee49f1971..2370c631b7a7a 100644 --- a/.github/workflows/linux-wasm-ci-build-and-test-workflow.yml +++ b/.github/workflows/linux-wasm-ci-build-and-test-workflow.yml @@ -142,7 +142,7 @@ jobs: - name: Upload WASM artifacts if: ${{ inputs.skip_publish != true }} - uses: actions/upload-artifact@v4 + uses: actions/upload-artifact@v5 with: name: ${{ inputs.build_config }}_wasm path: ${{ github.workspace }}/artifacts/wasm @@ -171,7 +171,7 @@ jobs: - name: Publish test results if: ${{ always() && inputs.build_config == 'Debug' }} - uses: actions/upload-artifact@v4 + uses: actions/upload-artifact@v5 with: name: test-results path: ${{ github.workspace }}/build/**/*.results.xml diff --git a/.github/workflows/linux_minimal_build.yml b/.github/workflows/linux_minimal_build.yml index 07d1314507fd9..af86975ee6cdc 100644 --- a/.github/workflows/linux_minimal_build.yml +++ b/.github/workflows/linux_minimal_build.yml @@ -49,7 +49,7 @@ jobs: uses: microsoft/onnxruntime-github-actions/build-and-prep-ort-files@v0.0.9 - name: Upload Test Data Artifact - uses: actions/upload-artifact@v4 + uses: actions/upload-artifact@v5 with: name: test_data path: ${{ runner.temp }}/minimal_build_test_data/ diff --git a/.github/workflows/publish-c-apidocs.yml b/.github/workflows/publish-c-apidocs.yml index fb4e92715a723..25b7899584bbf 100644 --- a/.github/workflows/publish-c-apidocs.yml +++ b/.github/workflows/publish-c-apidocs.yml @@ -45,7 +45,7 @@ jobs: rm -rf site/docs/api/c mv build/doxygen/html _site/docs/api/c - name: Upload new site - uses: actions/upload-artifact@v4 + uses: actions/upload-artifact@v5 with: name: onnxruntime-c-apidocs path: _site diff --git a/.github/workflows/publish-csharp-apidocs.yml b/.github/workflows/publish-csharp-apidocs.yml index 683c5594e82f2..34b9c1af9552f 100644 --- a/.github/workflows/publish-csharp-apidocs.yml +++ b/.github/workflows/publish-csharp-apidocs.yml @@ -56,7 +56,7 @@ jobs: if (Test-Path $OutputDirectory) { Remove-Item -Recurse -Force $OutputDirectory } Move-Item -Path csharp\ApiDocs\csharp -Destination $OutputDirectory - name: Upload docs artifact - uses: actions/upload-artifact@v4 + uses: actions/upload-artifact@v5 with: name: onnxruntime-csharp-apidocs path: _site diff --git a/.github/workflows/publish-java-apidocs.yml b/.github/workflows/publish-java-apidocs.yml index 742069542ecb9..656d0627ed17d 100644 --- a/.github/workflows/publish-java-apidocs.yml +++ b/.github/workflows/publish-java-apidocs.yml @@ -43,7 +43,7 @@ jobs: mkdir -p _site/docs/api mv java/build/docs/javadoc _site/docs/api/java - name: Upload new site - uses: actions/upload-artifact@v4 + uses: actions/upload-artifact@v5 with: name: onnxruntime-java-apidocs path: _site diff --git a/.github/workflows/publish-js-apidocs.yml b/.github/workflows/publish-js-apidocs.yml index cada1ceecd8e0..e71d3b3c57a4b 100644 --- a/.github/workflows/publish-js-apidocs.yml +++ b/.github/workflows/publish-js-apidocs.yml @@ -43,7 +43,7 @@ jobs: mkdir -p _site/docs/api mv js/common/docs _site/docs/api/js - name: Upload docs artifact - uses: actions/upload-artifact@v4 + uses: actions/upload-artifact@v5 with: name: onnxruntime-node-apidocs path: _site diff --git a/.github/workflows/publish-objectivec-apidocs.yml b/.github/workflows/publish-objectivec-apidocs.yml index 7f1611fdff315..983d3d478a49d 100644 --- a/.github/workflows/publish-objectivec-apidocs.yml +++ b/.github/workflows/publish-objectivec-apidocs.yml @@ -52,7 +52,7 @@ jobs: shell: bash - name: Upload new site - uses: actions/upload-artifact@v4 + uses: actions/upload-artifact@v5 with: name: onnxruntime-objectivec-apidocs path: ./_site diff --git a/.github/workflows/publish-python-apidocs.yml b/.github/workflows/publish-python-apidocs.yml index 4baa8a0f5c272..389d1683fb1ff 100644 --- a/.github/workflows/publish-python-apidocs.yml +++ b/.github/workflows/publish-python-apidocs.yml @@ -50,7 +50,7 @@ jobs: mkdir -p _site/docs/api/ mv build/docs/html _site/docs/api/python - name: Upload docs artifact - uses: actions/upload-artifact@v4 + uses: actions/upload-artifact@v5 with: name: onnxruntime-python-apidocs path: _site diff --git a/.github/workflows/react_native.yml b/.github/workflows/react_native.yml index c853e7158bacc..f827f3bc95456 100644 --- a/.github/workflows/react_native.yml +++ b/.github/workflows/react_native.yml @@ -63,7 +63,7 @@ jobs: cp ${BASE_PATH}/*.pom ${{ runner.temp }}/artifacts - name: Upload Android AAR Artifact - uses: actions/upload-artifact@v4 + uses: actions/upload-artifact@v5 with: name: onnxruntime-android-full-aar path: ${{ runner.temp }}/artifacts @@ -206,7 +206,7 @@ jobs: --build-settings-file ${{ github.workspace }}/tools/ci_build/github/js/react_native_e2e_full_ios_framework_build_settings_arm64.json - name: Upload iOS Pod Artifact - uses: actions/upload-artifact@v4 + uses: actions/upload-artifact@v5 with: name: ios_pod path: ${{ runner.temp }}/ios_pod diff --git a/.github/workflows/reusable_linux_build.yml b/.github/workflows/reusable_linux_build.yml index 1a9c0e0a72031..02e6388ce4738 100644 --- a/.github/workflows/reusable_linux_build.yml +++ b/.github/workflows/reusable_linux_build.yml @@ -163,7 +163,7 @@ jobs: # ------------- Upload Build Output Step ------------- - name: Upload Build Output Artifact if: inputs.upload_build_output == true - uses: actions/upload-artifact@v4 + uses: actions/upload-artifact@v5 with: name: build-output-${{ inputs.architecture }}-${{ inputs.build_config }} path: ${{ runner.temp }}/${{ inputs.build_config }} @@ -172,7 +172,7 @@ jobs: # ------------- Upload Log on Build Failure Step ------------- - name: Upload VCPKG Manifest Install Log on Update or Build Failure if: steps.update_step.outcome == 'failure' || steps.build_step.outcome == 'failure' - uses: actions/upload-artifact@v4 + uses: actions/upload-artifact@v5 with: name: vcpkg-manifest-install-log-${{ inputs.architecture }}-${{ inputs.build_config }} path: ${{ runner.temp }}/${{ inputs.build_config }}/${{ inputs.build_config }}/vcpkg-manifest-install.log diff --git a/.github/workflows/windows-web-ci-workflow.yml b/.github/workflows/windows-web-ci-workflow.yml index 89e87632a0ba7..eee98332056f6 100644 --- a/.github/workflows/windows-web-ci-workflow.yml +++ b/.github/workflows/windows-web-ci-workflow.yml @@ -173,7 +173,7 @@ jobs: # this step is added to help investigate the shader validation failure which is hard to reproduce - name: Upload WebGPU shader validation log on failure if: ${{ failure() && inputs.build_config == 'Debug' }} - uses: actions/upload-artifact@v4 + uses: actions/upload-artifact@v5 with: name: webgpu-shader-validation-logs path: ${{ runner.temp }}\web\test\07\chrome_debug.log @@ -203,7 +203,7 @@ jobs: - name: Upload NPM packages if: ${{ inputs.build_config == 'Release' }} - uses: actions/upload-artifact@v4 + uses: actions/upload-artifact@v5 with: name: ${{ inputs.package_name }} path: ${{ github.workspace }}\artifacts_npm diff --git a/.github/workflows/windows_cuda.yml b/.github/workflows/windows_cuda.yml index c241eac20165f..fd5b65eb039a3 100644 --- a/.github/workflows/windows_cuda.yml +++ b/.github/workflows/windows_cuda.yml @@ -132,7 +132,7 @@ jobs: shell: pwsh - name: Upload build artifacts - uses: actions/upload-artifact@v4 + uses: actions/upload-artifact@v5 with: name: build-artifacts path: ${{ runner.temp }}\build diff --git a/.github/workflows/windows_tensorrt.yml b/.github/workflows/windows_tensorrt.yml index 77cd8ec501b66..229efb01f0018 100644 --- a/.github/workflows/windows_tensorrt.yml +++ b/.github/workflows/windows_tensorrt.yml @@ -137,7 +137,7 @@ jobs: shell: pwsh - name: Upload build artifacts - uses: actions/upload-artifact@v4 + uses: actions/upload-artifact@v5 with: name: build-artifacts path: ${{ runner.temp }}\build diff --git a/.github/workflows/windows_x64_debug_build_x64_debug.yml b/.github/workflows/windows_x64_debug_build_x64_debug.yml index e4d1477b5619c..d62c7130e0ebb 100644 --- a/.github/workflows/windows_x64_debug_build_x64_debug.yml +++ b/.github/workflows/windows_x64_debug_build_x64_debug.yml @@ -109,14 +109,14 @@ jobs: # Publish artifacts only on failure and if DocUpdateNeeded is true (example) - name: Publish OperatorKernels.md (Conditional) - uses: actions/upload-artifact@v4 + uses: actions/upload-artifact@v5 if: failure() && env.DocUpdateNeeded == 'true' # Use env. for step-level vars with: name: OperatorKernels.md path: ${{ github.workspace }}/docs/OperatorKernels.md - name: Publish ContribOperators.md (Conditional) - uses: actions/upload-artifact@v4 + uses: actions/upload-artifact@v5 if: failure() && env.DocUpdateNeeded == 'true' with: name: ContribOperators.md diff --git a/.github/workflows/windows_x64_release_build_x64_release.yml b/.github/workflows/windows_x64_release_build_x64_release.yml index 46b667ac22b02..a2991bb0f1131 100644 --- a/.github/workflows/windows_x64_release_build_x64_release.yml +++ b/.github/workflows/windows_x64_release_build_x64_release.yml @@ -107,14 +107,14 @@ jobs: working-directory: "${{ github.workspace }}\\build\\RelWithDebInfo\\RelWithDebInfo" - name: Publish OperatorKernels.md (Conditional) - uses: actions/upload-artifact@v4 + uses: actions/upload-artifact@v5 if: failure() && env.DocUpdateNeeded == 'true' with: name: OperatorKernels.md path: ${{ github.workspace }}/docs/OperatorKernels.md - name: Publish ContribOperators.md (Conditional) - uses: actions/upload-artifact@v4 + uses: actions/upload-artifact@v5 if: failure() && env.DocUpdateNeeded == 'true' with: name: ContribOperators.md diff --git a/.github/workflows/windows_x64_release_ep_generic_interface_build_x64_release_ep_generic_interface.yml b/.github/workflows/windows_x64_release_ep_generic_interface_build_x64_release_ep_generic_interface.yml index 4026869c6e4f2..bb6c5035b0dce 100644 --- a/.github/workflows/windows_x64_release_ep_generic_interface_build_x64_release_ep_generic_interface.yml +++ b/.github/workflows/windows_x64_release_ep_generic_interface_build_x64_release_ep_generic_interface.yml @@ -92,14 +92,14 @@ jobs: run: python tools\ValidateNativeDelegateAttributes.py working-directory: ${{ github.workspace }}\\csharp - name: Publish OperatorKernels.md (Conditional) - uses: actions/upload-artifact@v4 + uses: actions/upload-artifact@v5 if: failure() && env.DocUpdateNeeded == 'true' with: name: OperatorKernels.md path: ${{ github.workspace }}/docs/OperatorKernels.md - name: Publish ContribOperators.md (Conditional) - uses: actions/upload-artifact@v4 + uses: actions/upload-artifact@v5 if: failure() && env.DocUpdateNeeded == 'true' with: name: ContribOperators.md diff --git a/.github/workflows/windows_x64_release_xnnpack.yml b/.github/workflows/windows_x64_release_xnnpack.yml index dd8c251ea23d3..b453cd570ac05 100644 --- a/.github/workflows/windows_x64_release_xnnpack.yml +++ b/.github/workflows/windows_x64_release_xnnpack.yml @@ -94,14 +94,14 @@ jobs: working-directory: ${{ github.workspace }}\\csharp - name: Publish OperatorKernels.md (Conditional) - uses: actions/upload-artifact@v4 + uses: actions/upload-artifact@v5 if: failure() && env.DocUpdateNeeded == 'true' with: name: OperatorKernels.md path: ${{ github.workspace }}/docs/OperatorKernels.md - name: Publish ContribOperators.md (Conditional) - uses: actions/upload-artifact@v4 + uses: actions/upload-artifact@v5 if: failure() && env.DocUpdateNeeded == 'true' with: name: ContribOperators.md diff --git a/.github/workflows/windows_x86.yml b/.github/workflows/windows_x86.yml index e8f04a955e32e..d81c5d559c8e5 100644 --- a/.github/workflows/windows_x86.yml +++ b/.github/workflows/windows_x86.yml @@ -102,14 +102,14 @@ jobs: working-directory: "${{ github.workspace }}\\build\\RelWithDebInfo\\RelWithDebInfo" - name: Publish OperatorKernels.md (Conditional) - uses: actions/upload-artifact@v4 + uses: actions/upload-artifact@v5 if: failure() && env.DocUpdateNeeded == 'true' with: name: OperatorKernels.md path: ${{ github.workspace }}/docs/OperatorKernels.md - name: Publish ContribOperators.md (Conditional) - uses: actions/upload-artifact@v4 + uses: actions/upload-artifact@v5 if: failure() && env.DocUpdateNeeded == 'true' with: name: ContribOperators.md From f7fd3b522d100482988194f3ecc905102b83032f Mon Sep 17 00:00:00 2001 From: Jiajia Qin Date: Wed, 29 Oct 2025 10:28:02 +0800 Subject: [PATCH 17/33] [webgpu] Register GQA based on graph capture (#26384) This pull request enables conditionally register GQA with total_sequence_length on gpu or not. It resolves the issue that a MemcpyToHost is generated when graph capture is enabled (refer to #25868). This is the last functionality part to support graph capture in webgpu ep in ORT. The main changes ensure that when graph capture is enabled, sequence length information is read from GPU buffers instead of CPU memory, and shader code generation adapts accordingly. This enables more efficient execution and compatibility with graph-captured models. In this PR, we still get total sequence length from `seqlen_k` tensor not `total_seqlen_tensor` tensor to keep consistent with other parts. In the next PR, we can refactor all places to directly use `total_seqlen_tensor` instead of `seqlen_k` when graph capture enabled. --- .../cpu/bert/group_query_attention_helper.h | 28 ++++++------- .../webgpu/bert/flash_attention.cc | 32 ++++++++++----- .../contrib_ops/webgpu/bert/flash_attention.h | 13 ++++--- .../webgpu/bert/flash_attention.wgsl.template | 39 +++++++++++++------ .../webgpu/bert/group_query_attention.cc | 35 +++++++++++------ .../webgpu/bert/group_query_attention.h | 2 + .../webgpu/webgpu_contrib_kernels.cc | 8 +++- .../webgpu/webgpu_contrib_kernels.h | 2 +- .../webgpu/webgpu_execution_provider.cc | 2 +- 9 files changed, 104 insertions(+), 57 deletions(-) diff --git a/onnxruntime/contrib_ops/cpu/bert/group_query_attention_helper.h b/onnxruntime/contrib_ops/cpu/bert/group_query_attention_helper.h index 46d3e7e675e85..01172bb8f3270 100644 --- a/onnxruntime/contrib_ops/cpu/bert/group_query_attention_helper.h +++ b/onnxruntime/contrib_ops/cpu/bert/group_query_attention_helper.h @@ -251,12 +251,14 @@ Status CheckInputs(const T* query, "seqlens_k must be shape (batch_size)."); } - // Set present sequence length from input total_seqlen tensor if (!onnxruntime::IsScalarOr1ElementVector(total_seqlen)) { return ORT_MAKE_STATUS(ONNXRUNTIME, INVALID_ARGUMENT, "total_sequence_length tensor must be of one element."); } - int total_sequence_length = *((*total_seqlen).template Data()); + + // When graph capture is enabled, total_seqlen is on GPU and cannot be read. Skip validation. + const bool is_total_seqlen_on_cpu = (total_seqlen->Location().device.Type() == OrtDevice::CPU); + int total_sequence_length = is_total_seqlen_on_cpu ? *((*total_seqlen).template Data()) : 0; int present_sequence_length = std::max(total_sequence_length, past_sequence_length); int rotary_dim = 0; @@ -267,22 +269,20 @@ Status CheckInputs(const T* query, "Input 'cos_cache' and 'sin_cache' shall be both present or both absent."); } + // Skip prompt type detection when total_seqlen is on GPU (graph capture mode) bool is_subsequent_prompt = false; - if (sequence_length > 1 && sequence_length != total_sequence_length) { - if (batch_size != 1) { - return ORT_MAKE_STATUS(ONNXRUNTIME, INVALID_ARGUMENT, - "batch_size must be 1 when sequence_length > 1 and past context is given."); + bool is_first_prompt = false; + if (is_total_seqlen_on_cpu) { + if (sequence_length > 1 && sequence_length != total_sequence_length) { + if (batch_size != 1) { + return ORT_MAKE_STATUS(ONNXRUNTIME, INVALID_ARGUMENT, + "batch_size must be 1 when sequence_length > 1 and past context is given."); + } + is_subsequent_prompt = true; } - is_subsequent_prompt = true; - } - bool is_first_prompt; - if (is_subsequent_prompt) { - is_first_prompt = false; // irrelevant for interactive decoding - } else { - // If not interactive, sequence_length is 1 for token gen and arbitrarily large for prompt is_first_prompt = (sequence_length == total_sequence_length); - if (!is_first_prompt && sequence_length != 1) { + if (!is_subsequent_prompt && !is_first_prompt && sequence_length != 1) { return ORT_MAKE_STATUS(ONNXRUNTIME, INVALID_ARGUMENT, "sequence_length shall be 1 when it is not prompt."); } diff --git a/onnxruntime/contrib_ops/webgpu/bert/flash_attention.cc b/onnxruntime/contrib_ops/webgpu/bert/flash_attention.cc index 1e69928f2a7ce..00f60142df159 100644 --- a/onnxruntime/contrib_ops/webgpu/bert/flash_attention.cc +++ b/onnxruntime/contrib_ops/webgpu/bert/flash_attention.cc @@ -31,9 +31,11 @@ Status CopyKVCacheProgram::GenerateShaderCode(ShaderHelper& shader) const { const auto& present_key = shader.AddOutput("present_key", ShaderUsage::UseUniform | ShaderUsage::UseIndicesTypeAlias); const auto& present_value = shader.AddOutput("present_value", ShaderUsage::UseUniform); const auto& copy_kv_shape = shader.AddIndices("copy_kv_shape"); + if (use_seqlen_k_) { + shader.AddInput("seqlen_k", ShaderUsage::None); + } // If prepare_indirect_dispatch is enabled, add seqlen_k input and indirect_buffer output if (prepare_indirect_dispatch_) { - shader.AddInput("seqlen_k", ShaderUsage::None); shader.AddOutput("indirect_buffer", ShaderUsage::None); } @@ -43,7 +45,7 @@ Status CopyKVCacheProgram::GenerateShaderCode(ShaderHelper& shader) const { " let sequence_id = output_indices[2];\n" " let num_head_id = output_indices[1];\n" " let batch = output_indices[0];\n"; - if (prepare_indirect_dispatch_) { + if (use_seqlen_k_) { shader.MainFunctionBody() << " let total_seq_length = u32(seqlen_k[0u]) + 1u;\n"; } else { shader.MainFunctionBody() << " let total_seq_length = uniforms.total_sequence_length;\n"; @@ -105,9 +107,10 @@ Status CopyKVCache(onnxruntime::webgpu::ComputeContext& context, const WebgpuAtt // Determine if we need to prepare indirect dispatch bool prepare_indirect_dispatch = (indirect_buffer != nullptr); + bool use_seqlen_k = (seqlen_k != nullptr); CopyKVCacheProgram program{"CopyKVCache", has_past, parameters.qkv_format_ == Q_K_V_BSNH_BNSH_BNSH, - prepare_indirect_dispatch}; + prepare_indirect_dispatch, use_seqlen_k}; if (parameters.qkv_format_ == Q_K_V_BSNH_BNSH_BNSH) { program.AddInputs({{K, ProgramTensorMetadataDependency::TypeAndRank, components}, {V, ProgramTensorMetadataDependency::TypeAndRank, components}}); @@ -119,7 +122,7 @@ Status CopyKVCache(onnxruntime::webgpu::ComputeContext& context, const WebgpuAtt {V, ProgramTensorMetadataDependency::TypeAndRank, reshaped_KV_shape, components}}); } - if (prepare_indirect_dispatch) { + if (use_seqlen_k) { program.AddInput({seqlen_k, ProgramTensorMetadataDependency::None}); } @@ -137,7 +140,7 @@ Status CopyKVCache(onnxruntime::webgpu::ComputeContext& context, const WebgpuAtt program.AddIndices(std::move(copy_kv_shape)); program.SetDispatchGroupSize(static_cast((copy_size + 63) / 64)) .SetWorkgroupSize(64) - .CacheHint(has_past, parameters.qkv_format_, parameters.past_present_share_buffer_, prepare_indirect_dispatch) + .CacheHint(has_past, parameters.qkv_format_, parameters.past_present_share_buffer_, prepare_indirect_dispatch, use_seqlen_k) .AddUniformVariables({{static_cast(copy_size)}, {static_cast(parameters.total_sequence_length_)}, {static_cast(parameters.kv_sequence_length_)}, @@ -167,6 +170,9 @@ Status FlashAttentionProgram::GenerateShaderCode(ShaderHelper& shader) const { if (has_attention_bias_) { shader.AddInput("attention_bias", ShaderUsage::UseUniform); } + if (use_seqlen_k_) { + shader.AddInput("seqlens_k", ShaderUsage::None); + } shader.AddOutput("output", ShaderUsage::UseUniform); return WGSL_TEMPLATE_APPLY(shader, "bert/flash_attention.wgsl.template", @@ -176,7 +182,8 @@ Status FlashAttentionProgram::GenerateShaderCode(ShaderHelper& shader) const { WGSL_TEMPLATE_PARAMETER(is_unidirectional, is_unidirectional_), WGSL_TEMPLATE_PARAMETER(prefer_subgroupshuffle, !is_nvidia_), WGSL_TEMPLATE_PARAMETER(qkv_head_size, qkv_head_size_), - WGSL_TEMPLATE_PARAMETER(qkv_num_heads, qkv_num_heads_)); + WGSL_TEMPLATE_PARAMETER(qkv_num_heads, qkv_num_heads_), + WGSL_TEMPLATE_PARAMETER(use_seqlen_k, use_seqlen_k_)); } Status FlashAttentionDecodeQKTProgram::GenerateShaderCode(ShaderHelper& shader) const { @@ -349,10 +356,12 @@ Status ApplyFlashAttention(const Tensor* Q, const Tensor* K, const Tensor* V, co // (batch_size, num_heads, total_sequence_length/max_sequence_length, head_size) const uint32_t present_sequence_length = static_cast(present_key->Shape()[2]); + const bool use_seqlen_k = seqlen_k != nullptr && context.IsGraphCaptureEnabled(); + if (parameters.sequence_length_ > 1) { const uint32_t tile_size = 64; // For encode path, use the original CopyKVCache without indirect dispatch preparation - ORT_RETURN_IF_ERROR(CopyKVCache(context, parameters, K, past_key, present_key, V, past_value, present_value, tile_size, seqlen_k, nullptr)); + ORT_RETURN_IF_ERROR(CopyKVCache(context, parameters, K, past_key, present_key, V, past_value, present_value, tile_size, use_seqlen_k ? seqlen_k : nullptr, nullptr)); bool has_attention_bias = attention_bias != nullptr; bool is_qualcomm = context.AdapterInfo().vendor == std::string_view{"qualcomm"}; bool is_nvidia = context.AdapterInfo().vendor == std::string_view{"nvidia"}; @@ -364,24 +373,27 @@ Status ApplyFlashAttention(const Tensor* Q, const Tensor* K, const Tensor* V, co parameters.head_size_, parameters.num_heads_, parameters.is_unidirectional_, - is_nvidia}; + is_nvidia, + use_seqlen_k}; program.AddInputs({{Q, ProgramTensorMetadataDependency::TypeAndRank, 4}, {present_key, ProgramTensorMetadataDependency::TypeAndRank, 4}, {present_value, ProgramTensorMetadataDependency::TypeAndRank, 4}}); if (has_attention_bias) { program.AddInputs({{attention_bias, ProgramTensorMetadataDependency::TypeAndRank}}); } + if (use_seqlen_k) { + program.AddInputs({{seqlen_k, ProgramTensorMetadataDependency::None}}); + } program.AddOutputs({{output, ProgramTensorMetadataDependency::TypeAndRank, 4}}); const float alpha = parameters.scale_ == 0.0f ? 1.f / sqrt(static_cast(parameters.head_size_)) : parameters.scale_; const uint32_t num_seq_tile = (parameters.sequence_length_ + tile_size - 1) / tile_size; program.SetDispatchGroupSize(parameters.num_heads_ * num_seq_tile) .SetWorkgroupSize(tile_size) - .CacheHint(has_attention_bias, parameters.head_size_, parameters.num_heads_, parameters.is_unidirectional_, is_qualcomm, is_nvidia) + .CacheHint(has_attention_bias, parameters.head_size_, parameters.num_heads_, parameters.is_unidirectional_, is_qualcomm, is_nvidia, use_seqlen_k) .AddUniformVariables({{static_cast(parameters.sequence_length_)}, {static_cast(parameters.total_sequence_length_)}, {static_cast(present_sequence_length)}, - {static_cast(parameters.total_sequence_length_ - parameters.kv_sequence_length_)}, {static_cast(parameters.n_reps)}, {alpha}, {num_seq_tile}}); diff --git a/onnxruntime/contrib_ops/webgpu/bert/flash_attention.h b/onnxruntime/contrib_ops/webgpu/bert/flash_attention.h index f372aeed0e563..9599c10533351 100644 --- a/onnxruntime/contrib_ops/webgpu/bert/flash_attention.h +++ b/onnxruntime/contrib_ops/webgpu/bert/flash_attention.h @@ -18,8 +18,8 @@ using namespace onnxruntime::webgpu; class CopyKVCacheProgram final : public Program { public: CopyKVCacheProgram(const std::string& kernel_name, bool has_past, bool kv_BNSH, - bool prepare_indirect_dispatch = false) - : Program{kernel_name}, has_past_(has_past), kv_BNSH_(kv_BNSH), prepare_indirect_dispatch_(prepare_indirect_dispatch) { + bool prepare_indirect_dispatch = false, bool use_seqlen_k = false) + : Program{kernel_name}, has_past_(has_past), kv_BNSH_(kv_BNSH), prepare_indirect_dispatch_(prepare_indirect_dispatch), use_seqlen_k_(use_seqlen_k) { } Status GenerateShaderCode(ShaderHelper& sh) const override; @@ -34,6 +34,7 @@ class CopyKVCacheProgram final : public Program { bool has_past_; bool kv_BNSH_; bool prepare_indirect_dispatch_; + bool use_seqlen_k_; }; class FlashAttentionProgram final : public Program { @@ -45,7 +46,8 @@ class FlashAttentionProgram final : public Program { int qkv_head_size, int qkv_num_heads, bool is_unidirectional, - bool is_nvidia) + bool is_nvidia, + bool use_seqlen_k = false) : Program{kernel_name}, has_attention_bias_(has_attention_bias), is_qualcomm_(is_qualcomm), @@ -53,7 +55,8 @@ class FlashAttentionProgram final : public Program { qkv_head_size_(qkv_head_size), qkv_num_heads_(qkv_num_heads), is_unidirectional_(is_unidirectional), - is_nvidia_(is_nvidia) { + is_nvidia_(is_nvidia), + use_seqlen_k_(use_seqlen_k) { } Status GenerateShaderCode(ShaderHelper& sh) const override; @@ -61,7 +64,6 @@ class FlashAttentionProgram final : public Program { WEBGPU_PROGRAM_DEFINE_UNIFORM_VARIABLES({"new_sequence_length", ProgramUniformVariableDataType::Uint32}, {"total_sequence_length", ProgramUniformVariableDataType::Uint32}, {"present_sequence_length", ProgramUniformVariableDataType::Uint32}, - {"past_sequence_length", ProgramUniformVariableDataType::Uint32}, {"n_reps", ProgramUniformVariableDataType::Uint32}, {"alpha", ProgramUniformVariableDataType::Float32}, {"num_seq_tile", ProgramUniformVariableDataType::Uint32}); @@ -74,6 +76,7 @@ class FlashAttentionProgram final : public Program { int qkv_num_heads_; bool is_unidirectional_; bool is_nvidia_; + bool use_seqlen_k_; }; class FlashAttentionDecodeQKTProgram final : public Program { diff --git a/onnxruntime/contrib_ops/webgpu/bert/flash_attention.wgsl.template b/onnxruntime/contrib_ops/webgpu/bert/flash_attention.wgsl.template index 0674702bd6030..a5922ec9512fd 100644 --- a/onnxruntime/contrib_ops/webgpu/bert/flash_attention.wgsl.template +++ b/onnxruntime/contrib_ops/webgpu/bert/flash_attention.wgsl.template @@ -6,10 +6,23 @@ #param prefer_subgroupshuffle #param qkv_head_size #param qkv_num_heads +#param use_seqlen_k const head_size : u32 = qkv_head_size; const num_heads : u32 = qkv_num_heads; +#if use_seqlen_k +// When graph capture is enabled, total_sequence_length is read from GPU buffer +fn get_total_sequence_length() -> u32 { + return u32(seqlens_k[0]) + 1u; +} +#else +// When graph capture is disabled, total_sequence_length comes from uniforms +fn get_total_sequence_length() -> u32 { + return uniforms.total_sequence_length; +} +#endif + #if is_fp16 const min_value = q_element_t(-65504.0); #else @@ -45,17 +58,17 @@ fn loadk(k_start : u32, head_idx : u32, local_idx : u32, k_step : u32) { let offset = head_idx * uniforms.present_sequence_length * head_size_vec + k_start * head_size_vec; for (var idx : u32 = local_idx; idx < head_size_vec * k_step; idx += workgroup_size_x) { let slot = u32(idx / head_size_vec); - let val = select(q_value_t(0), present_key[offset + idx], k_start + slot < uniforms.total_sequence_length); + let val = select(q_value_t(0), present_key[offset + idx], k_start + slot < get_total_sequence_length()); k_tile[slot][idx % head_size_vec] = val; } } -fn loadv(v_start : u32, head_idx : u32, local_idx : u32, k_step : u32) { +fn loadv(v_start : u32, head_idx : u32, local_idx : u32, v_step : u32) { // Stored as float16[batch_size,num_heads,present_sequence_length,96] let offset = head_idx * uniforms.present_sequence_length * head_size_vec + v_start * head_size_vec; - for (var idx : u32 = local_idx; idx < head_size_vec * k_step; idx += workgroup_size_x) { + for (var idx : u32 = local_idx; idx < head_size_vec * v_step; idx += workgroup_size_x) { let slot = u32(idx / head_size_vec); - let val = select(q_value_t(0), present_value[offset + idx], v_start + slot < uniforms.total_sequence_length); + let val = select(q_value_t(0), present_value[offset + idx], v_start + slot < get_total_sequence_length()); v_tile[slot][idx % head_size_vec] = val; } } @@ -93,12 +106,12 @@ fn writeo(o_idx_global : u32, head_idx : u32) { #if has_attention_bias fn loadAttentionBias(q_idx_global : u32, k_idx_global : u32, head_idx : u32) -> vec4 { // Stored as float16[batch_size,num_heads,new_seq_length,total_sequence_length] - if (q_idx_global >= uniforms.new_sequence_length || k_idx_global >= uniforms.total_sequence_length) { + if (q_idx_global >= uniforms.new_sequence_length || k_idx_global >= get_total_sequence_length()) { return vec4(0); } - let offset_base = head_idx * uniforms.new_sequence_length * uniforms.total_sequence_length + q_idx_global * uniforms.total_sequence_length; + let offset_base = head_idx * uniforms.new_sequence_length * get_total_sequence_length() + q_idx_global * get_total_sequence_length(); let offset = offset_base + k_idx_global; - let offset_max = offset_base + uniforms.total_sequence_length; + let offset_max = offset_base + get_total_sequence_length(); let c1 = q_element_t(attention_bias[min(offset, offset_max)]); let c2 = q_element_t(attention_bias[min(offset + 1, offset_max)]); let c3 = q_element_t(attention_bias[min(offset + 2, offset_max)]); @@ -141,16 +154,18 @@ $MAIN { var previous_max : q_element_t = min_value; var previous_denom : q_element_t = 0; + let total_sequence_length = get_total_sequence_length(); #if is_unidirectional // If attention is unidirectional, set the loop bound to enforce causal masking. - let max_causal_len_for_workgroup = uniforms.past_sequence_length + + let past_sequence_length = total_sequence_length - uniforms.new_sequence_length; + let max_causal_len_for_workgroup = past_sequence_length + (workgroup_idx % uniforms.num_seq_tile + 1) * workgroup_size_x; - let loop_bound = min(uniforms.total_sequence_length, max_causal_len_for_workgroup); - let seq_causal_length = uniforms.past_sequence_length + q_idx_global + 1; + let loop_bound = min(total_sequence_length, max_causal_len_for_workgroup); + let seq_causal_length = past_sequence_length + q_idx_global + 1; #else - let loop_bound = uniforms.total_sequence_length; - let seq_causal_length = uniforms.total_sequence_length; + let loop_bound = total_sequence_length; + let seq_causal_length = total_sequence_length; #endif for (var k_start = 0u; k_start < loop_bound; k_start += capped_sg_size) { diff --git a/onnxruntime/contrib_ops/webgpu/bert/group_query_attention.cc b/onnxruntime/contrib_ops/webgpu/bert/group_query_attention.cc index 80a909438aa73..cadc155092277 100644 --- a/onnxruntime/contrib_ops/webgpu/bert/group_query_attention.cc +++ b/onnxruntime/contrib_ops/webgpu/bert/group_query_attention.cc @@ -19,18 +19,6 @@ namespace onnxruntime { namespace contrib { namespace webgpu { -ONNX_OPERATOR_KERNEL_EX( - GroupQueryAttention, - kMSDomain, - 1, - kWebGpuExecutionProvider, - (*KernelDefBuilder::Create()) - .TypeConstraint("T", WebGpuSupportedFloatTypes()) - .MayInplace(3, 1) - .MayInplace(4, 2) - .InputMemoryType(OrtMemTypeCPUInput, 6), - GroupQueryAttention); - Status SplitPackedQKVProgram::GenerateShaderCode(ShaderHelper& sh) const { const auto& packed_qkv = sh.AddInput("packed_qkv", ShaderUsage::UseOffsetToIndices | ShaderUsage::UseUniform); const auto& query = sh.AddOutput("query", ShaderUsage::UseSetByIndices | ShaderUsage::UseUniform); @@ -270,6 +258,29 @@ Status GroupQueryAttention::ComputeInternal(onnxruntime::webgpu::ComputeContext& present_value, parameters, context, head_sink, seqlen_k, local_window_size_); } +KernelCreateInfo CreateGroupQueryAttentionKernelInfo(bool enable_graph_capture) { + KernelDefBuilder builder; + builder.SetName("GroupQueryAttention") + .SetDomain(kMSDomain) + .SinceVersion(1) + .Provider(kWebGpuExecutionProvider) + .TypeConstraint("T", WebGpuSupportedFloatTypes()) + .MayInplace(3, 1) + .MayInplace(4, 2); + + // Only set InputMemoryType to CPU when graph capture is disabled + if (!enable_graph_capture) { + builder.InputMemoryType(OrtMemTypeCPUInput, 6); + } + + return KernelCreateInfo( + builder.Build(), + [](FuncManager&, const OpKernelInfo& info, std::unique_ptr& out) -> Status { + out = std::make_unique(info); + return Status::OK(); + }); +} + } // namespace webgpu } // namespace contrib } // namespace onnxruntime diff --git a/onnxruntime/contrib_ops/webgpu/bert/group_query_attention.h b/onnxruntime/contrib_ops/webgpu/bert/group_query_attention.h index 77ecc047636e3..a26f8c48435d8 100644 --- a/onnxruntime/contrib_ops/webgpu/bert/group_query_attention.h +++ b/onnxruntime/contrib_ops/webgpu/bert/group_query_attention.h @@ -58,6 +58,8 @@ class GroupQueryAttention final : public WebGpuKernel { Status ComputeInternal(onnxruntime::webgpu::ComputeContext& context) const override; }; +KernelCreateInfo CreateGroupQueryAttentionKernelInfo(bool enable_graph_capture); + } // namespace webgpu } // namespace contrib } // namespace onnxruntime diff --git a/onnxruntime/contrib_ops/webgpu/webgpu_contrib_kernels.cc b/onnxruntime/contrib_ops/webgpu/webgpu_contrib_kernels.cc index 728be355a2679..fe0bc5dee92ff 100644 --- a/onnxruntime/contrib_ops/webgpu/webgpu_contrib_kernels.cc +++ b/onnxruntime/contrib_ops/webgpu/webgpu_contrib_kernels.cc @@ -2,6 +2,7 @@ // Licensed under the MIT License. #include "contrib_ops/webgpu/webgpu_contrib_kernels.h" +#include "contrib_ops/webgpu/bert/group_query_attention.h" #include "core/framework/op_kernel.h" @@ -34,7 +35,7 @@ KernelCreateInfo BuildKernelCreateInfo() { return info; } -Status RegisterWebGpuContribKernels(KernelRegistry& kernel_registry) { +Status RegisterWebGpuContribKernels(KernelRegistry& kernel_registry, bool enable_graph_capture) { static const BuildKernelCreateInfoFn function_table[] = { BuildKernelCreateInfo, // default entry to avoid the list become empty after ops-reducing BuildKernelCreateInfo, @@ -44,7 +45,6 @@ Status RegisterWebGpuContribKernels(KernelRegistry& kernel_registry) { BuildKernelCreateInfo, BuildKernelCreateInfo, BuildKernelCreateInfo, - BuildKernelCreateInfo, BuildKernelCreateInfo, BuildKernelCreateInfo, BuildKernelCreateInfo, @@ -61,6 +61,10 @@ Status RegisterWebGpuContribKernels(KernelRegistry& kernel_registry) { ORT_RETURN_IF_ERROR(kernel_registry.Register(std::move(info))); } } + + // Register GroupQueryAttention with conditional InputMemoryType based on graph capture + ORT_RETURN_IF_ERROR(kernel_registry.Register(CreateGroupQueryAttentionKernelInfo(enable_graph_capture))); + return Status::OK(); } diff --git a/onnxruntime/contrib_ops/webgpu/webgpu_contrib_kernels.h b/onnxruntime/contrib_ops/webgpu/webgpu_contrib_kernels.h index d73859de78239..a4fcfb8390798 100644 --- a/onnxruntime/contrib_ops/webgpu/webgpu_contrib_kernels.h +++ b/onnxruntime/contrib_ops/webgpu/webgpu_contrib_kernels.h @@ -13,7 +13,7 @@ namespace webgpu { template KernelCreateInfo BuildKernelCreateInfo(); -Status RegisterWebGpuContribKernels(KernelRegistry& kernel_registry); +Status RegisterWebGpuContribKernels(KernelRegistry& kernel_registry, bool enable_graph_capture = false); } // namespace webgpu } // namespace contrib diff --git a/onnxruntime/core/providers/webgpu/webgpu_execution_provider.cc b/onnxruntime/core/providers/webgpu/webgpu_execution_provider.cc index 89fc13d26269f..3df194217933e 100644 --- a/onnxruntime/core/providers/webgpu/webgpu_execution_provider.cc +++ b/onnxruntime/core/providers/webgpu/webgpu_execution_provider.cc @@ -780,7 +780,7 @@ std::unique_ptr RegisterKernels(bool enable_graph_capture = fals ORT_THROW_IF_ERROR(kernel_registry->Register(CreateCastKernelInfo<23>(enable_graph_capture))); #ifndef DISABLE_CONTRIB_OPS - Status status = ::onnxruntime::contrib::webgpu::RegisterWebGpuContribKernels(*kernel_registry); + Status status = ::onnxruntime::contrib::webgpu::RegisterWebGpuContribKernels(*kernel_registry, enable_graph_capture); ORT_ENFORCE(status.IsOK(), "Failed to register WebGPU contrib kernels: " + status.ErrorMessage()); #endif From df418e21f17816686c912f754d60776ea1631a66 Mon Sep 17 00:00:00 2001 From: Changming Sun Date: Tue, 28 Oct 2025 20:13:42 -0700 Subject: [PATCH 18/33] Add int8/uint8 support for Max and Min operators (#26386) --- docs/OperatorKernels.md | 8 +-- .../providers/cpu/math/element_wise_ops.cc | 12 ++-- .../cpu/math/element_wise_ops_test.cc | 68 +++++++++++++++++++ 3 files changed, 80 insertions(+), 8 deletions(-) diff --git a/docs/OperatorKernels.md b/docs/OperatorKernels.md index 0d66e69c8e925..73b38afff34f3 100644 --- a/docs/OperatorKernels.md +++ b/docs/OperatorKernels.md @@ -242,8 +242,8 @@ Do not modify directly.* |||[9, 12]|**T** = tensor(double), tensor(float), tensor(int32), tensor(int64), tensor(uint32), tensor(uint64)| |||[1, 8]|**T** = tensor(double), tensor(float)| |MatMulInteger|*in* A:**T1**
*in* B:**T2**
*in* a_zero_point:**T1**
*in* b_zero_point:**T2**
*out* Y:**T3**|10+|**T1** = tensor(int8), tensor(uint8)
**T2** = tensor(int8), tensor(uint8)
**T3** = tensor(int32)| -|Max|*in* data_0:**T**
*out* max:**T**|13+|**T** = tensor(double), tensor(float), tensor(float16), tensor(int32), tensor(int64), tensor(uint32), tensor(uint64)| -|||12|**T** = tensor(double), tensor(float), tensor(float16), tensor(int32), tensor(int64), tensor(uint32), tensor(uint64)| +|Max|*in* data_0:**T**
*out* max:**T**|13+|**T** = tensor(double), tensor(float), tensor(float16), tensor(int32), tensor(int64), tensor(int8), tensor(uint32), tensor(uint64), tensor(uint8)| +|||12|**T** = tensor(double), tensor(float), tensor(float16), tensor(int32), tensor(int64), tensor(int8), tensor(uint32), tensor(uint64), tensor(uint8)| |||[8, 11]|**T** = tensor(double), tensor(float)| |||[6, 7]|**T** = tensor(float)| |MaxPool|*in* X:**T**
*out* Y:**T**

or

*in* X:**T**
*out* Y:**T**
*out* Indices:**I**|22+|**I** = tensor(int64)
**T** = tensor(double), tensor(float), tensor(int8), tensor(uint8)| @@ -263,8 +263,8 @@ Do not modify directly.* |MelWeightMatrix|*in* num_mel_bins:**T1**
*in* dft_length:**T1**
*in* sample_rate:**T1**
*in* lower_edge_hertz:**T2**
*in* upper_edge_hertz:**T2**
*out* output:**T3**|17+|**T1** = tensor(int32), tensor(int64)
**T2** = tensor(float)
**T3** = tensor(double), tensor(float), tensor(int16), tensor(int32), tensor(int64), tensor(int8), tensor(uint16), tensor(uint32), tensor(uint64), tensor(uint8)| |MemcpyFromHost|*in* X:**T**
*out* Y:**T**|1+|**T** = seq(tensor(bfloat16)), seq(tensor(bool)), seq(tensor(double)), seq(tensor(float)), seq(tensor(float16)), seq(tensor(float8e4m3fn)), seq(tensor(float8e4m3fnuz)), seq(tensor(float8e5m2)), seq(tensor(float8e5m2fnuz)), seq(tensor(int16)), seq(tensor(int32)), seq(tensor(int64)), seq(tensor(int8)), seq(tensor(uint16)), seq(tensor(uint32)), seq(tensor(uint64)), seq(tensor(uint8)), tensor(bfloat16), tensor(bool), tensor(double), tensor(float), tensor(float16), tensor(float8e4m3fn), tensor(float8e4m3fnuz), tensor(float8e5m2), tensor(float8e5m2fnuz), tensor(int16), tensor(int32), tensor(int64), tensor(int8), tensor(uint16), tensor(uint32), tensor(uint64), tensor(uint8)| |MemcpyToHost|*in* X:**T**
*out* Y:**T**|1+|**T** = seq(tensor(bfloat16)), seq(tensor(bool)), seq(tensor(double)), seq(tensor(float)), seq(tensor(float16)), seq(tensor(float8e4m3fn)), seq(tensor(float8e4m3fnuz)), seq(tensor(float8e5m2)), seq(tensor(float8e5m2fnuz)), seq(tensor(int16)), seq(tensor(int32)), seq(tensor(int64)), seq(tensor(int8)), seq(tensor(uint16)), seq(tensor(uint32)), seq(tensor(uint64)), seq(tensor(uint8)), tensor(bfloat16), tensor(bool), tensor(double), tensor(float), tensor(float16), tensor(float8e4m3fn), tensor(float8e4m3fnuz), tensor(float8e5m2), tensor(float8e5m2fnuz), tensor(int16), tensor(int32), tensor(int64), tensor(int8), tensor(uint16), tensor(uint32), tensor(uint64), tensor(uint8)| -|Min|*in* data_0:**T**
*out* min:**T**|13+|**T** = tensor(double), tensor(float), tensor(float16), tensor(int32), tensor(int64), tensor(uint32), tensor(uint64)| -|||12|**T** = tensor(double), tensor(float), tensor(float16), tensor(int32), tensor(int64), tensor(uint32), tensor(uint64)| +|Min|*in* data_0:**T**
*out* min:**T**|13+|**T** = tensor(double), tensor(float), tensor(float16), tensor(int32), tensor(int64), tensor(int8), tensor(uint32), tensor(uint64), tensor(uint8)| +|||12|**T** = tensor(double), tensor(float), tensor(float16), tensor(int32), tensor(int64), tensor(int8), tensor(uint32), tensor(uint64), tensor(uint8)| |||[8, 11]|**T** = tensor(double), tensor(float)| |||[6, 7]|**T** = tensor(float)| |Mod|*in* A:**T**
*in* B:**T**
*out* C:**T**|13+|**T** = tensor(double), tensor(float), tensor(float16), tensor(int16), tensor(int32), tensor(int64), tensor(int8), tensor(uint16), tensor(uint32), tensor(uint64), tensor(uint8)| diff --git a/onnxruntime/core/providers/cpu/math/element_wise_ops.cc b/onnxruntime/core/providers/cpu/math/element_wise_ops.cc index 72300d028501a..b940d71e1165e 100644 --- a/onnxruntime/core/providers/cpu/math/element_wise_ops.cc +++ b/onnxruntime/core/providers/cpu/math/element_wise_ops.cc @@ -20,14 +20,16 @@ namespace op_kernel_type_control { ORT_SPECIFY_OP_KERNEL_ARG_DEFAULT_TYPES(kCpuExecutionProvider, kOnnxDomain, Max, 8, Input, 0, float, double); ORT_SPECIFY_OP_KERNEL_ARG_DEFAULT_TYPES(kCpuExecutionProvider, kOnnxDomain, Max, 12, Input, 0, - float, double, MLFloat16, int32_t, uint32_t, int64_t, uint64_t); + float, double, MLFloat16, int8_t, int32_t, uint32_t, + int64_t, uint8_t, uint64_t); ORT_SPECIFY_OP_KERNEL_ARG_REQUIRED_TYPES(kCpuExecutionProvider, kOnnxDomain, Max, 12, Input, 0, int32_t, int64_t); // Min ORT_SPECIFY_OP_KERNEL_ARG_DEFAULT_TYPES(kCpuExecutionProvider, kOnnxDomain, Min, 8, Input, 0, float, double); ORT_SPECIFY_OP_KERNEL_ARG_DEFAULT_TYPES(kCpuExecutionProvider, kOnnxDomain, Min, 12, Input, 0, - float, double, MLFloat16, int32_t, uint32_t, int64_t, uint64_t); + float, double, MLFloat16, int8_t, int32_t, uint32_t, + int64_t, uint8_t, uint64_t); ORT_SPECIFY_OP_KERNEL_ARG_REQUIRED_TYPES(kCpuExecutionProvider, kOnnxDomain, Min, 12, Input, 0, int32_t, int64_t); @@ -989,7 +991,8 @@ Status Min_8::Compute(OpKernelContext* context) const { return MinMaxMLFloat16(*this, context); break; default: - utils::MLTypeCallDispatcher + utils::MLTypeCallDispatcher t_disp(dt_type); return t_disp.InvokeRet(*this, context); } @@ -1055,7 +1058,8 @@ Status Max_8::Compute(OpKernelContext* context) const { return MinMaxMLFloat16(*this, context); break; default: - utils::MLTypeCallDispatcher + utils::MLTypeCallDispatcher t_disp(dt_type); return t_disp.InvokeRet(*this, context); } diff --git a/onnxruntime/test/providers/cpu/math/element_wise_ops_test.cc b/onnxruntime/test/providers/cpu/math/element_wise_ops_test.cc index d848865f719b8..cbb8ca43e8f06 100644 --- a/onnxruntime/test/providers/cpu/math/element_wise_ops_test.cc +++ b/onnxruntime/test/providers/cpu/math/element_wise_ops_test.cc @@ -3700,6 +3700,74 @@ TEST(MathOpTest, Equal_multidirectional_broadcastAB_bool) { test.Run(); } +TEST(MathOpTest, Max_12_Int8) { + OpTester test("Max", 12); + test.AddInput("data_0", {1, 3}, + {1, 2, 3}); + test.AddInput("data_2", {3, 3}, + {10, 20, 30, + 40, 50, 60, + 70, 80, 90}); + test.AddInput("data_1", {3, 1}, + {-1, -2, 127}); + test.AddOutput("max", {3, 3}, + {10, 20, 30, + 40, 50, 60, + 127, 127, 127}); + test.Run(OpTester::ExpectResult::kExpectSuccess, "", {kTensorrtExecutionProvider, kOpenVINOExecutionProvider}); +} + +TEST(MathOpTest, Max_12_UInt8) { + OpTester test("Max", 12); + test.AddInput("data_0", {1, 3}, + {1, 20, 30}); + test.AddInput("data_2", {3, 3}, + {10, 20, 30, + 40, 50, 60, + 70, 80, 90}); + test.AddInput("data_1", {3, 1}, + {100, 20, 30}); + test.AddOutput("max", {3, 3}, + {100, 100, 100, + 40, 50, 60, + 70, 80, 90}); + test.Run(OpTester::ExpectResult::kExpectSuccess, "", {kTensorrtExecutionProvider}); +} + +TEST(MathOpTest, Min_12_Int8) { + OpTester test("Min", 12); + test.AddInput("data_0", {1, 3}, + {1, 2, 3}); + test.AddInput("data_2", {3, 3}, + {10, 20, 30, + 40, 50, 60, + -70, -80, -90}); + test.AddInput("data_1", {3, 1}, + {-1, 20, 127}); + test.AddOutput("min", {3, 3}, + {-1, -1, -1, + 1, 2, 3, + -70, -80, -90}); + test.Run(OpTester::ExpectResult::kExpectSuccess, "", {kTensorrtExecutionProvider, kOpenVINOExecutionProvider}); +} + +TEST(MathOpTest, Min_12_UInt8) { + OpTester test("Min", 12); + test.AddInput("data_0", {1, 3}, + {1, 20, 30}); + test.AddInput("data_2", {3, 3}, + {10, 20, 30, + 40, 50, 60, + 70, 80, 90}); + test.AddInput("data_1", {3, 1}, + {1, 20, 30}); + test.AddOutput("min", {3, 3}, + {1, 1, 1, + 1, 20, 20, + 1, 20, 30}); + test.Run(OpTester::ExpectResult::kExpectSuccess, "", {kTensorrtExecutionProvider}); +} + TEST(MathOpTest, Mean_6) { OpTester test("Mean", 6); std::vector dims{3, 3}; From 80b6e931f2aa0ce87cad1b8fbaeb85ff9c1f7554 Mon Sep 17 00:00:00 2001 From: Wanming Lin Date: Wed, 29 Oct 2025 11:20:44 +0800 Subject: [PATCH 19/33] [WebNN] Fallback int64 indices to int32 (#26308) ONNX's ScatterND and ScatterElements limit their indices input to int64, but some WebNN backends only support int32 indices. As a workaround for such backends, we can insert a Cast operation to convert the data type. --- .../core/providers/webnn/builders/helper.cc | 11 +++++++++ .../core/providers/webnn/builders/helper.h | 4 ++++ .../impl/scatterElements_op_builder.cc | 23 +++++++++++++++---- .../builders/impl/scatterND_op_builder.cc | 23 ++++++++++++++++--- 4 files changed, 54 insertions(+), 7 deletions(-) diff --git a/onnxruntime/core/providers/webnn/builders/helper.cc b/onnxruntime/core/providers/webnn/builders/helper.cc index 9056ea6d86f65..dc290209b0385 100644 --- a/onnxruntime/core/providers/webnn/builders/helper.cc +++ b/onnxruntime/core/providers/webnn/builders/helper.cc @@ -439,5 +439,16 @@ uint16_t PackFloat32ToUint16AsFloat16(float value) { return sign_float16 | (exponent_float16 << 10) | mantissa_float16; } +// Check if it can fallback to int32 if the input of WebNN op doesn't support int64. +bool CanFallbackInt64ToInt32(const emscripten::val& wnn_limits, + const std::string& webnn_op_type, + const std::string& input_name) { + emscripten::val supported_data_types = wnn_limits[webnn_op_type][input_name]["dataTypes"]; + + return !supported_data_types.isUndefined() && + !supported_data_types.call("includes", emscripten::val("int64")).as() && + supported_data_types.call("includes", emscripten::val("int32")).as(); +} + } // namespace webnn } // namespace onnxruntime diff --git a/onnxruntime/core/providers/webnn/builders/helper.h b/onnxruntime/core/providers/webnn/builders/helper.h index fbabc23504636..0bfbb3c90543c 100644 --- a/onnxruntime/core/providers/webnn/builders/helper.h +++ b/onnxruntime/core/providers/webnn/builders/helper.h @@ -297,5 +297,9 @@ bool IsMLTensorSupported(); uint8_t PackInt8ToUint8DoubledNibbles(int8_t value, const int32_t& data_type); uint16_t PackFloat32ToUint16AsFloat16(float value); +bool CanFallbackInt64ToInt32(const emscripten::val& wnn_limits, + const std::string& webnn_op_type, + const std::string& input_name); + } // namespace webnn } // namespace onnxruntime diff --git a/onnxruntime/core/providers/webnn/builders/impl/scatterElements_op_builder.cc b/onnxruntime/core/providers/webnn/builders/impl/scatterElements_op_builder.cc index c2974bd988f6b..dd596b96fa8c0 100644 --- a/onnxruntime/core/providers/webnn/builders/impl/scatterElements_op_builder.cc +++ b/onnxruntime/core/providers/webnn/builders/impl/scatterElements_op_builder.cc @@ -24,6 +24,7 @@ class ScatterElementsOpBuilder : public BaseOpBuilder { const WebnnDeviceType /* device_type */, const logging::Logger& logger) const override; bool HasSupportedInputsImpl(const GraphViewer& graph_viewer, const Node& node, const emscripten::val& wnn_limits, const logging::Logger& logger) const override; + mutable bool can_fallback_int64_to_int32_ = false; }; // Add operator related. @@ -35,7 +36,13 @@ Status ScatterElementsOpBuilder::AddToModelBuilderImpl(ModelBuilder& model_build emscripten::val indices = model_builder.GetOperand(input_defs[1]->Name()); emscripten::val updates = model_builder.GetOperand(input_defs[2]->Name()); emscripten::val options = emscripten::val::object(); - options.set("label", node.Name()); + + // ONNX specifies that indices must use int64, but some WebNN backends only support int32. + // As a workaround for such backends, we can insert a Cast operation to convert the data type. + if (can_fallback_int64_to_int32_) { + options.set("label", node.Name() + "_cast_indices_to_int32"); + indices = model_builder.GetBuilder().call("cast", indices, emscripten::val("int32"), options); + } std::vector input_shape; ORT_RETURN_IF_NOT(GetShape(*input_defs[0], input_shape, logger), "Cannot get shape"); @@ -43,6 +50,7 @@ Status ScatterElementsOpBuilder::AddToModelBuilderImpl(ModelBuilder& model_build NodeAttrHelper helper(node); const uint32_t axis = static_cast(HandleNegativeAxis(helper.Get("axis", 0), rank)); options.set("axis", axis); + options.set("label", node.Name()); emscripten::val output = model_builder.GetBuilder().call("scatterElements", data, indices, updates, options); @@ -86,9 +94,16 @@ bool ScatterElementsOpBuilder::HasSupportedInputsImpl(const GraphViewer&, const const std::string_view op_type = node.OpType(); - return IsDataTypeSupportedByOp(op_type, data_type, wnn_limits, "input", "data", logger) && - IsDataTypeSupportedByOp(op_type, indices_type, wnn_limits, "indices", "indices", logger) && - IsInputRankSupportedByOp(node, wnn_limits, logger); + if (!IsDataTypeSupportedByOp(op_type, data_type, wnn_limits, "input", "data", logger) || + !IsInputRankSupportedByOp(node, wnn_limits, logger)) { + return false; + } + + // ONNX specifies that indices must use int64, but some WebNN backends only support int32. + // Allows to use int32 as a workaround for such backends. + can_fallback_int64_to_int32_ = CanFallbackInt64ToInt32(wnn_limits, "scatterElements", "indices"); + return can_fallback_int64_to_int32_ || + IsDataTypeSupportedByOp(op_type, indices_type, wnn_limits, "indices", "indices", logger); } void CreateScatterElementsOpBuilder(const std::string& op_type, OpBuilderRegistrations& op_registrations) { diff --git a/onnxruntime/core/providers/webnn/builders/impl/scatterND_op_builder.cc b/onnxruntime/core/providers/webnn/builders/impl/scatterND_op_builder.cc index a7788cfd847e9..4754ba07dc649 100644 --- a/onnxruntime/core/providers/webnn/builders/impl/scatterND_op_builder.cc +++ b/onnxruntime/core/providers/webnn/builders/impl/scatterND_op_builder.cc @@ -24,6 +24,7 @@ class ScatterNDOpBuilder : public BaseOpBuilder { const WebnnDeviceType /* device_type */, const logging::Logger& logger) const override; bool HasSupportedInputsImpl(const GraphViewer& graph_viewer, const Node& node, const emscripten::val& wnn_limits, const logging::Logger& logger) const override; + mutable bool can_fallback_int64_to_int32_ = false; }; // Add operator related. @@ -35,6 +36,14 @@ Status ScatterNDOpBuilder::AddToModelBuilderImpl(ModelBuilder& model_builder, co emscripten::val indices = model_builder.GetOperand(input_defs[1]->Name()); emscripten::val updates = model_builder.GetOperand(input_defs[2]->Name()); emscripten::val options = emscripten::val::object(); + + // ONNX specifies that indices must use int64, but some WebNN backends only support int32. + // As a workaround for such backends, we can insert a Cast operation to convert the data type. + if (can_fallback_int64_to_int32_) { + options.set("label", node.Name() + "_cast_indices_to_int32"); + indices = model_builder.GetBuilder().call("cast", indices, emscripten::val("int32"), options); + } + options.set("label", node.Name()); emscripten::val output = model_builder.GetBuilder().call("scatterND", data, indices, updates, options); @@ -76,9 +85,17 @@ bool ScatterNDOpBuilder::HasSupportedInputsImpl(const GraphViewer&, const Node& return false; } const std::string_view op_type = node.OpType(); - return IsDataTypeSupportedByOp(op_type, data_type, wnn_limits, "input", "data", logger) && - IsDataTypeSupportedByOp(op_type, indices_type, wnn_limits, "indices", "indices", logger) && - IsInputRankSupportedByOp(node, wnn_limits, logger); + + if (!IsDataTypeSupportedByOp(op_type, data_type, wnn_limits, "input", "data", logger) || + !IsInputRankSupportedByOp(node, wnn_limits, logger)) { + return false; + } + + // ONNX specifies that indices must use int64, but some WebNN backends only support int32. + // Allows to use int32 as a workaround for such backends. + can_fallback_int64_to_int32_ = CanFallbackInt64ToInt32(wnn_limits, "scatterND", "indices"); + return can_fallback_int64_to_int32_ || + IsDataTypeSupportedByOp(op_type, indices_type, wnn_limits, "indices", "indices", logger); } void CreateScatterNDOpBuilder(const std::string& op_type, OpBuilderRegistrations& op_registrations) { From 34b7558efde040e1b7cd017a9429dffa70ddae5f Mon Sep 17 00:00:00 2001 From: Baiju Meswani Date: Tue, 28 Oct 2025 23:07:51 -0700 Subject: [PATCH 20/33] Add QC license to the ort foundry package (#26428) --- .../c-api-artifacts-package-and-publish-steps-windows-qnn.yml | 1 + tools/nuget/generate_nuspec_for_custom_nuget.py | 3 +++ 2 files changed, 4 insertions(+) diff --git a/tools/ci_build/github/azure-pipelines/templates/c-api-artifacts-package-and-publish-steps-windows-qnn.yml b/tools/ci_build/github/azure-pipelines/templates/c-api-artifacts-package-and-publish-steps-windows-qnn.yml index 72343613d6b26..d9565675da63f 100644 --- a/tools/ci_build/github/azure-pipelines/templates/c-api-artifacts-package-and-publish-steps-windows-qnn.yml +++ b/tools/ci_build/github/azure-pipelines/templates/c-api-artifacts-package-and-publish-steps-windows-qnn.yml @@ -88,6 +88,7 @@ steps: copy $(Build.BinariesDirectory)\${{parameters.buildConfig}}\${{parameters.buildConfig}}\QnnHtpV73Stub.dll $(Build.BinariesDirectory)\${{parameters.artifactName}}\lib copy $(Build.BinariesDirectory)\${{parameters.buildConfig}}\${{parameters.buildConfig}}\QnnSaver.dll $(Build.BinariesDirectory)\${{parameters.artifactName}}\lib copy $(Build.BinariesDirectory)\${{parameters.buildConfig}}\${{parameters.buildConfig}}\QnnSystem.dll $(Build.BinariesDirectory)\${{parameters.artifactName}}\lib + copy $(Build.BinariesDirectory)\${{parameters.buildConfig}}\${{parameters.buildConfig}}\Qualcomm_LICENSE.pdf $(Build.BinariesDirectory)\${{parameters.artifactName}} # copy trt ep libraries only when trt ep is enabled copy $(Build.BinariesDirectory)\${{parameters.buildConfig}}\${{parameters.buildConfig}}\onnxruntime_providers_tensorrt.dll $(Build.BinariesDirectory)\${{parameters.artifactName}}\lib diff --git a/tools/nuget/generate_nuspec_for_custom_nuget.py b/tools/nuget/generate_nuspec_for_custom_nuget.py index 4421bf3ba56b5..291ff67f801b6 100644 --- a/tools/nuget/generate_nuspec_for_custom_nuget.py +++ b/tools/nuget/generate_nuspec_for_custom_nuget.py @@ -51,6 +51,9 @@ def generate_files(lines, args): files_list.append( f'' ) + files_list.append( + f'' + ) source_props = os.path.join( args.root_dir, From a958614ddb9181a8fabc997163e5c0b1a6dc2159 Mon Sep 17 00:00:00 2001 From: Wenqin Yang Date: Thu, 30 Oct 2025 05:00:38 +0800 Subject: [PATCH 21/33] Bug fix for conv1d (#26421) ### Description We don't want to adjusted the dispatch size when we try to run `Conv1d`. ### Motivation and Context --- onnxruntime/core/providers/webgpu/tensor/transpose.cc | 10 ++++++---- 1 file changed, 6 insertions(+), 4 deletions(-) diff --git a/onnxruntime/core/providers/webgpu/tensor/transpose.cc b/onnxruntime/core/providers/webgpu/tensor/transpose.cc index 1458eceb3e244..04e3b09a8b790 100644 --- a/onnxruntime/core/providers/webgpu/tensor/transpose.cc +++ b/onnxruntime/core/providers/webgpu/tensor/transpose.cc @@ -168,10 +168,12 @@ Status Transpose::DoTranspose(onnxruntime::webgpu::ComputeContext& context, // // TODO: Revert this change once the driver issue is fixed. if (context.AdapterInfo().vendor == std::string_view{"intel"}) { - ORT_ENFORCE(rank == static_cast(4), "Input tensor must have rank 4."); - dispatch_x = ceil_div(input_shape[0] * input_shape[1], 2); - dispatch_y = ceil_div(input_shape[2], 4); - dispatch_z = ceil_div(input_shape[3], 8); + // Only adjusted the dispatch size when rank is 4 yet. + if (rank == static_cast(4)) { + dispatch_x = ceil_div(input_shape[0] * input_shape[1], 2); + dispatch_y = ceil_div(input_shape[2], 4); + dispatch_z = ceil_div(input_shape[3], 8); + } } program.SetDispatchGroupSize(dispatch_x, dispatch_y, dispatch_z); } From 860d0853a6eefdf19e21b0e9982bde2ffbc8a65d Mon Sep 17 00:00:00 2001 From: Adrian Lizarraga Date: Wed, 29 Oct 2025 15:10:05 -0700 Subject: [PATCH 22/33] [Plugin EP] Allow EP to provide additional virtual devices (#26234) ### Description Adds APIs to allow a plugin EP to create a virtual `OrtHardwareDevice` that can be used for model cross-compilation. For example, this allows an EP to create a compiled model for NPU on a device that does not have an NPU. #### Application code An application must explicitly allow registered plugin EPs to create virtual devices. This is currently done by using a registration name that ends in the `".virtual"` suffix. Ex: ```c++ #include "onnxruntime_cxx_api.h" #include "onnxruntime_ep_device_ep_metadata_keys.h" const char* ep_registration_name = "my_ep_lib.virtual"; // IMPORTANT: ".virtual" suffix is a signal to EP library ort_env->RegisterExecutionProviderLibrary(ep_registration_name, "my_ep.dll"); std::vector ep_devices = ort_env->GetEpDevices(); // ep_devices includes an OrtEpDevice from "my_ep.dll" that uses a virtual OrtHardwareDevice. Ort::ConstEpDevice virtual_ep_device = std::find_if(ep_devices.begin(), ep_devices.end(), [](Ort::ConstEpDevice& device) { return device.EpName() == std::string("MyEpName"); }); // App can look in HW metadata to check if is virtual Ort::ConstHardwareDevice virtual_hw_device = virtual_ep_device.Device(); std::unordered_map metadata = virtual_hw_device.Metadata().GetKeyValuePairs(); assert(metadata[kOrtHardwareDevice_MetadataKey_IsVirtual] == "1"); // App can use the virtual OrtEpDevice in a session to, for example, compile a model // ... ``` #### Plugin EP code This PR introduces a new _optional_ C API function in the `OrtEpFactory` struct called `SetEnvironmentOptions` that allows ORT to pass options (as key/value pairs) to an EP factory. Currently, the only key supported is `"allow_virtual_devices"`, which indicates to the EP factory that creating virtual devices is allowed. When the application registers a plugin EP library, ORT creates the library's EP factories and checks if they implement the `SetEnvironmentOptions` API function. If so, ORT calls `ep_factory.SetEnvironmentOptions` with `"allow_virtual_devices"` set to `"1"` if the EP registration name set by the application ends in the `".virtual"` suffix (or `"0"` otherwise). Here's an example implementation of `OrtEpFactory::SetEnvironmentOptions` taken from a [test plugin EP that supports a virtual GPU](https://github.com/microsoft/onnxruntime/tree/adrianl/plugin-ep-specify-ort-hw-device/onnxruntime/test/autoep/library/example_plugin_ep_virt_gpu): ```c++ /*static*/ OrtStatus* ORT_API_CALL EpFactoryVirtualGpu::SetEnvironmentOptionsImpl(OrtEpFactory* this_ptr, const OrtKeyValuePairs* options) noexcept { auto* factory = static_cast(this_ptr); const char* value = factory->ort_api_.GetKeyValue(options, "allow_virtual_devices"); if (value != nullptr) { factory->allow_virtual_devices_ = strcmp(value, "1") == 0; } return nullptr; } ``` An EP factory can create a virtual hardware device within `OrtEpFactory::GetSupportedDevices` by using a new API function called `CreateHardwareDevice`. The EP factory is expected to own the hardware device instance, which should be released when the factory is destroyed via `ReleaseHardwareDevice`. The [test plugin EP shows an implementation](https://github.com/microsoft/onnxruntime/blob/d87f8b86406525f5801a7a9933b1ced1eb40940c/onnxruntime/test/autoep/library/example_plugin_ep_virt_gpu/ep_factory.cc#L86) of `OrtEpFactory::GetSupportedDevices` that creates a virtual GPU device. ```c++ /*static*/ OrtStatus* ORT_API_CALL EpFactoryVirtualGpu::GetSupportedDevicesImpl(OrtEpFactory* this_ptr, const OrtHardwareDevice* const* /*devices*/, size_t /*num_devices*/, OrtEpDevice** ep_devices, size_t max_ep_devices, size_t* p_num_ep_devices) noexcept { size_t& num_ep_devices = *p_num_ep_devices; auto* factory = static_cast(this_ptr); num_ep_devices = 0; // Create a virtual OrtHardwareDevice if application indicated it is allowed (e.g., for cross-compiling). // This example EP creates a virtual GPU OrtHardwareDevice and adds a new OrtEpDevice that uses the virtual GPU. if (factory->allow_virtual_devices_ && num_ep_devices < max_ep_devices) { OrtKeyValuePairs* hw_metadata = nullptr; factory->ort_api_.CreateKeyValuePairs(&hw_metadata); factory->ort_api_.AddKeyValuePair(hw_metadata, kOrtHardwareDevice_MetadataKey_IsVirtual, "1"); auto* status = factory->ep_api_.CreateHardwareDevice(OrtHardwareDeviceType::OrtHardwareDeviceType_GPU, factory->vendor_id_, /*device_id*/ 0, factory->vendor_.c_str(), hw_metadata, &factory->virtual_hw_device_); // ... OrtEpDevice* virtual_ep_device = nullptr; status = factory->ort_api_.GetEpApi()->CreateEpDevice(factory, factory->virtual_hw_device_, ep_metadata, ep_options, &virtual_ep_device); // ... ep_devices[num_ep_devices++] = virtual_ep_device; ``` ### Motivation and Context --- cmake/onnxruntime_unittests.cmake | 49 ++- .../core/session/onnxruntime_ep_c_api.h | 56 +++ .../onnxruntime_ep_device_ep_metadata_keys.h | 9 +- onnxruntime/core/session/environment.cc | 25 ++ onnxruntime/core/session/plugin_ep/ep_api.cc | 31 ++ onnxruntime/core/session/plugin_ep/ep_api.h | 7 + .../session/plugin_ep/ep_factory_internal.cc | 6 +- .../session/plugin_ep/ep_factory_internal.h | 4 + .../plugin_ep/ep_factory_internal_impl.h | 5 + .../plugin_ep/forward_to_factory_impl.h | 5 + .../library/{ => example_plugin_ep}/ep.cc | 0 .../library/{ => example_plugin_ep}/ep.h | 2 +- .../{ => example_plugin_ep}/ep_allocator.h | 2 +- .../{ => example_plugin_ep}/ep_arena.cc | 0 .../{ => example_plugin_ep}/ep_arena.h | 2 +- .../ep_data_transfer.cc | 0 .../ep_data_transfer.h | 2 +- .../{ => example_plugin_ep}/ep_factory.cc | 5 +- .../{ => example_plugin_ep}/ep_factory.h | 2 +- .../ep_stream_support.cc | 0 .../ep_stream_support.h | 2 +- .../example_plugin_ep.cc | 0 .../example_plugin_ep_library.def | 0 .../example_plugin_ep_library.lds | 0 .../autoep/library/example_plugin_ep_utils.cc | 48 --- .../library/example_plugin_ep_virt_gpu/ep.cc | 321 ++++++++++++++++++ .../library/example_plugin_ep_virt_gpu/ep.h | 62 ++++ .../example_plugin_ep_virt_gpu/ep_factory.cc | 214 ++++++++++++ .../example_plugin_ep_virt_gpu/ep_factory.h | 82 +++++ .../example_plugin_ep_virt_gpu/ep_lib.def | 5 + .../example_plugin_ep_virt_gpu/ep_lib.lds | 7 + .../ep_lib_entry.cc | 52 +++ ...le_plugin_ep_utils.h => plugin_ep_utils.h} | 44 ++- onnxruntime/test/autoep/test_allocators.cc | 2 +- onnxruntime/test/autoep/test_autoep_utils.cc | 36 +- onnxruntime/test/autoep/test_autoep_utils.h | 18 +- onnxruntime/test/autoep/test_data_transfer.cc | 2 +- onnxruntime/test/autoep/test_execution.cc | 38 ++- onnxruntime/test/autoep/test_registration.cc | 97 +++++- onnxruntime/test/autoep/test_selection.cc | 10 + 40 files changed, 1152 insertions(+), 100 deletions(-) rename onnxruntime/test/autoep/library/{ => example_plugin_ep}/ep.cc (100%) rename onnxruntime/test/autoep/library/{ => example_plugin_ep}/ep.h (98%) rename onnxruntime/test/autoep/library/{ => example_plugin_ep}/ep_allocator.h (99%) rename onnxruntime/test/autoep/library/{ => example_plugin_ep}/ep_arena.cc (100%) rename onnxruntime/test/autoep/library/{ => example_plugin_ep}/ep_arena.h (99%) rename onnxruntime/test/autoep/library/{ => example_plugin_ep}/ep_data_transfer.cc (100%) rename onnxruntime/test/autoep/library/{ => example_plugin_ep}/ep_data_transfer.h (97%) rename onnxruntime/test/autoep/library/{ => example_plugin_ep}/ep_factory.cc (98%) rename onnxruntime/test/autoep/library/{ => example_plugin_ep}/ep_factory.h (99%) rename onnxruntime/test/autoep/library/{ => example_plugin_ep}/ep_stream_support.cc (100%) rename onnxruntime/test/autoep/library/{ => example_plugin_ep}/ep_stream_support.h (98%) rename onnxruntime/test/autoep/library/{ => example_plugin_ep}/example_plugin_ep.cc (100%) rename onnxruntime/test/autoep/library/{ => example_plugin_ep}/example_plugin_ep_library.def (100%) rename onnxruntime/test/autoep/library/{ => example_plugin_ep}/example_plugin_ep_library.lds (100%) delete mode 100644 onnxruntime/test/autoep/library/example_plugin_ep_utils.cc create mode 100644 onnxruntime/test/autoep/library/example_plugin_ep_virt_gpu/ep.cc create mode 100644 onnxruntime/test/autoep/library/example_plugin_ep_virt_gpu/ep.h create mode 100644 onnxruntime/test/autoep/library/example_plugin_ep_virt_gpu/ep_factory.cc create mode 100644 onnxruntime/test/autoep/library/example_plugin_ep_virt_gpu/ep_factory.h create mode 100644 onnxruntime/test/autoep/library/example_plugin_ep_virt_gpu/ep_lib.def create mode 100644 onnxruntime/test/autoep/library/example_plugin_ep_virt_gpu/ep_lib.lds create mode 100644 onnxruntime/test/autoep/library/example_plugin_ep_virt_gpu/ep_lib_entry.cc rename onnxruntime/test/autoep/library/{example_plugin_ep_utils.h => plugin_ep_utils.h} (75%) diff --git a/cmake/onnxruntime_unittests.cmake b/cmake/onnxruntime_unittests.cmake index 460736ff8506e..57ad1e597a205 100644 --- a/cmake/onnxruntime_unittests.cmake +++ b/cmake/onnxruntime_unittests.cmake @@ -1982,9 +1982,13 @@ endif() if (WIN32 AND onnxruntime_BUILD_SHARED_LIB AND NOT CMAKE_SYSTEM_NAME STREQUAL "Emscripten" AND NOT onnxruntime_MINIMAL_BUILD) + + # # example_plugin_ep - file(GLOB onnxruntime_autoep_test_library_src "${TEST_SRC_DIR}/autoep/library/*.h" - "${TEST_SRC_DIR}/autoep/library/*.cc") + # + file(GLOB onnxruntime_autoep_test_library_src "${TEST_SRC_DIR}/autoep/library/example_plugin_ep/*.h" + "${TEST_SRC_DIR}/autoep/library/example_plugin_ep/*.cc" + "${TEST_SRC_DIR}/autoep/library/plugin_ep_utils.h") onnxruntime_add_shared_library_module(example_plugin_ep ${onnxruntime_autoep_test_library_src}) target_include_directories(example_plugin_ep PRIVATE ${REPO_ROOT}/include/onnxruntime/core/session) target_link_libraries(example_plugin_ep PRIVATE onnxruntime) @@ -1994,12 +1998,12 @@ if (WIN32 AND onnxruntime_BUILD_SHARED_LIB AND set(ONNXRUNTIME_AUTOEP_LIB_LINK_FLAG "-Xlinker -dead_strip") elseif (NOT CMAKE_SYSTEM_NAME MATCHES "AIX") string(CONCAT ONNXRUNTIME_AUTOEP_LIB_LINK_FLAG - "-Xlinker --version-script=${TEST_SRC_DIR}/autoep/library/example_plugin_ep_library.lds " + "-Xlinker --version-script=${TEST_SRC_DIR}/autoep/library/example_plugin_ep/example_plugin_ep_library.lds " "-Xlinker --no-undefined -Xlinker --gc-sections -z noexecstack") endif() else() set(ONNXRUNTIME_AUTOEP_LIB_LINK_FLAG - "-DEF:${TEST_SRC_DIR}/autoep/library/example_plugin_ep_library.def") + "-DEF:${TEST_SRC_DIR}/autoep/library/example_plugin_ep/example_plugin_ep_library.def") endif() set_property(TARGET example_plugin_ep APPEND_STRING PROPERTY LINK_FLAGS @@ -2008,7 +2012,42 @@ if (WIN32 AND onnxruntime_BUILD_SHARED_LIB AND set_target_properties(example_plugin_ep PROPERTIES FOLDER "ONNXRuntimeTest") source_group(TREE ${TEST_SRC_DIR} FILES ${onnxruntime_autoep_test_library_src}) + # + # example_plugin_ep_virt_gpu + # + set(onnxruntime_autoep_test_example_plugin_ep_virt_gpu_src + "${TEST_SRC_DIR}/autoep/library/plugin_ep_utils.h" + "${TEST_SRC_DIR}/autoep/library/example_plugin_ep_virt_gpu/ep_lib_entry.cc" + "${TEST_SRC_DIR}/autoep/library/example_plugin_ep_virt_gpu/ep_factory.h" + "${TEST_SRC_DIR}/autoep/library/example_plugin_ep_virt_gpu/ep_factory.cc" + "${TEST_SRC_DIR}/autoep/library/example_plugin_ep_virt_gpu/ep.h" + "${TEST_SRC_DIR}/autoep/library/example_plugin_ep_virt_gpu/ep.cc") + onnxruntime_add_shared_library_module(example_plugin_ep_virt_gpu ${onnxruntime_autoep_test_example_plugin_ep_virt_gpu_src}) + target_include_directories(example_plugin_ep_virt_gpu PRIVATE ${REPO_ROOT}/include/onnxruntime/core/session) + target_link_libraries(example_plugin_ep_virt_gpu PRIVATE onnxruntime) + + if(UNIX) + if (APPLE) + set(ONNXRUNTIME_AUTOEP_EP_LIB_VIRT_GPU_LINK_FLAG "-Xlinker -dead_strip") + elseif (NOT CMAKE_SYSTEM_NAME MATCHES "AIX") + string(CONCAT ONNXRUNTIME_AUTOEP_EP_LIB_VIRT_GPU_LINK_FLAG + "-Xlinker --version-script=${TEST_SRC_DIR}/autoep/library/example_plugin_ep_virt_gpu/ep_lib.lds " + "-Xlinker --no-undefined -Xlinker --gc-sections -z noexecstack") + endif() + else() + set(ONNXRUNTIME_AUTOEP_EP_LIB_VIRT_GPU_LINK_FLAG + "-DEF:${TEST_SRC_DIR}/autoep/library/example_plugin_ep_virt_gpu/ep_lib.def") + endif() + + set_property(TARGET example_plugin_ep_virt_gpu APPEND_STRING PROPERTY LINK_FLAGS + ${ONNXRUNTIME_AUTOEP_EP_LIB_VIRT_GPU_LINK_FLAG}) + + set_target_properties(example_plugin_ep_virt_gpu PROPERTIES FOLDER "ONNXRuntimeTest") + source_group(TREE ${TEST_SRC_DIR} FILES ${onnxruntime_autoep_test_example_plugin_ep_virt_gpu_src}) + + # # test library + # file(GLOB onnxruntime_autoep_test_SRC "${ONNXRUNTIME_AUTOEP_TEST_SRC_DIR}/*.h" "${ONNXRUNTIME_AUTOEP_TEST_SRC_DIR}/*.cc") @@ -2041,7 +2080,7 @@ if (WIN32 AND onnxruntime_BUILD_SHARED_LIB AND TARGET onnxruntime_autoep_test SOURCES ${onnxruntime_autoep_test_SRC} ${onnxruntime_unittest_main_src} LIBS ${onnxruntime_autoep_test_LIBS} - DEPENDS ${all_dependencies} example_plugin_ep + DEPENDS ${all_dependencies} example_plugin_ep example_plugin_ep_virt_gpu ) endif() diff --git a/include/onnxruntime/core/session/onnxruntime_ep_c_api.h b/include/onnxruntime/core/session/onnxruntime_ep_c_api.h index 975f6b453a88d..a8e94d690177f 100644 --- a/include/onnxruntime/core/session/onnxruntime_ep_c_api.h +++ b/include/onnxruntime/core/session/onnxruntime_ep_c_api.h @@ -465,6 +465,33 @@ struct OrtEpApi { */ ORT_API_T(uint64_t, GetSyncIdForLastWaitOnSyncStream, _In_ const OrtSyncStream* producer_stream, _In_ const OrtSyncStream* consumer_stream); + + /** \brief Create an OrtHardwareDevice. + * + * \note Called within OrtEpFactory::GetSupportedDevices to create a new hardware device (e.g., virtual). + * + * \param[in] type The hardware device type. + * \param[in] vendor_id The hardware device's vendor identifier. + * \param[in] device_id The hardware device's identifier. + * \param[in] vendor_name The hardware device's vendor name as a null-terminated string. Copied by ORT. + * \param[in] metadata Optional OrtKeyValuePairs instance for hardware device metadata that may be queried by + * applications via OrtApi::GetEpDevices(). + * Refer to onnxruntime_ep_device_ep_metadata_keys.h for common OrtHardwareDevice metadata keys. + * \param[out] hardware_device Output parameter set to the new OrtHardwareDevice instance that is created. + * Must be release with ReleaseHardwareDevice(). + * + * \snippet{doc} snippets.dox OrtStatus Return Value + * + * \since Version 1.24. + */ + ORT_API2_STATUS(CreateHardwareDevice, _In_ OrtHardwareDeviceType type, + _In_ uint32_t vendor_id, + _In_ uint32_t device_id, + _In_ const char* vendor_name, + _In_opt_ const OrtKeyValuePairs* metadata, + _Out_ OrtHardwareDevice** hardware_device); + + ORT_CLASS_RELEASE(HardwareDevice); }; /** @@ -981,6 +1008,35 @@ struct OrtEpFactory { _In_ const OrtMemoryDevice* memory_device, _In_opt_ const OrtKeyValuePairs* stream_options, _Outptr_ OrtSyncStreamImpl** stream); + + /** \brief Set environment options on this EP factory. + * + * Environment options can be set by ORT after calling the library's 'CreateEpFactories' function to + * create EP factories. + * + * Supported options: + * "allow_virtual_devices": Allows EP factory to specify OrtEpDevice instances that use custom + * virtual OrtHardwareDevices, which can be created via OrtEpApi::CreateHardwareDevice(). + * + * A virtual OrtHardwareDevice does not represent actual hardware on the device, and is identified + * via the metadata entry "is_virtual" with a value of "1". + * Refer to onnxruntime_ep_device_ep_metadata_keys.h for well-known OrtHardwareDevice metadata keys. + * + * Allowed values: + * -# "0": Default. Creation of virtual devices is not allowed. + * -# "1": Creation of virtual devices is allowed. + * + * \param[in] this_ptr The OrtEpFactory instance. + * \param[in] options The configuration options. + * + * \note Implementation of this function is optional. + * An EP factory should only implement this if it needs to handle any environment options. + * + * \snippet{doc} snippets.dox OrtStatus Return Value + * + * \since Version 1.24. + */ + ORT_API2_STATUS(SetEnvironmentOptions, _In_ OrtEpFactory* this_ptr, _In_ const OrtKeyValuePairs* options); }; #ifdef __cplusplus diff --git a/include/onnxruntime/core/session/onnxruntime_ep_device_ep_metadata_keys.h b/include/onnxruntime/core/session/onnxruntime_ep_device_ep_metadata_keys.h index bbd6a43bb7a41..f6afd84dabc5e 100644 --- a/include/onnxruntime/core/session/onnxruntime_ep_device_ep_metadata_keys.h +++ b/include/onnxruntime/core/session/onnxruntime_ep_device_ep_metadata_keys.h @@ -3,7 +3,7 @@ #pragma once -// This file contains well-known keys for OrtEpDevice EP metadata entries. +// This file contains well-known keys for OrtEpDevice and OrtHardwareDevice metadata entries. // It does NOT specify all available metadata keys. // Key for the execution provider version string. This should be available for all plugin EPs. @@ -16,3 +16,10 @@ static const char* const kOrtModelMetadata_EpCompatibilityInfoPrefix = "ep_compa // Key for the execution provider library path (for dynamically loaded EPs) static const char* const kOrtEpDevice_EpMetadataKey_LibraryPath = "library_path"; + +// Optional metadata key to determine if a OrtHardwareDevice represents a virtual (non-hardware) device. +// Possible values: +// - "0": OrtHardwareDevice is not virtual (i.e., actual hardware device). This is the assumed default value +// if this metadata key is not present. +// - "1": OrtHardwareDevice is virtual. +static const char* const kOrtHardwareDevice_MetadataKey_IsVirtual = "is_virtual"; diff --git a/onnxruntime/core/session/environment.cc b/onnxruntime/core/session/environment.cc index 9c40eb75780ee..cde77eeed8aa5 100644 --- a/onnxruntime/core/session/environment.cc +++ b/onnxruntime/core/session/environment.cc @@ -746,6 +746,29 @@ std::vector SortDevicesByType() { return sorted_devices; } + +bool AreVirtualDevicesAllowed(std::string_view lib_registration_name) { + constexpr std::string_view suffix{".virtual"}; + + return lib_registration_name.size() >= suffix.size() && + lib_registration_name.compare(lib_registration_name.size() - suffix.size(), + suffix.size(), suffix) == 0; +} + +Status SetEpFactoryEnvironmentOptions(OrtEpFactory& factory, std::string_view lib_registration_name) { + // OrtEpFactory::SetEnvironmentOptions was added in ORT 1.24 + if (factory.ort_version_supported < 24 || factory.SetEnvironmentOptions == nullptr) { + return Status::OK(); + } + + // We only set one option now but this can be generalized if necessary. + OrtKeyValuePairs options; + options.Add("allow_virtual_devices", AreVirtualDevicesAllowed(lib_registration_name) ? "1" : "0"); + + ORT_RETURN_IF_ERROR(ToStatusAndRelease(factory.SetEnvironmentOptions(&factory, &options))); + + return Status::OK(); +} } // namespace Status Environment::EpInfo::Create(std::unique_ptr library_in, std::unique_ptr& out, @@ -772,6 +795,8 @@ Status Environment::EpInfo::Create(std::unique_ptr library_in, std::u auto& factory = *factory_ptr; + ORT_RETURN_IF_ERROR(SetEpFactoryEnvironmentOptions(factory, instance.library->RegistrationName())); + std::array ep_devices{nullptr}; size_t num_ep_devices = 0; ORT_RETURN_IF_ERROR(ToStatusAndRelease( diff --git a/onnxruntime/core/session/plugin_ep/ep_api.cc b/onnxruntime/core/session/plugin_ep/ep_api.cc index 366f96e585918..7efb0a68c735d 100644 --- a/onnxruntime/core/session/plugin_ep/ep_api.cc +++ b/onnxruntime/core/session/plugin_ep/ep_api.cc @@ -4,6 +4,8 @@ #include "core/session/plugin_ep/ep_api.h" #include +#include +#include #include #include "core/common/semver.h" @@ -205,6 +207,32 @@ ORT_API(uint64_t, GetSyncIdForLastWaitOnSyncStream, _In_ const OrtSyncStream* pr return id; } +ORT_API_STATUS_IMPL(CreateHardwareDevice, _In_ OrtHardwareDeviceType type, + _In_ uint32_t vendor_id, + _In_ uint32_t device_id, + _In_ const char* vendor_name, + _In_opt_ const OrtKeyValuePairs* metadata, + _Out_ OrtHardwareDevice** hardware_device) { + API_IMPL_BEGIN + auto device = std::make_unique(); + device->type = type; + device->vendor_id = vendor_id; + device->device_id = device_id; + device->vendor = std::string(vendor_name); + + if (metadata) { + device->metadata = *metadata; + } + + *hardware_device = device.release(); + return nullptr; + API_IMPL_END +} + +ORT_API(void, ReleaseHardwareDevice, _Frees_ptr_opt_ OrtHardwareDevice* device) { + delete device; +} + static constexpr OrtEpApi ort_ep_api = { // NOTE: ABI compatibility depends on the order within this struct so all additions must be at the end, // and no functions can be removed (the implementation needs to change to return an error). @@ -231,6 +259,9 @@ static constexpr OrtEpApi ort_ep_api = { &OrtExecutionProviderApi::SyncStream_GetSyncId, &OrtExecutionProviderApi::GetSyncIdForLastWaitOnSyncStream, // End of Version 23 - DO NOT MODIFY ABOVE + + &OrtExecutionProviderApi::CreateHardwareDevice, + &OrtExecutionProviderApi::ReleaseHardwareDevice, }; // checks that we don't violate the rule that the functions must remain in the slots they were originally assigned diff --git a/onnxruntime/core/session/plugin_ep/ep_api.h b/onnxruntime/core/session/plugin_ep/ep_api.h index c0dc79f3fb333..129230be4f618 100644 --- a/onnxruntime/core/session/plugin_ep/ep_api.h +++ b/onnxruntime/core/session/plugin_ep/ep_api.h @@ -40,4 +40,11 @@ ORT_API(const OrtSyncStreamImpl*, SyncStream_GetImpl, _In_ const OrtSyncStream* ORT_API(uint64_t, SyncStream_GetSyncId, _In_ const OrtSyncStream* stream); ORT_API(uint64_t, GetSyncIdForLastWaitOnSyncStream, _In_ const OrtSyncStream* producer_stream, _In_ const OrtSyncStream* consumer_stream); +ORT_API_STATUS_IMPL(CreateHardwareDevice, _In_ OrtHardwareDeviceType type, + _In_ uint32_t vendor_id, + _In_ uint32_t device_id, + _In_ const char* vendor_name, + _In_opt_ const OrtKeyValuePairs* metadata, + _Out_ OrtHardwareDevice** hardware_device); +ORT_API(void, ReleaseHardwareDevice, _Frees_ptr_opt_ OrtHardwareDevice* device); } // namespace OrtExecutionProviderApi diff --git a/onnxruntime/core/session/plugin_ep/ep_factory_internal.cc b/onnxruntime/core/session/plugin_ep/ep_factory_internal.cc index f3e30caf07e81..364bab471ddbe 100644 --- a/onnxruntime/core/session/plugin_ep/ep_factory_internal.cc +++ b/onnxruntime/core/session/plugin_ep/ep_factory_internal.cc @@ -3,6 +3,8 @@ #include "core/session/plugin_ep/ep_factory_internal.h" +#include + #include "core/framework/error_code_helper.h" #include "core/session/abi_devices.h" #include "core/session/abi_session_options_impl.h" @@ -13,7 +15,8 @@ namespace onnxruntime { using Forward = ForwardToFactoryImpl; EpFactoryInternal::EpFactoryInternal(std::unique_ptr impl) - : impl_{std::move(impl)} { + : OrtEpFactory{}, // Ensure optional functions are default initialized to nullptr + impl_{std::move(impl)} { ort_version_supported = ORT_API_VERSION; OrtEpFactory::GetName = Forward::GetFactoryName; @@ -29,6 +32,7 @@ EpFactoryInternal::EpFactoryInternal(std::unique_ptr impl OrtEpFactory::CreateDataTransfer = Forward::CreateDataTransfer; OrtEpFactory::IsStreamAware = Forward::IsStreamAware; OrtEpFactory::CreateSyncStreamForDevice = Forward::CreateSyncStreamForDevice; + OrtEpFactory::SetEnvironmentOptions = Forward::SetEnvironmentOptions; } InternalExecutionProviderFactory::InternalExecutionProviderFactory(EpFactoryInternal& ep_factory, diff --git a/onnxruntime/core/session/plugin_ep/ep_factory_internal.h b/onnxruntime/core/session/plugin_ep/ep_factory_internal.h index 093bfce462d32..6eb83a117fb63 100644 --- a/onnxruntime/core/session/plugin_ep/ep_factory_internal.h +++ b/onnxruntime/core/session/plugin_ep/ep_factory_internal.h @@ -87,6 +87,10 @@ class EpFactoryInternal : public OrtEpFactory { return impl_->ValidateCompiledModelCompatibilityInfo(devices, num_devices, compatibility_info, model_compatibility); } + OrtStatus* SetEnvironmentOptions(_In_ const OrtKeyValuePairs* options) noexcept { + return impl_->SetEnvironmentOptions(options); + } + // Function ORT calls to release an EP instance. void ReleaseEp(OrtEp* /*ep*/) noexcept { // we never create an OrtEp so we should never be trying to release one diff --git a/onnxruntime/core/session/plugin_ep/ep_factory_internal_impl.h b/onnxruntime/core/session/plugin_ep/ep_factory_internal_impl.h index f29154d19c53c..de9e2d44431bf 100644 --- a/onnxruntime/core/session/plugin_ep/ep_factory_internal_impl.h +++ b/onnxruntime/core/session/plugin_ep/ep_factory_internal_impl.h @@ -83,6 +83,11 @@ class EpFactoryInternalImpl { "CreateSyncStreamForDevice is not implemented for this EP factory."); } + virtual OrtStatus* SetEnvironmentOptions(const OrtKeyValuePairs* /*options*/) noexcept { + // Default implementation does not handle any options. + return nullptr; + } + // Function ORT calls to release an EP instance. void ReleaseEp(OrtEp* ep); diff --git a/onnxruntime/core/session/plugin_ep/forward_to_factory_impl.h b/onnxruntime/core/session/plugin_ep/forward_to_factory_impl.h index 2cceb1d08d536..65c396181f0a7 100644 --- a/onnxruntime/core/session/plugin_ep/forward_to_factory_impl.h +++ b/onnxruntime/core/session/plugin_ep/forward_to_factory_impl.h @@ -82,6 +82,11 @@ struct ForwardToFactoryImpl { return static_cast(this_ptr)->CreateSyncStreamForDevice(memory_device, stream_options, stream); } + static OrtStatus* ORT_API_CALL SetEnvironmentOptions(_In_ OrtEpFactory* this_ptr, + _In_ const OrtKeyValuePairs* options) noexcept { + return static_cast(this_ptr)->SetEnvironmentOptions(options); + } + static void ORT_API_CALL ReleaseEp(OrtEpFactory* this_ptr, OrtEp* ep) noexcept { static_cast(this_ptr)->ReleaseEp(ep); } diff --git a/onnxruntime/test/autoep/library/ep.cc b/onnxruntime/test/autoep/library/example_plugin_ep/ep.cc similarity index 100% rename from onnxruntime/test/autoep/library/ep.cc rename to onnxruntime/test/autoep/library/example_plugin_ep/ep.cc diff --git a/onnxruntime/test/autoep/library/ep.h b/onnxruntime/test/autoep/library/example_plugin_ep/ep.h similarity index 98% rename from onnxruntime/test/autoep/library/ep.h rename to onnxruntime/test/autoep/library/example_plugin_ep/ep.h index 279925a7ec3e1..7e96a523cf285 100644 --- a/onnxruntime/test/autoep/library/ep.h +++ b/onnxruntime/test/autoep/library/example_plugin_ep/ep.h @@ -5,7 +5,7 @@ #include -#include "example_plugin_ep_utils.h" +#include "../plugin_ep_utils.h" class ExampleEpFactory; struct MulKernel; diff --git a/onnxruntime/test/autoep/library/ep_allocator.h b/onnxruntime/test/autoep/library/example_plugin_ep/ep_allocator.h similarity index 99% rename from onnxruntime/test/autoep/library/ep_allocator.h rename to onnxruntime/test/autoep/library/example_plugin_ep/ep_allocator.h index e46c03dfc8f14..febf8c7dbd8c1 100644 --- a/onnxruntime/test/autoep/library/ep_allocator.h +++ b/onnxruntime/test/autoep/library/example_plugin_ep/ep_allocator.h @@ -3,7 +3,7 @@ #pragma once -#include "example_plugin_ep_utils.h" +#include "../plugin_ep_utils.h" #include diff --git a/onnxruntime/test/autoep/library/ep_arena.cc b/onnxruntime/test/autoep/library/example_plugin_ep/ep_arena.cc similarity index 100% rename from onnxruntime/test/autoep/library/ep_arena.cc rename to onnxruntime/test/autoep/library/example_plugin_ep/ep_arena.cc diff --git a/onnxruntime/test/autoep/library/ep_arena.h b/onnxruntime/test/autoep/library/example_plugin_ep/ep_arena.h similarity index 99% rename from onnxruntime/test/autoep/library/ep_arena.h rename to onnxruntime/test/autoep/library/example_plugin_ep/ep_arena.h index caa2c61db835f..c8fd1db5dc007 100644 --- a/onnxruntime/test/autoep/library/ep_arena.h +++ b/onnxruntime/test/autoep/library/example_plugin_ep/ep_arena.h @@ -26,7 +26,7 @@ limitations under the License. #undef ORT_API_MANUAL_INIT #include "ep_allocator.h" -#include "example_plugin_ep_utils.h" +#include "../plugin_ep_utils.h" #if defined(PLATFORM_WINDOWS) #include diff --git a/onnxruntime/test/autoep/library/ep_data_transfer.cc b/onnxruntime/test/autoep/library/example_plugin_ep/ep_data_transfer.cc similarity index 100% rename from onnxruntime/test/autoep/library/ep_data_transfer.cc rename to onnxruntime/test/autoep/library/example_plugin_ep/ep_data_transfer.cc diff --git a/onnxruntime/test/autoep/library/ep_data_transfer.h b/onnxruntime/test/autoep/library/example_plugin_ep/ep_data_transfer.h similarity index 97% rename from onnxruntime/test/autoep/library/ep_data_transfer.h rename to onnxruntime/test/autoep/library/example_plugin_ep/ep_data_transfer.h index da74d42b4affe..f1dad784ff84b 100644 --- a/onnxruntime/test/autoep/library/ep_data_transfer.h +++ b/onnxruntime/test/autoep/library/example_plugin_ep/ep_data_transfer.h @@ -3,7 +3,7 @@ #pragma once -#include "example_plugin_ep_utils.h" +#include "../plugin_ep_utils.h" struct ExampleDataTransfer : OrtDataTransferImpl, ApiPtrs { ExampleDataTransfer(ApiPtrs api_ptrs, diff --git a/onnxruntime/test/autoep/library/ep_factory.cc b/onnxruntime/test/autoep/library/example_plugin_ep/ep_factory.cc similarity index 98% rename from onnxruntime/test/autoep/library/ep_factory.cc rename to onnxruntime/test/autoep/library/example_plugin_ep/ep_factory.cc index 4da7d722a5e0b..a2a4848ed060f 100644 --- a/onnxruntime/test/autoep/library/ep_factory.cc +++ b/onnxruntime/test/autoep/library/example_plugin_ep/ep_factory.cc @@ -12,7 +12,7 @@ #include "ep_stream_support.h" ExampleEpFactory::ExampleEpFactory(const char* ep_name, ApiPtrs apis, const OrtLogger& default_logger) - : ApiPtrs(apis), default_logger_{default_logger}, ep_name_{ep_name} { + : OrtEpFactory{}, ApiPtrs(apis), default_logger_{default_logger}, ep_name_{ep_name} { ort_version_supported = ORT_API_VERSION; // set to the ORT version we were compiled with. GetName = GetNameImpl; GetVendor = GetVendorImpl; @@ -190,8 +190,7 @@ OrtStatus* ORT_API_CALL ExampleEpFactory::CreateEpImpl(OrtEpFactory* this_ptr, // Create EP configuration from session options, if needed. // Note: should not store a direct reference to the session options object as its lifespan is not guaranteed. std::string ep_context_enable; - RETURN_IF_ERROR(GetSessionConfigEntryOrDefault(factory->ort_api, *session_options, - "ep.context_enable", "0", ep_context_enable)); + RETURN_IF_ERROR(GetSessionConfigEntryOrDefault(*session_options, "ep.context_enable", "0", ep_context_enable)); ExampleEp::Config config = {}; config.enable_ep_context = ep_context_enable == "1"; diff --git a/onnxruntime/test/autoep/library/ep_factory.h b/onnxruntime/test/autoep/library/example_plugin_ep/ep_factory.h similarity index 99% rename from onnxruntime/test/autoep/library/ep_factory.h rename to onnxruntime/test/autoep/library/example_plugin_ep/ep_factory.h index 088deda1fe9d2..6f6aaf2aaa9fc 100644 --- a/onnxruntime/test/autoep/library/ep_factory.h +++ b/onnxruntime/test/autoep/library/example_plugin_ep/ep_factory.h @@ -7,7 +7,7 @@ #include "ep_arena.h" #include "ep_data_transfer.h" -#include "example_plugin_ep_utils.h" +#include "../plugin_ep_utils.h" /// /// Example EP factory that can create an OrtEp and return information about the supported hardware devices. diff --git a/onnxruntime/test/autoep/library/ep_stream_support.cc b/onnxruntime/test/autoep/library/example_plugin_ep/ep_stream_support.cc similarity index 100% rename from onnxruntime/test/autoep/library/ep_stream_support.cc rename to onnxruntime/test/autoep/library/example_plugin_ep/ep_stream_support.cc diff --git a/onnxruntime/test/autoep/library/ep_stream_support.h b/onnxruntime/test/autoep/library/example_plugin_ep/ep_stream_support.h similarity index 98% rename from onnxruntime/test/autoep/library/ep_stream_support.h rename to onnxruntime/test/autoep/library/example_plugin_ep/ep_stream_support.h index a825e5afd2250..847ed708c5ca7 100644 --- a/onnxruntime/test/autoep/library/ep_stream_support.h +++ b/onnxruntime/test/autoep/library/example_plugin_ep/ep_stream_support.h @@ -5,7 +5,7 @@ #include "onnxruntime_c_api.h" #include "ep_factory.h" -#include "example_plugin_ep_utils.h" +#include "../plugin_ep_utils.h" class ExampleEpFactory; diff --git a/onnxruntime/test/autoep/library/example_plugin_ep.cc b/onnxruntime/test/autoep/library/example_plugin_ep/example_plugin_ep.cc similarity index 100% rename from onnxruntime/test/autoep/library/example_plugin_ep.cc rename to onnxruntime/test/autoep/library/example_plugin_ep/example_plugin_ep.cc diff --git a/onnxruntime/test/autoep/library/example_plugin_ep_library.def b/onnxruntime/test/autoep/library/example_plugin_ep/example_plugin_ep_library.def similarity index 100% rename from onnxruntime/test/autoep/library/example_plugin_ep_library.def rename to onnxruntime/test/autoep/library/example_plugin_ep/example_plugin_ep_library.def diff --git a/onnxruntime/test/autoep/library/example_plugin_ep_library.lds b/onnxruntime/test/autoep/library/example_plugin_ep/example_plugin_ep_library.lds similarity index 100% rename from onnxruntime/test/autoep/library/example_plugin_ep_library.lds rename to onnxruntime/test/autoep/library/example_plugin_ep/example_plugin_ep_library.lds diff --git a/onnxruntime/test/autoep/library/example_plugin_ep_utils.cc b/onnxruntime/test/autoep/library/example_plugin_ep_utils.cc deleted file mode 100644 index 8b36f5f4e9a13..0000000000000 --- a/onnxruntime/test/autoep/library/example_plugin_ep_utils.cc +++ /dev/null @@ -1,48 +0,0 @@ -// Copyright (c) Microsoft Corporation. All rights reserved. -// Licensed under the MIT License. - -#include "example_plugin_ep_utils.h" - -#include - -OrtStatus* GetSessionConfigEntryOrDefault(const OrtApi& /* ort_api */, const OrtSessionOptions& session_options, - const char* config_key, const std::string& default_val, - /*out*/ std::string& config_val) { - try { - Ort::ConstSessionOptions sess_opt{&session_options}; - config_val = sess_opt.GetConfigEntryOrDefault(config_key, default_val); - } catch (const Ort::Exception& ex) { - Ort::Status status(ex); - return status.release(); - } - - return nullptr; -} - -void IsFloatTensor(Ort::ConstValueInfo value_info, bool& result) { - result = false; - - auto type_info = value_info.TypeInfo(); - ONNXType onnx_type = type_info.GetONNXType(); - if (onnx_type != ONNX_TYPE_TENSOR) { - return; - } - - auto type_shape = type_info.GetTensorTypeAndShapeInfo(); - ONNXTensorElementDataType elem_type = type_shape.GetElementType(); - if (elem_type != ONNX_TENSOR_ELEMENT_DATA_TYPE_FLOAT) { - return; - } - result = true; -} - -std::optional> GetTensorShape(Ort::ConstValueInfo value_info) { - const auto type_info = value_info.TypeInfo(); - const auto onnx_type = type_info.GetONNXType(); - if (onnx_type != ONNX_TYPE_TENSOR) { - return std::nullopt; - } - - const auto type_shape = type_info.GetTensorTypeAndShapeInfo(); - return type_shape.GetShape(); -} diff --git a/onnxruntime/test/autoep/library/example_plugin_ep_virt_gpu/ep.cc b/onnxruntime/test/autoep/library/example_plugin_ep_virt_gpu/ep.cc new file mode 100644 index 0000000000000..99a580f5577f7 --- /dev/null +++ b/onnxruntime/test/autoep/library/example_plugin_ep_virt_gpu/ep.cc @@ -0,0 +1,321 @@ +// Copyright (c) Microsoft Corporation. All rights reserved. +// Licensed under the MIT License. + +#include "ep.h" + +#include +#include +#include +#include +#include +#include +#include + +#include "ep_factory.h" +#include "../plugin_ep_utils.h" + +/// +/// Empty (not implemented) computation functor for a compiled Add. +/// This EP only supports a virtual GPU device that cannot run inference, but can create a compiled model. +/// +struct VirtualCompiledAdd { + VirtualCompiledAdd(const OrtApi& ort_api, const OrtLogger& logger) : ort_api(ort_api), logger(logger) {} + + OrtStatus* Compute(OrtKernelContext* /*kernel_ctx*/) { + RETURN_IF_ERROR(ort_api.Logger_LogMessage(&logger, + OrtLoggingLevel::ORT_LOGGING_LEVEL_INFO, + "VirtualCompiledAdd::Compute", ORT_FILE, __LINE__, __FUNCTION__)); + return ort_api.CreateStatus(ORT_NOT_IMPLEMENTED, "EP only supports a virtual GPU that cannot run ops."); + } + + const OrtApi& ort_api; + const OrtLogger& logger; +}; + +/// +/// Example OrtNodeComputeInfo that represents the computation function for a compiled OrtGraph. +/// +struct AddNodeComputeInfo : OrtNodeComputeInfo { + explicit AddNodeComputeInfo(EpVirtualGpu& ep); + + static OrtStatus* ORT_API_CALL CreateStateImpl(OrtNodeComputeInfo* this_ptr, + OrtNodeComputeContext* compute_context, + void** compute_state); + static OrtStatus* ORT_API_CALL ComputeImpl(OrtNodeComputeInfo* this_ptr, void* compute_state, + OrtKernelContext* kernel_context); + static void ORT_API_CALL ReleaseStateImpl(OrtNodeComputeInfo* this_ptr, void* compute_state); + + EpVirtualGpu& ep; +}; + +EpVirtualGpu::EpVirtualGpu(EpFactoryVirtualGpu& factory, const EpVirtualGpu::Config& config, const OrtLogger& logger) + : OrtEp{}, // explicitly call the struct ctor to ensure all optional values are default initialized + factory_{factory}, + config_{config}, + ort_api_{factory.GetOrtApi()}, + ep_api_{factory.GetEpApi()}, + model_editor_api_{factory.GetModelEditorApi()}, + name_{factory.GetEpName()}, + logger_{logger} { + ort_version_supported = ORT_API_VERSION; // set to the ORT version we were compiled with. + + // Initialize the execution provider's function table + GetName = GetNameImpl; + GetCapability = GetCapabilityImpl; + Compile = CompileImpl; + ReleaseNodeComputeInfos = ReleaseNodeComputeInfosImpl; + + auto status = ort_api_.Logger_LogMessage(&logger_, + OrtLoggingLevel::ORT_LOGGING_LEVEL_INFO, + ("EpVirtualGpu has been created with name " + name_).c_str(), + ORT_FILE, __LINE__, __FUNCTION__); + // ignore status for now + (void)status; +} + +EpVirtualGpu::~EpVirtualGpu() = default; + +/*static*/ +const char* ORT_API_CALL EpVirtualGpu ::GetNameImpl(const OrtEp* this_ptr) noexcept { + const auto* ep = static_cast(this_ptr); + return ep->name_.c_str(); +} + +/*static*/ +OrtStatus* ORT_API_CALL EpVirtualGpu::GetCapabilityImpl(OrtEp* this_ptr, const OrtGraph* ort_graph, + OrtEpGraphSupportInfo* graph_support_info) noexcept { + try { + EpVirtualGpu* ep = static_cast(this_ptr); + + Ort::ConstGraph graph{ort_graph}; + std::vector nodes = graph.GetNodes(); + + if (nodes.empty()) { + return nullptr; // No nodes to process + } + + std::vector supported_nodes; + + for (const auto& node : nodes) { + auto op_type = node.GetOperatorType(); + + if (op_type == "Add") { + supported_nodes.push_back(node); // Only support a single Add for now. + break; + } + } + + if (supported_nodes.empty()) { + return nullptr; + } + + // Create (optional) fusion options for the supported nodes to fuse. + OrtNodeFusionOptions node_fusion_options = {}; + node_fusion_options.ort_version_supported = ORT_API_VERSION; + node_fusion_options.drop_constant_initializers = false; + + RETURN_IF_ERROR(ep->ep_api_.EpGraphSupportInfo_AddNodesToFuse(graph_support_info, + reinterpret_cast(supported_nodes.data()), + supported_nodes.size(), + &node_fusion_options)); + } catch (const Ort::Exception& ex) { + Ort::Status status(ex); + return status.release(); + } catch (const std::exception& ex) { + Ort::Status status(ex.what(), ORT_EP_FAIL); + return status.release(); + } + + return nullptr; +} + +/*static*/ +OrtStatus* ORT_API_CALL EpVirtualGpu::CompileImpl(_In_ OrtEp* this_ptr, _In_ const OrtGraph** ort_graphs, + _In_ const OrtNode** fused_nodes, _In_ size_t count, + _Out_writes_all_(count) OrtNodeComputeInfo** node_compute_infos, + _Out_writes_(count) OrtNode** ep_context_nodes) noexcept { + try { + if (count != 1) { + Ort::Status status("Expected to compile a single graph", ORT_EP_FAIL); + return status.release(); + } + + EpVirtualGpu* ep = static_cast(this_ptr); + + Ort::ConstGraph graph{ort_graphs[0]}; + + std::vector nodes = graph.GetNodes(); + if (nodes.size() != 1) { + Ort::Status status("Expected to compile a single Add node", ORT_EP_FAIL); + return status.release(); + } + + auto node_op_type = nodes[0].GetOperatorType(); + if (node_op_type != "Add") { + Ort::Status status("Expected to compile a single Add node", ORT_EP_FAIL); + return status.release(); + } + + // Now we know we're compiling a single Add node. Create a computation kernel. + Ort::ConstNode fused_node{fused_nodes[0]}; + auto ep_name = fused_node.GetEpName(); + if (ep_name != ep->name_) { + Ort::Status status("The fused node is expected to assigned to this EP to run on", ORT_EP_FAIL); + return status.release(); + } + + // Associate the name of the fused node with our VirtualCompiledAdd. + auto fused_node_name = fused_node.GetName(); + ep->compiled_subgraphs_.emplace(std::move(fused_node_name), + std::make_unique(ep->ort_api_, ep->logger_)); + + // Update the OrtNodeComputeInfo associated with the graph. + auto node_compute_info = std::make_unique(*ep); + node_compute_infos[0] = node_compute_info.release(); + + // Create EpContext nodes for the fused nodes we compiled (if enabled by user via session options). + if (ep->config_.enable_ep_context) { + assert(ep_context_nodes != nullptr); + RETURN_IF_ERROR(ep->CreateEpContextNodes(gsl::span(fused_nodes, count), + gsl::span(ep_context_nodes, count))); + } + } catch (const Ort::Exception& ex) { + Ort::Status status(ex); + return status.release(); + } catch (const std::exception& ex) { + Ort::Status status(ex.what(), ORT_EP_FAIL); + return status.release(); + } + + return nullptr; +} + +// Creates EPContext nodes from the given fused nodes. +// This is an example implementation that can be used to generate an EPContext model. However, this example EP +// cannot currently run the EPContext model. +OrtStatus* EpVirtualGpu::CreateEpContextNodes(gsl::span fused_nodes, + /*out*/ gsl::span ep_context_nodes) { + try { + assert(fused_nodes.size() == ep_context_nodes.size()); + + // Helper to collect input or output names from an array of OrtValueInfo instances. + auto collect_input_output_names = [&](gsl::span value_infos, + std::vector& result) { + std::vector value_names; + value_names.reserve(value_infos.size()); + + for (const auto vi : value_infos) { + value_names.push_back(vi.GetName()); + } + + result = std::move(value_names); + }; + + // Create an "EPContext" node for every fused node. + for (size_t i = 0; i < fused_nodes.size(); ++i) { + Ort::ConstNode fused_node{fused_nodes[i]}; + auto fused_node_name = fused_node.GetName(); + + std::vector fused_node_inputs = fused_node.GetInputs(); + std::vector fused_node_outputs = fused_node.GetOutputs(); + + std::vector input_names; + std::vector output_names; + + collect_input_output_names(fused_node_inputs, /*out*/ input_names); + collect_input_output_names(fused_node_outputs, /*out*/ output_names); + + int64_t is_main_context = (i == 0); + int64_t embed_mode = 1; + + // Create node attributes. The CreateNode() function copies the attributes. + std::array attributes = {}; + std::string ep_ctx = "binary_data"; + attributes[0] = Ort::OpAttr("ep_cache_context", ep_ctx.data(), static_cast(ep_ctx.size()), + ORT_OP_ATTR_STRING); + + attributes[1] = Ort::OpAttr("main_context", &is_main_context, 1, ORT_OP_ATTR_INT); + attributes[2] = Ort::OpAttr("embed_mode", &embed_mode, 1, ORT_OP_ATTR_INT); + attributes[3] = Ort::OpAttr("ep_sdk_version", "1", 1, ORT_OP_ATTR_STRING); + attributes[4] = Ort::OpAttr("partition_name", fused_node_name.data(), static_cast(fused_node_name.size()), + ORT_OP_ATTR_STRING); + + attributes[5] = Ort::OpAttr("source", this->name_.data(), static_cast(this->name_.size()), + ORT_OP_ATTR_STRING); + + std::vector c_input_names; + std::transform(input_names.begin(), input_names.end(), std::back_inserter(c_input_names), + [](const std::string& s) { return s.c_str(); }); + std::vector c_output_names; + std::transform(output_names.begin(), output_names.end(), std::back_inserter(c_output_names), + [](const std::string& s) { return s.c_str(); }); + + OrtOpAttr** op_attrs = reinterpret_cast(attributes.data()); + RETURN_IF_ERROR(model_editor_api_.CreateNode("EPContext", "com.microsoft", fused_node_name.c_str(), + c_input_names.data(), c_input_names.size(), + c_output_names.data(), c_output_names.size(), + op_attrs, attributes.size(), + &ep_context_nodes[i])); + } + } catch (const Ort::Exception& ex) { + Ort::Status status(ex); + return status.release(); + } catch (const std::exception& ex) { + Ort::Status status(ex.what(), ORT_EP_FAIL); + return status.release(); + } + + return nullptr; +} + +/*static*/ +void ORT_API_CALL EpVirtualGpu::ReleaseNodeComputeInfosImpl(OrtEp* this_ptr, + OrtNodeComputeInfo** node_compute_infos, + size_t num_node_compute_infos) noexcept { + (void)this_ptr; + for (size_t i = 0; i < num_node_compute_infos; i++) { + delete node_compute_infos[i]; + } +} + +// +// Implementation of AddNodeComputeInfo +// +AddNodeComputeInfo::AddNodeComputeInfo(EpVirtualGpu& ep) : ep(ep) { + ort_version_supported = ORT_API_VERSION; + CreateState = CreateStateImpl; + Compute = ComputeImpl; + ReleaseState = ReleaseStateImpl; +} + +OrtStatus* AddNodeComputeInfo::CreateStateImpl(OrtNodeComputeInfo* this_ptr, + OrtNodeComputeContext* compute_context, + void** compute_state) { + auto* node_compute_info = static_cast(this_ptr); + EpVirtualGpu& ep = node_compute_info->ep; + + std::string fused_node_name = ep.GetEpApi().NodeComputeContext_NodeName(compute_context); + auto subgraph_it = ep.GetCompiledSubgraphs().find(fused_node_name); + if (subgraph_it == ep.GetCompiledSubgraphs().end()) { + std::string message = "Unable to get compiled subgraph for fused node with name " + fused_node_name; + return ep.GetOrtApi().CreateStatus(ORT_EP_FAIL, message.c_str()); + } + + VirtualCompiledAdd& add_impl = *subgraph_it->second; + *compute_state = &add_impl; + return nullptr; +} + +OrtStatus* AddNodeComputeInfo::ComputeImpl(OrtNodeComputeInfo* this_ptr, void* compute_state, + OrtKernelContext* kernel_context) { + (void)this_ptr; + VirtualCompiledAdd& add_impl = *reinterpret_cast(compute_state); + return add_impl.Compute(kernel_context); +} + +void AddNodeComputeInfo::ReleaseStateImpl(OrtNodeComputeInfo* this_ptr, void* compute_state) { + (void)this_ptr; + VirtualCompiledAdd& add_impl = *reinterpret_cast(compute_state); + (void)add_impl; + // Do nothing for this example. +} diff --git a/onnxruntime/test/autoep/library/example_plugin_ep_virt_gpu/ep.h b/onnxruntime/test/autoep/library/example_plugin_ep_virt_gpu/ep.h new file mode 100644 index 0000000000000..da7bb05d79e62 --- /dev/null +++ b/onnxruntime/test/autoep/library/example_plugin_ep_virt_gpu/ep.h @@ -0,0 +1,62 @@ +// Copyright (c) Microsoft Corporation. All rights reserved. +// Licensed under the MIT License. + +#pragma once + +#include + +#define ORT_API_MANUAL_INIT +#include "onnxruntime_cxx_api.h" +#undef ORT_API_MANUAL_INIT + +class EpFactoryVirtualGpu; +struct VirtualCompiledAdd; + +/// +/// Example EP for a virtual GPU OrtHardwareDevice that was created by the EP factory itself (not ORT). +/// Can only compile/execute a single Add node. Only used to test that an EP can provide additional hardware devices. +/// +class EpVirtualGpu : public OrtEp { + public: + struct Config { + bool enable_ep_context = false; + // Other EP configs (typically extracted from OrtSessionOptions or OrtHardwareDevice(s)) + }; + + EpVirtualGpu(EpFactoryVirtualGpu& factory, const Config& config, const OrtLogger& logger); + ~EpVirtualGpu(); + + const OrtApi& GetOrtApi() const { return ort_api_; } + const OrtEpApi& GetEpApi() const { return ep_api_; } + + std::unordered_map>& GetCompiledSubgraphs() { + return compiled_subgraphs_; + } + + private: + static const char* ORT_API_CALL GetNameImpl(const OrtEp* this_ptr) noexcept; + + static OrtStatus* ORT_API_CALL GetCapabilityImpl(OrtEp* this_ptr, const OrtGraph* graph, + OrtEpGraphSupportInfo* graph_support_info) noexcept; + + static OrtStatus* ORT_API_CALL CompileImpl(_In_ OrtEp* this_ptr, _In_ const OrtGraph** graphs, + _In_ const OrtNode** fused_nodes, _In_ size_t count, + _Out_writes_all_(count) OrtNodeComputeInfo** node_compute_infos, + _Out_writes_(count) OrtNode** ep_context_nodes) noexcept; + + static void ORT_API_CALL ReleaseNodeComputeInfosImpl(OrtEp* this_ptr, + OrtNodeComputeInfo** node_compute_infos, + size_t num_node_compute_infos) noexcept; + + OrtStatus* CreateEpContextNodes(gsl::span fused_nodes, + /*out*/ gsl::span ep_context_nodes); + + EpFactoryVirtualGpu& factory_; + Config config_{}; + const OrtApi& ort_api_; + const OrtEpApi& ep_api_; + const OrtModelEditorApi& model_editor_api_; + std::string name_; + const OrtLogger& logger_; + std::unordered_map> compiled_subgraphs_; +}; diff --git a/onnxruntime/test/autoep/library/example_plugin_ep_virt_gpu/ep_factory.cc b/onnxruntime/test/autoep/library/example_plugin_ep_virt_gpu/ep_factory.cc new file mode 100644 index 0000000000000..da8c2b3ed7c6b --- /dev/null +++ b/onnxruntime/test/autoep/library/example_plugin_ep_virt_gpu/ep_factory.cc @@ -0,0 +1,214 @@ +// Copyright (c) Microsoft Corporation. All rights reserved. +// Licensed under the MIT License. + +#include "ep_factory.h" + +#include + +#include "core/session/onnxruntime_ep_device_ep_metadata_keys.h" + +#include "ep.h" +#include "../plugin_ep_utils.h" + +EpFactoryVirtualGpu::EpFactoryVirtualGpu(const OrtApi& ort_api, const OrtEpApi& ep_api, + const OrtModelEditorApi& model_editor_api, const OrtLogger& default_logger) + : OrtEpFactory{}, + ort_api_(ort_api), + ep_api_(ep_api), + model_editor_api_(model_editor_api), + allow_virtual_devices_{false}, + default_logger_{default_logger} { + ort_version_supported = ORT_API_VERSION; // set to the ORT version we were compiled with. + GetName = GetNameImpl; + GetVendor = GetVendorImpl; + GetVendorId = GetVendorIdImpl; + GetVersion = GetVersionImpl; + + SetEnvironmentOptions = SetEnvironmentOptionsImpl; + GetSupportedDevices = GetSupportedDevicesImpl; + + CreateEp = CreateEpImpl; + ReleaseEp = ReleaseEpImpl; + + CreateAllocator = CreateAllocatorImpl; + ReleaseAllocator = ReleaseAllocatorImpl; + + CreateDataTransfer = CreateDataTransferImpl; + + IsStreamAware = IsStreamAwareImpl; + CreateSyncStreamForDevice = CreateSyncStreamForDeviceImpl; +} + +EpFactoryVirtualGpu::~EpFactoryVirtualGpu() { + if (virtual_hw_device_ != nullptr) { + ep_api_.ReleaseHardwareDevice(virtual_hw_device_); + } +} + +/*static*/ +const char* ORT_API_CALL EpFactoryVirtualGpu::GetNameImpl(const OrtEpFactory* this_ptr) noexcept { + const auto* factory = static_cast(this_ptr); + return factory->ep_name_.c_str(); +} + +/*static*/ +const char* ORT_API_CALL EpFactoryVirtualGpu::GetVendorImpl(const OrtEpFactory* this_ptr) noexcept { + const auto* factory = static_cast(this_ptr); + return factory->vendor_.c_str(); +} + +/*static*/ +uint32_t ORT_API_CALL EpFactoryVirtualGpu::GetVendorIdImpl(const OrtEpFactory* this_ptr) noexcept { + const auto* factory = static_cast(this_ptr); + return factory->vendor_id_; +} + +/*static*/ +const char* ORT_API_CALL EpFactoryVirtualGpu::GetVersionImpl(const OrtEpFactory* this_ptr) noexcept { + const auto* factory = static_cast(this_ptr); + return factory->ep_version_.c_str(); +} + +/*static*/ +OrtStatus* ORT_API_CALL EpFactoryVirtualGpu::SetEnvironmentOptionsImpl(OrtEpFactory* this_ptr, + const OrtKeyValuePairs* options) noexcept { + auto* factory = static_cast(this_ptr); + const char* value = factory->ort_api_.GetKeyValue(options, "allow_virtual_devices"); + + if (value != nullptr) { + factory->allow_virtual_devices_ = strcmp(value, "1") == 0; + } + + return nullptr; +} + +/*static*/ +OrtStatus* ORT_API_CALL EpFactoryVirtualGpu::GetSupportedDevicesImpl(OrtEpFactory* this_ptr, + const OrtHardwareDevice* const* /*devices*/, + size_t /*num_devices*/, + OrtEpDevice** ep_devices, + size_t max_ep_devices, + size_t* p_num_ep_devices) noexcept { + size_t& num_ep_devices = *p_num_ep_devices; + auto* factory = static_cast(this_ptr); + + num_ep_devices = 0; + + // Create a virtual OrtHardwareDevice if application indicated it is allowed (e.g., for cross-compiling). + // This example EP creates a virtual GPU OrtHardwareDevice and adds a new OrtEpDevice that uses the virtual GPU. + if (factory->allow_virtual_devices_ && num_ep_devices < max_ep_devices) { + OrtKeyValuePairs* hw_metadata = nullptr; + factory->ort_api_.CreateKeyValuePairs(&hw_metadata); + factory->ort_api_.AddKeyValuePair(hw_metadata, kOrtHardwareDevice_MetadataKey_IsVirtual, "1"); + + auto* status = factory->ep_api_.CreateHardwareDevice(OrtHardwareDeviceType::OrtHardwareDeviceType_GPU, + factory->vendor_id_, + /*device_id*/ 0, + factory->vendor_.c_str(), + hw_metadata, + &factory->virtual_hw_device_); + factory->ort_api_.ReleaseKeyValuePairs(hw_metadata); // Release since ORT makes a copy. + + if (status != nullptr) { + return status; + } + + OrtKeyValuePairs* ep_metadata = nullptr; + OrtKeyValuePairs* ep_options = nullptr; + factory->ort_api_.CreateKeyValuePairs(&ep_metadata); + factory->ort_api_.CreateKeyValuePairs(&ep_options); + + // made up example metadata values. + factory->ort_api_.AddKeyValuePair(ep_metadata, "some_metadata", "1"); + factory->ort_api_.AddKeyValuePair(ep_options, "compile_optimization", "O3"); + + OrtEpDevice* virtual_ep_device = nullptr; + status = factory->ort_api_.GetEpApi()->CreateEpDevice(factory, factory->virtual_hw_device_, ep_metadata, + ep_options, &virtual_ep_device); + + factory->ort_api_.ReleaseKeyValuePairs(ep_metadata); + factory->ort_api_.ReleaseKeyValuePairs(ep_options); + + if (status != nullptr) { + return status; + } + + ep_devices[num_ep_devices++] = virtual_ep_device; + } + + return nullptr; +} + +/*static*/ +OrtStatus* ORT_API_CALL EpFactoryVirtualGpu::CreateEpImpl(OrtEpFactory* this_ptr, + const OrtHardwareDevice* const* /*devices*/, + const OrtKeyValuePairs* const* /*ep_metadata*/, + size_t num_devices, + const OrtSessionOptions* session_options, + const OrtLogger* logger, + OrtEp** ep) noexcept { + auto* factory = static_cast(this_ptr); + *ep = nullptr; + + if (num_devices != 1) { + // we only registered for GPU and only expected to be selected for one GPU + return factory->ort_api_.CreateStatus(ORT_INVALID_ARGUMENT, + "EpFactoryVirtualGpu only supports selection for one device."); + } + + std::string ep_context_enable; + RETURN_IF_ERROR(GetSessionConfigEntryOrDefault(*session_options, "ep.context_enable", "0", ep_context_enable)); + + EpVirtualGpu::Config config = {}; + config.enable_ep_context = ep_context_enable == "1"; + + auto actual_ep = std::make_unique(*factory, config, *logger); + + *ep = actual_ep.release(); + return nullptr; +} + +/*static*/ +void ORT_API_CALL EpFactoryVirtualGpu::ReleaseEpImpl(OrtEpFactory* /*this_ptr*/, OrtEp* ep) noexcept { + EpVirtualGpu* dummy_ep = static_cast(ep); + delete dummy_ep; +} + +/*static*/ +OrtStatus* ORT_API_CALL EpFactoryVirtualGpu::CreateAllocatorImpl(OrtEpFactory* /*this_ptr*/, + const OrtMemoryInfo* /*memory_info*/, + const OrtKeyValuePairs* /*allocator_options*/, + OrtAllocator** allocator) noexcept { + // Don't support custom allocators in this example for simplicity. A GPU EP would normally support allocators. + *allocator = nullptr; + return nullptr; +} + +/*static*/ +void ORT_API_CALL EpFactoryVirtualGpu::ReleaseAllocatorImpl(OrtEpFactory* /*this_ptr*/, + OrtAllocator* /*allocator*/) noexcept { + // Do nothing. +} + +/*static*/ +OrtStatus* ORT_API_CALL EpFactoryVirtualGpu::CreateDataTransferImpl(OrtEpFactory* /*this_ptr*/, + OrtDataTransferImpl** data_transfer) noexcept { + // Don't support data transfer in this example for simplicity. A GPU EP would normally support it. + *data_transfer = nullptr; + return nullptr; +} + +/*static*/ +bool ORT_API_CALL EpFactoryVirtualGpu::IsStreamAwareImpl(const OrtEpFactory* /*this_ptr*/) noexcept { + return false; +} + +/*static*/ +OrtStatus* ORT_API_CALL EpFactoryVirtualGpu::CreateSyncStreamForDeviceImpl(OrtEpFactory* /*this_ptr*/, + const OrtMemoryDevice* /*memory_device*/, + const OrtKeyValuePairs* /*stream_options*/, + OrtSyncStreamImpl** stream) noexcept { + // Don't support sync streams in this example. A GPU EP would normally support it. + *stream = nullptr; + return nullptr; +} diff --git a/onnxruntime/test/autoep/library/example_plugin_ep_virt_gpu/ep_factory.h b/onnxruntime/test/autoep/library/example_plugin_ep_virt_gpu/ep_factory.h new file mode 100644 index 0000000000000..2357b3676aa79 --- /dev/null +++ b/onnxruntime/test/autoep/library/example_plugin_ep_virt_gpu/ep_factory.h @@ -0,0 +1,82 @@ +// Copyright (c) Microsoft Corporation. All rights reserved. +// Licensed under the MIT License. + +#pragma once + +#include + +#define ORT_API_MANUAL_INIT +#include "onnxruntime_cxx_api.h" +#undef ORT_API_MANUAL_INIT + +/// +/// EP factory that creates an OrtEp instance that supports a virtual GPU OrtHardwareDevice +/// created by the factory itself (not ORT). +/// +class EpFactoryVirtualGpu : public OrtEpFactory { + public: + EpFactoryVirtualGpu(const OrtApi& ort_api, const OrtEpApi& ep_api, const OrtModelEditorApi& model_editor_api, + const OrtLogger& default_logger); + ~EpFactoryVirtualGpu(); + + const OrtApi& GetOrtApi() const { return ort_api_; } + const OrtEpApi& GetEpApi() const { return ep_api_; } + const OrtModelEditorApi& GetModelEditorApi() const { return model_editor_api_; } + const std::string& GetEpName() const { return ep_name_; } + + private: + static const char* ORT_API_CALL GetNameImpl(const OrtEpFactory* this_ptr) noexcept; + + static const char* ORT_API_CALL GetVendorImpl(const OrtEpFactory* this_ptr) noexcept; + static uint32_t ORT_API_CALL GetVendorIdImpl(const OrtEpFactory* this_ptr) noexcept; + + static const char* ORT_API_CALL GetVersionImpl(const OrtEpFactory* this_ptr) noexcept; + + static OrtStatus* ORT_API_CALL GetSupportedDevicesImpl(OrtEpFactory* this_ptr, + const OrtHardwareDevice* const* devices, + size_t num_devices, + OrtEpDevice** ep_devices, + size_t max_ep_devices, + size_t* p_num_ep_devices) noexcept; + + static OrtStatus* ORT_API_CALL CreateEpImpl(OrtEpFactory* this_ptr, + const OrtHardwareDevice* const* /*devices*/, + const OrtKeyValuePairs* const* /*ep_metadata*/, + size_t num_devices, + const OrtSessionOptions* session_options, + const OrtLogger* logger, + OrtEp** ep) noexcept; + + static void ORT_API_CALL ReleaseEpImpl(OrtEpFactory* /*this_ptr*/, OrtEp* ep) noexcept; + + static OrtStatus* ORT_API_CALL CreateAllocatorImpl(OrtEpFactory* this_ptr, + const OrtMemoryInfo* memory_info, + const OrtKeyValuePairs* /*allocator_options*/, + OrtAllocator** allocator) noexcept; + + static void ORT_API_CALL ReleaseAllocatorImpl(OrtEpFactory* /*this*/, OrtAllocator* allocator) noexcept; + + static OrtStatus* ORT_API_CALL CreateDataTransferImpl(OrtEpFactory* this_ptr, + OrtDataTransferImpl** data_transfer) noexcept; + + static bool ORT_API_CALL IsStreamAwareImpl(const OrtEpFactory* this_ptr) noexcept; + + static OrtStatus* ORT_API_CALL CreateSyncStreamForDeviceImpl(OrtEpFactory* this_ptr, + const OrtMemoryDevice* memory_device, + const OrtKeyValuePairs* stream_options, + OrtSyncStreamImpl** stream) noexcept; + + static OrtStatus* ORT_API_CALL SetEnvironmentOptionsImpl(OrtEpFactory* this_ptr, + const OrtKeyValuePairs* options) noexcept; + + const OrtApi& ort_api_; + const OrtEpApi& ep_api_; + const OrtModelEditorApi& model_editor_api_; + bool allow_virtual_devices_{false}; + const OrtLogger& default_logger_; + OrtHardwareDevice* virtual_hw_device_{}; + const std::string ep_name_{"EpVirtualGpu"}; + const std::string vendor_{"Contoso2"}; // EP vendor name + const uint32_t vendor_id_{0xB358}; // EP vendor ID + const std::string ep_version_{"0.1.0"}; // EP version +}; diff --git a/onnxruntime/test/autoep/library/example_plugin_ep_virt_gpu/ep_lib.def b/onnxruntime/test/autoep/library/example_plugin_ep_virt_gpu/ep_lib.def new file mode 100644 index 0000000000000..e9481d0d60b28 --- /dev/null +++ b/onnxruntime/test/autoep/library/example_plugin_ep_virt_gpu/ep_lib.def @@ -0,0 +1,5 @@ +LIBRARY "example_plugin_ep_virt_gpu.dll" +EXPORTS + CreateEpFactories @1 + ReleaseEpFactory @2 + diff --git a/onnxruntime/test/autoep/library/example_plugin_ep_virt_gpu/ep_lib.lds b/onnxruntime/test/autoep/library/example_plugin_ep_virt_gpu/ep_lib.lds new file mode 100644 index 0000000000000..a6d2ef09a7b16 --- /dev/null +++ b/onnxruntime/test/autoep/library/example_plugin_ep_virt_gpu/ep_lib.lds @@ -0,0 +1,7 @@ +VERS_1.0.0 { + global: + CreateEpFactories; + ReleaseEpFactory; + local: + *; +}; diff --git a/onnxruntime/test/autoep/library/example_plugin_ep_virt_gpu/ep_lib_entry.cc b/onnxruntime/test/autoep/library/example_plugin_ep_virt_gpu/ep_lib_entry.cc new file mode 100644 index 0000000000000..1e438e156828d --- /dev/null +++ b/onnxruntime/test/autoep/library/example_plugin_ep_virt_gpu/ep_lib_entry.cc @@ -0,0 +1,52 @@ +// Copyright (c) Microsoft Corporation. All rights reserved. +// Licensed under the MIT License. + +#include + +#define ORT_API_MANUAL_INIT +#include "onnxruntime_cxx_api.h" +#undef ORT_API_MANUAL_INIT + +#include "ep_factory.h" + +// To make symbols visible on macOS/iOS +#ifdef __APPLE__ +#define EXPORT_SYMBOL __attribute__((visibility("default"))) +#else +#define EXPORT_SYMBOL +#endif + +extern "C" { +// +// Public symbols +// +EXPORT_SYMBOL OrtStatus* CreateEpFactories(const char* /*registration_name*/, const OrtApiBase* ort_api_base, + const OrtLogger* default_logger, + OrtEpFactory** factories, size_t max_factories, size_t* num_factories) { + const OrtApi* ort_api = ort_api_base->GetApi(ORT_API_VERSION); + const OrtEpApi* ep_api = ort_api->GetEpApi(); + const OrtModelEditorApi* model_editor_api = ort_api->GetModelEditorApi(); + + // Manual init for the C++ API + Ort::InitApi(ort_api); + + std::unique_ptr factory = std::make_unique(*ort_api, *ep_api, *model_editor_api, + *default_logger); + + if (max_factories < 1) { + return ort_api->CreateStatus(ORT_INVALID_ARGUMENT, + "Not enough space to return EP factory. Need at least one."); + } + + factories[0] = factory.release(); + *num_factories = 1; + + return nullptr; +} + +EXPORT_SYMBOL OrtStatus* ReleaseEpFactory(OrtEpFactory* factory) { + delete static_cast(factory); + return nullptr; +} + +} // extern "C" diff --git a/onnxruntime/test/autoep/library/example_plugin_ep_utils.h b/onnxruntime/test/autoep/library/plugin_ep_utils.h similarity index 75% rename from onnxruntime/test/autoep/library/example_plugin_ep_utils.h rename to onnxruntime/test/autoep/library/plugin_ep_utils.h index decc89251dc7b..2024c5185b0d6 100644 --- a/onnxruntime/test/autoep/library/example_plugin_ep_utils.h +++ b/onnxruntime/test/autoep/library/plugin_ep_utils.h @@ -104,12 +104,46 @@ struct FloatInitializer { }; // Returns an entry in the session option configurations, or a default value if not present. -OrtStatus* GetSessionConfigEntryOrDefault(const OrtApi& ort_api, const OrtSessionOptions& session_options, - const char* config_key, const std::string& default_val, - /*out*/ std::string& config_val); +inline OrtStatus* GetSessionConfigEntryOrDefault(const OrtSessionOptions& session_options, + const char* config_key, const std::string& default_val, + /*out*/ std::string& config_val) { + try { + Ort::ConstSessionOptions sess_opt{&session_options}; + config_val = sess_opt.GetConfigEntryOrDefault(config_key, default_val); + } catch (const Ort::Exception& ex) { + Ort::Status status(ex); + return status.release(); + } + + return nullptr; +} // Returns true (via output parameter) if the given OrtValueInfo represents a float tensor. -void IsFloatTensor(Ort::ConstValueInfo value_info, bool& result); +inline void IsFloatTensor(Ort::ConstValueInfo value_info, bool& result) { + result = false; + + auto type_info = value_info.TypeInfo(); + ONNXType onnx_type = type_info.GetONNXType(); + if (onnx_type != ONNX_TYPE_TENSOR) { + return; + } + + auto type_shape = type_info.GetTensorTypeAndShapeInfo(); + ONNXTensorElementDataType elem_type = type_shape.GetElementType(); + if (elem_type != ONNX_TENSOR_ELEMENT_DATA_TYPE_FLOAT) { + return; + } + result = true; +} // Gets the tensor shape from `value_info`. Returns std::nullopt if `value_info` is not a tensor. -std::optional> GetTensorShape(Ort::ConstValueInfo value_info); +inline std::optional> GetTensorShape(Ort::ConstValueInfo value_info) { + const auto type_info = value_info.TypeInfo(); + const auto onnx_type = type_info.GetONNXType(); + if (onnx_type != ONNX_TYPE_TENSOR) { + return std::nullopt; + } + + const auto type_shape = type_info.GetTensorTypeAndShapeInfo(); + return type_shape.GetShape(); +} diff --git a/onnxruntime/test/autoep/test_allocators.cc b/onnxruntime/test/autoep/test_allocators.cc index 88b522eb10dca..3c73237708828 100644 --- a/onnxruntime/test/autoep/test_allocators.cc +++ b/onnxruntime/test/autoep/test_allocators.cc @@ -61,7 +61,7 @@ struct DummyAllocator : OrtAllocator { // validate CreateSharedAllocator allows adding an arena to the shared allocator TEST(SharedAllocators, AddArenaToSharedAllocator) { RegisteredEpDeviceUniquePtr example_ep; - Utils::RegisterAndGetExampleEp(*ort_env, example_ep); + Utils::RegisterAndGetExampleEp(*ort_env, Utils::example_ep_info, example_ep); Ort::ConstEpDevice example_ep_device{example_ep.get()}; diff --git a/onnxruntime/test/autoep/test_autoep_utils.cc b/onnxruntime/test/autoep/test_autoep_utils.cc index 7045ccca2f576..d8404e5161e0a 100644 --- a/onnxruntime/test/autoep/test_autoep_utils.cc +++ b/onnxruntime/test/autoep/test_autoep_utils.cc @@ -15,7 +15,28 @@ namespace onnxruntime { namespace test { -Utils::ExamplePluginInfo Utils::example_ep_info; +Utils::ExamplePluginInfo::ExamplePluginInfo(const ORTCHAR_T* lib_path, const char* reg_name, const char* ep_name) + : library_path(lib_path), registration_name(reg_name), ep_name(ep_name) {} + +const Utils::ExamplePluginInfo Utils::example_ep_info( +#if _WIN32 + ORT_TSTR("example_plugin_ep.dll"), +#else + ORT_TSTR("libexample_plugin_ep.so"), +#endif + // The example_plugin_ep always uses the registration name as the EP name. + "example_ep", + "example_ep"); + +const Utils::ExamplePluginInfo Utils::example_ep_virt_gpu_info( +#if _WIN32 + ORT_TSTR("example_plugin_ep_virt_gpu.dll"), +#else + "libexample_plugin_ep_virt_gpu.so", +#endif + "example_plugin_ep_virt_gpu.virtual", // Ends in ".virtual" to allow creation of virtual devices. + // This EP's name is hardcoded to the following + "EpVirtualGpu"); void Utils::GetEp(Ort::Env& env, const std::string& ep_name, const OrtEpDevice*& ep_device) { const OrtApi& c_api = Ort::GetApi(); @@ -36,18 +57,19 @@ void Utils::GetEp(Ort::Env& env, const std::string& ep_name, const OrtEpDevice*& } } -void Utils::RegisterAndGetExampleEp(Ort::Env& env, RegisteredEpDeviceUniquePtr& registered_ep) { +void Utils::RegisterAndGetExampleEp(Ort::Env& env, const ExamplePluginInfo& ep_info, + RegisteredEpDeviceUniquePtr& registered_ep) { const OrtApi& c_api = Ort::GetApi(); // this should load the library and create OrtEpDevice ASSERT_ORTSTATUS_OK(c_api.RegisterExecutionProviderLibrary(env, - example_ep_info.registration_name.c_str(), - example_ep_info.library_path.c_str())); + ep_info.registration_name.c_str(), + ep_info.library_path.c_str())); const OrtEpDevice* example_ep = nullptr; - GetEp(env, example_ep_info.registration_name, example_ep); + GetEp(env, ep_info.ep_name, example_ep); ASSERT_NE(example_ep, nullptr); - registered_ep = RegisteredEpDeviceUniquePtr(example_ep, [&env, c_api](const OrtEpDevice* /*ep*/) { - c_api.UnregisterExecutionProviderLibrary(env, example_ep_info.registration_name.c_str()); + registered_ep = RegisteredEpDeviceUniquePtr(example_ep, [&env, &ep_info, c_api](const OrtEpDevice* /*ep*/) { + c_api.UnregisterExecutionProviderLibrary(env, ep_info.registration_name.c_str()); }); } diff --git a/onnxruntime/test/autoep/test_autoep_utils.h b/onnxruntime/test/autoep/test_autoep_utils.h index 2dd7b5f0428e2..f6b5e3623505f 100644 --- a/onnxruntime/test/autoep/test_autoep_utils.h +++ b/onnxruntime/test/autoep/test_autoep_utils.h @@ -15,23 +15,23 @@ using RegisteredEpDeviceUniquePtr = std::unique_ptr ep_options; + + session_options.AppendExecutionProvider_V2(*ort_env, {plugin_ep_device}, ep_options); + + // Create model compilation options from the session options. + Ort::ModelCompilationOptions compile_options(*ort_env, session_options); + compile_options.SetFlags(OrtCompileApiFlags_ERROR_IF_NO_NODES_COMPILED); + compile_options.SetInputModelPath(input_model_file); + compile_options.SetOutputModelPath(output_model_file); + + // Compile the model. + ASSERT_CXX_ORTSTATUS_OK(Ort::CompileModel(*ort_env, compile_options)); + // Make sure the compiled model was generated. + ASSERT_TRUE(std::filesystem::exists(output_model_file)); + } +} } // namespace test } // namespace onnxruntime diff --git a/onnxruntime/test/autoep/test_registration.cc b/onnxruntime/test/autoep/test_registration.cc index 88c2e320990e1..9a0219b57092c 100644 --- a/onnxruntime/test/autoep/test_registration.cc +++ b/onnxruntime/test/autoep/test_registration.cc @@ -23,6 +23,7 @@ namespace test { TEST(OrtEpLibrary, LoadUnloadPluginLibrary) { const std::filesystem::path& library_path = Utils::example_ep_info.library_path; const std::string& registration_name = Utils::example_ep_info.registration_name; + const std::string& ep_name = Utils::example_ep_info.ep_name; const OrtApi* c_api = &Ort::GetApi(); // this should load the library and create OrtEpDevice @@ -35,10 +36,8 @@ TEST(OrtEpLibrary, LoadUnloadPluginLibrary) { ASSERT_ORTSTATUS_OK(Ort::GetApi().GetEpDevices(*ort_env, &ep_devices, &num_devices)); // should be one device for the example EP auto num_test_ep_devices = std::count_if(ep_devices, ep_devices + num_devices, - [®istration_name, &c_api](const OrtEpDevice* device) { - // the example uses the registration name for the EP name - // but that is not a requirement and the two can differ. - return c_api->EpDevice_EpName(device) == registration_name; + [&ep_name, &c_api](const OrtEpDevice* device) { + return c_api->EpDevice_EpName(device) == ep_name; }); ASSERT_EQ(num_test_ep_devices, 1) << "Expected an OrtEpDevice to have been created by the test library."; @@ -50,6 +49,7 @@ TEST(OrtEpLibrary, LoadUnloadPluginLibrary) { TEST(OrtEpLibrary, LoadUnloadPluginLibraryCxxApi) { const std::filesystem::path& library_path = Utils::example_ep_info.library_path; const std::string& registration_name = Utils::example_ep_info.registration_name; + const std::string& ep_name = Utils::example_ep_info.ep_name; // this should load the library and create OrtEpDevice ort_env->RegisterExecutionProviderLibrary(registration_name.c_str(), library_path.c_str()); @@ -58,14 +58,13 @@ TEST(OrtEpLibrary, LoadUnloadPluginLibraryCxxApi) { // should be one device for the example EP auto test_ep_device = std::find_if(ep_devices.begin(), ep_devices.end(), - [®istration_name](Ort::ConstEpDevice& device) { - // the example uses the registration name for the EP name - // but that is not a requirement and the two can differ. - return device.EpName() == registration_name; + [&ep_name](Ort::ConstEpDevice& device) { + return device.EpName() == ep_name; }); ASSERT_NE(test_ep_device, ep_devices.end()) << "Expected an OrtEpDevice to have been created by the test library."; - // test all the C++ getters. expected values are from \onnxruntime\test\autoep\library\example_plugin_ep.cc + // test all the C++ getters. + // expected values are from \onnxruntime\test\autoep\library\example_plugin_ep\*.cc ASSERT_STREQ(test_ep_device->EpVendor(), "Contoso"); auto metadata = test_ep_device->EpMetadata(); @@ -89,6 +88,86 @@ TEST(OrtEpLibrary, LoadUnloadPluginLibraryCxxApi) { ort_env->UnregisterExecutionProviderLibrary(registration_name.c_str()); } +// Test loading example_plugin_ep_virt_gpu and its associated OrtEpDevice/OrtHardwareDevice. +// This EP creates a new OrtHardwareDevice instance that represents a virtual GPU and gives to ORT. +TEST(OrtEpLibrary, LoadUnloadPluginVirtGpuLibraryCxxApi) { + const std::filesystem::path& library_path = Utils::example_ep_virt_gpu_info.library_path; + const std::string& registration_name = "example_plugin_ep_virt_gpu"; + const std::string& ep_name = Utils::example_ep_virt_gpu_info.ep_name; + + auto get_plugin_ep_devices = [&ep_name]() -> std::vector { + std::vector all_ep_devices = ort_env->GetEpDevices(); + std::vector ep_devices; + + std::copy_if(all_ep_devices.begin(), all_ep_devices.end(), std::back_inserter(ep_devices), + [&ep_name](Ort::ConstEpDevice& device) { + return device.EpName() == ep_name; + }); + + return ep_devices; + }; + + auto is_hw_device_virtual = [](Ort::ConstHardwareDevice hw_device) -> bool { + std::unordered_map metadata_entries = hw_device.Metadata().GetKeyValuePairs(); + auto iter = metadata_entries.find(kOrtHardwareDevice_MetadataKey_IsVirtual); + + if (iter == metadata_entries.end()) { + return false; + } + + return iter->second == "1"; + }; + + // Test getting EP's supported OrtEpDevices. Do not allow virtual devices. + // The EP should not return any OrtEpDevice instances. + { + ort_env->RegisterExecutionProviderLibrary(registration_name.c_str(), library_path.c_str()); + + // Find ep devices for this EP. Should not get any. + std::vector ep_devices = get_plugin_ep_devices(); + ASSERT_EQ(ep_devices.size(), 0); + + ort_env->UnregisterExecutionProviderLibrary(registration_name.c_str()); + } + + // Test getting EP's supported OrtEpDevices, but ALLOW virtual devices. + // The EP should return a OrtEpDevice for a virtual GPU. + { + // Use a registration name ending with ".virtual" to indicate to the EP library (factory) that creating virtual + // devices is allowed. + std::string registration_name_for_virtual_devices = registration_name + ".virtual"; + ort_env->RegisterExecutionProviderLibrary(registration_name_for_virtual_devices.c_str(), library_path.c_str()); + + // Find ep devices for this EP. Should get a virtual gpu. + std::vector ep_devices = get_plugin_ep_devices(); + ASSERT_EQ(ep_devices.size(), 1); + + auto virt_gpu_ep_device = std::find_if(ep_devices.begin(), ep_devices.end(), + [](Ort::ConstEpDevice& ep_device) { + return ep_device.Device().Type() == OrtHardwareDeviceType_GPU; + }); + + ASSERT_TRUE(is_hw_device_virtual(virt_gpu_ep_device->Device())); + + // test metadata and provider options attached to the virtual OrtEpDevice. + // expected values are from \onnxruntime\test\autoep\library\example_plugin_ep_virt_gpu\*.cc + ASSERT_STREQ(virt_gpu_ep_device->EpVendor(), "Contoso2"); + + auto metadata = virt_gpu_ep_device->EpMetadata(); + ASSERT_STREQ(metadata.GetValue(kOrtEpDevice_EpMetadataKey_Version), "0.1.0"); + ASSERT_STREQ(metadata.GetValue("some_metadata"), "1"); + + auto options = virt_gpu_ep_device->EpOptions(); + ASSERT_STREQ(options.GetValue("compile_optimization"), "O3"); + + // Check the virtual GPU hw device info. + ASSERT_EQ(virt_gpu_ep_device->Device().VendorId(), 0xB358); + ASSERT_EQ(virt_gpu_ep_device->Device().DeviceId(), 0); + ASSERT_STREQ(virt_gpu_ep_device->Device().Vendor(), virt_gpu_ep_device->EpVendor()); + + ort_env->UnregisterExecutionProviderLibrary(registration_name_for_virtual_devices.c_str()); + } +} } // namespace test } // namespace onnxruntime diff --git a/onnxruntime/test/autoep/test_selection.cc b/onnxruntime/test/autoep/test_selection.cc index 72f39be917f90..106a9d474c2b2 100644 --- a/onnxruntime/test/autoep/test_selection.cc +++ b/onnxruntime/test/autoep/test_selection.cc @@ -13,6 +13,7 @@ #include "core/session/abi_key_value_pairs.h" #include "core/session/abi_session_options_impl.h" #include "core/session/onnxruntime_cxx_api.h" +#include "core/session/onnxruntime_ep_device_ep_metadata_keys.h" #include "test_allocator.h" #include "test/autoep/test_autoep_utils.h" @@ -35,6 +36,12 @@ void DefaultDeviceSelection(const std::string& ep_name, std::vectorEpDevice_EpName(device) == ep_name) { + const auto* hw_device = c_api->EpDevice_Device(device); + const OrtKeyValuePairs* hw_kvps = c_api->HardwareDevice_Metadata(hw_device); + + const char* is_virtual = c_api->GetKeyValue(hw_kvps, kOrtHardwareDevice_MetadataKey_IsVirtual); + ASSERT_TRUE(is_virtual == nullptr || strcmp(is_virtual, "0") == 0); + devices.push_back(device); break; } @@ -193,6 +200,9 @@ TEST(AutoEpSelection, DmlEP) { const auto* device = c_api->EpDevice_Device(ep_device); const OrtKeyValuePairs* kvps = c_api->HardwareDevice_Metadata(device); + const char* is_virtual = c_api->GetKeyValue(kvps, kOrtHardwareDevice_MetadataKey_IsVirtual); + ASSERT_TRUE(is_virtual == nullptr || strcmp(is_virtual, "0") == 0); + if (devices.empty()) { // add the first device devices.push_back(ep_device); From b86098800f6f17b25940089335f19d3585a2599a Mon Sep 17 00:00:00 2001 From: Dmitri Smirnov Date: Thu, 30 Oct 2025 10:44:56 -0700 Subject: [PATCH 23/33] Save much memory at model loading time by converting weights to OrtValues early (#26345) ### Description Converts weights early and revert "Properly remove in-memory references (#25652)" This reverts commit 3ca49d88017cfbf90f23b7d85426ab2da0a9e1a9 and makes appropriate adjustments for the current state of the code. This PR is made possible and on the heels of: https://github.com/microsoft/onnxruntime/pull/26263 https://github.com/microsoft/onnxruntime/pull/25833. Previous history: https://github.com/microsoft/onnxruntime/pull/23979 https://github.com/microsoft/onnxruntime/pull/25320 https://github.com/microsoft/onnxruntime/pull/25626 https://github.com/microsoft/onnxruntime/pull/25652 The first change (https://github.com/microsoft/onnxruntime/pull/26263) allows us to convert initializers to OrtValues early and save lots of memory at model loading time. Specifically, for Phi-4-mini-instruct-INT4 model before and after looks like this: **Before** Before change DEBUG 2025-10-16 144819 **After** After change DEBUG 2025-10-16 144819 The two peaks represent memory usage at optimization time (8.1Gb before) and after weights memory mapping (6.5Gb) After this change corresponding numbers look 3.5Gb and 4.7Gb respectively. Most of the savings during optimization phase come from `ConstantFolding` where we are able to reuse the resulting OrtValues directly for the new initializers. This PR concludes a series of PRs converting initializers to OrtValues. Memory consumption before the conversion began was 9.3Gb and 6.7Gb respectively. We are saving almost 6Gb during optimization and 2Gb for the steady state. image The model also loads about 12 seconds faster. Example of ConstantFolding being one of the top contributors where we duplicate memory for higher peak before Resolve takes care of no longer used initializers. Sanpshot 3 Peak on ConstantFolding Transpose Optimizer Snapshot 4 Peak AddInitializer from ConstantFolding image ### Motivation and Context Reduce memory usage. --- include/onnxruntime/core/graph/graph.h | 7 - .../core/framework/session_state_utils.cc | 33 ++-- onnxruntime/core/framework/tensor.cc | 4 +- onnxruntime/core/graph/graph.cc | 76 +++++---- onnxruntime/core/graph/graph_utils.cc | 12 +- onnxruntime/core/graph/graph_utils.h | 8 +- .../core/optimizer/attention_fusion.cc | 2 +- .../compute_optimizer/shared_utils.cc | 2 +- .../core/optimizer/constant_folding.cc | 13 +- onnxruntime/core/optimizer/conv_add_fusion.cc | 4 +- onnxruntime/core/optimizer/conv_bn_fusion.cc | 4 +- onnxruntime/core/optimizer/conv_mul_fusion.cc | 4 +- .../optimizer/double_qdq_pairs_remover.cc | 2 +- .../core/optimizer/embed_layer_norm_fusion.cc | 2 +- .../fuse_initializers_transformer.cc | 8 +- onnxruntime/core/optimizer/gather_fusion.cc | 8 +- .../optimizer/group_query_attention_fusion.cc | 6 +- .../core/optimizer/matmul_add_fusion.cc | 2 +- .../core/optimizer/matmul_bn_fusion.cc | 4 +- .../core/optimizer/nchwc_transformer.cc | 10 +- .../qdq_transformer/avx2_weight_s8_to_u8.cc | 8 +- .../optimizer/qdq_transformer/qdq_s8_to_u8.cc | 2 +- .../optimizer/qdq_transformer/s8_to_u8.cc | 4 +- .../selectors_actions/qdq_actions.cc | 12 +- .../weight_bias_quantization.cc | 4 +- .../qdq_transformer/where_dummy_dq.cc | 6 +- .../core/optimizer/relu_clip_fusion.cc | 2 +- onnxruntime/core/optimizer/reshape_fusion.cc | 4 +- .../core/optimizer/stft_decomposition.cc | 6 +- .../core/optimizer/transformer_memcpy.cc | 20 ++- .../ort_optimizer_api_impl.cc | 10 +- .../core/optimizer/unsqueeze_elimination.cc | 11 +- .../providers/shared_library/provider_api.h | 2 +- onnxruntime/core/session/inference_session.cc | 23 --- .../core/session/provider_bridge_ort.cc | 2 +- .../test/framework/allocation_planner_test.cc | 24 +-- .../test/framework/cuda/fence_cuda_test.cc | 2 +- .../test/framework/session_state_test.cc | 148 ++++++------------ onnxruntime/test/ir/graph_test.cc | 5 - .../providers/tensorrt/tensorrt_basic_test.cc | 4 +- onnxruntime/test/shared_lib/test_inference.cc | 2 +- .../core/optimizer/conv1d_replacement.cc | 2 +- .../core/optimizer/megatron_transformer.cc | 28 ++-- .../orttraining/core/optimizer/qdq_fusion.cc | 4 +- .../optimizer/sce_loss_grad_bias_fusion.cc | 2 +- 45 files changed, 257 insertions(+), 291 deletions(-) diff --git a/include/onnxruntime/core/graph/graph.h b/include/onnxruntime/core/graph/graph.h index 9a0708d72b4f8..11ca73790ea79 100644 --- a/include/onnxruntime/core/graph/graph.h +++ b/include/onnxruntime/core/graph/graph.h @@ -1454,13 +1454,6 @@ class Graph { // NOLINT(clang-analyzer-optin.performance.Padding): preserve exi return Resolve(default_options); } - /// - /// This function converts all the graph TensorProto initializers into OrtValues - /// and creates a in-memory external data reference for each OrtValue. - /// - /// - Status ConvertInitializersIntoOrtValues(); - /** * @brief Converts a subset of graph TensorProto initializers into OrtValues and updates the graph proto. * diff --git a/onnxruntime/core/framework/session_state_utils.cc b/onnxruntime/core/framework/session_state_utils.cc index 4f8c5607afce9..254c520b4e54a 100644 --- a/onnxruntime/core/framework/session_state_utils.cc +++ b/onnxruntime/core/framework/session_state_utils.cc @@ -140,12 +140,12 @@ static common::Status DeserializeTensorProto(const Env& env, const std::basic_st std::move(tensor), ort_value); } } else { - // for internal initializer, always allocate memory on device - tensor - ORT_RETURN_IF_ERROR(AllocateTensor(memory_buffer, tensor, type, tensor_shape, - use_device_allocator_for_initializers, alloc)); - if (device == default_cpu_device) { // deserialize directly to CPU tensor + // Do not use arena for internal initializer, just like we do for OrtValue initializers + ORT_RETURN_IF_ERROR(AllocateTensorOnDeviceOrMemory(/* use_device_allocator_for_initializers =*/true, + tensor_shape, type, + default_cpu_alloc, tensor)); ORT_RETURN_IF_ERROR(utils::TensorProtoToTensor(env, proto_path.c_str(), tensor_proto, tensor)); Tensor::InitOrtValue(std::move(tensor), ort_value); return common::Status::OK(); @@ -154,13 +154,19 @@ static common::Status DeserializeTensorProto(const Env& env, const std::basic_st return ORT_MAKE_STATUS(ONNXRUNTIME, FAIL, "string tensor is not supported for copying between allocators"); } + // Allocate according to the plan on the device or directly on the device according to + // use_device_allocator_for_initializers + ORT_RETURN_IF_ERROR(AllocateTensor(memory_buffer, tensor, type, tensor_shape, + use_device_allocator_for_initializers, alloc)); + // deserialize to CPU first for non-CPU allocator, then copy // for internal initializer - // 1. allocate memory on CPU - deserialized_tensor - // 2. deserialize tensor_proto into a preallocated tensor (deserialized_tensor) + // 1. allocate memory on CPU - deserialized_tensor. Do not use arena not to waste space for temporary buffers. + // 2. deserialize tensor_proto into a pre-allocated tensor (deserialized_tensor) // 3. copy tensor from CPU to device - deserialized_tensor -> tensor (allocated above) -> ort_value Tensor deserialized_tensor; - ORT_RETURN_IF_ERROR(AllocateTensorOnDeviceOrMemory(use_device_allocator_for_initializers, tensor_shape, type, + ORT_RETURN_IF_ERROR(AllocateTensorOnDeviceOrMemory(/* use_device_allocator_for_initializers =*/true, + tensor_shape, type, default_cpu_alloc, deserialized_tensor)); ORT_RETURN_IF_ERROR(utils::TensorProtoToTensor(env, proto_path.c_str(), tensor_proto, deserialized_tensor)); @@ -346,6 +352,13 @@ common::Status SaveInitializedTensors( << i.second << " bytes for " << i.first.ToString() << std::endl; } + // ??? Should we ignore this session option if the EP is explicitly providing the read only allocator? + // bool have_readonly_initializer_allocator = alloc->Info().alloc_type == OrtReadOnlyAllocator; + // This option also means to ignore arena if present and use Reserve(). + const bool use_device_allocator_for_initializers = + session_options.config_options.GetConfigOrDefault( + kOrtSessionOptionsUseDeviceAllocatorForInitializers, "0") == "1"; + // 3. create weight tensors based on weights buffer for (const auto& entry : id_to_initialized_tensor) { // We check for cancellation for every initializer since mapping from disk can be costly @@ -375,12 +388,6 @@ common::Status SaveInitializedTensors( // TODO: if the tensor need be copied, does it have enough room? ORT_RETURN_IF_ERROR(planner.GetPreallocatedBuffer(ort_value_index, name, memory_buffer, alloc)); - // ??? Should we ignore this session option if the EP is explicitly providing the read only allocator? - // bool have_readonly_initializer_allocator = alloc->Info().alloc_type == OrtReadOnlyAllocator; - const bool use_device_allocator_for_initializers = - session_options.config_options.GetConfigOrDefault( - kOrtSessionOptionsUseDeviceAllocatorForInitializers, "0") == "1"; - // Check if we already have an OrtValue for this initializer on CPU if (OrtValue ort_value_from_graph; graph.GetOrtValueInitializer(name, ort_value_from_graph)) { diff --git a/onnxruntime/core/framework/tensor.cc b/onnxruntime/core/framework/tensor.cc index 133f21be97c46..eefd7825eca5b 100644 --- a/onnxruntime/core/framework/tensor.cc +++ b/onnxruntime/core/framework/tensor.cc @@ -93,14 +93,14 @@ Tensor::Tensor(MLDataType elt_type, const TensorShape& shape, std::shared_ptr 0) { p_data = allocator->Alloc(len); } - Init(elt_type, shape, p_data, allocator, 0L); + Init(elt_type, shape, p_data, std::move(allocator), 0L); } Tensor::Tensor(MLDataType elt_type, const TensorShape& shape, void* p_data, std::shared_ptr deleter, ptrdiff_t offset, gsl::span strides) : alloc_info_(deleter->Info()) { ORT_ENFORCE(elt_type != nullptr); - Init(elt_type, shape, p_data, deleter, offset, strides); + Init(elt_type, shape, p_data, std::move(deleter), offset, strides); } void Tensor::InitOrtValue(MLDataType elt_type, const TensorShape& shape, std::shared_ptr allocator, diff --git a/onnxruntime/core/graph/graph.cc b/onnxruntime/core/graph/graph.cc index 8b599dc86d997..3d67314cf693a 100644 --- a/onnxruntime/core/graph/graph.cc +++ b/onnxruntime/core/graph/graph.cc @@ -1231,6 +1231,28 @@ Graph::Graph(const Model& owning_model, ArgNameToTypeMap name_to_type_map; const auto& model_path = ModelPath(); + // If the tensor proto data is large enough, move data from TensorProto to an OrtValue + // - Add external data reference to TensorProto that points to an OrtValue. + // This lambda should not be used on initializers that already have external data reference. + // Otherwise, this function does nothing. + auto put_large_tensor_in_ort_value = [this, &model_path](ONNX_NAMESPACE::TensorProto& tensor_proto) { + size_t size_in_bytes = 0; + ORT_THROW_IF_ERROR(utils::GetSizeInBytesFromTensorProto<0>(tensor_proto, &size_in_bytes)); + if (size_in_bytes > utils::kSmallTensorExternalDataThreshold) { + OrtValue ort_value; + ORT_THROW_IF_ERROR(utils::TensorProtoToOrtValue(Env::Default(), model_path, tensor_proto, + CPUAllocator::DefaultInstance(), ort_value)); + constexpr const bool use_tensor_buffer_true = true; + auto tensor_proto_to_add = utils::TensorToTensorProto(ort_value.Get(), tensor_proto.name(), + use_tensor_buffer_true); + assert(ort_value.IsAllocated()); + auto ins_result = ortvalue_initializers_.insert_or_assign(tensor_proto_to_add.name(), std::move(ort_value)); + ORT_ENFORCE(ins_result.second, "Unexpected duplicate insert or assign OrtValue for tensor: ", tensor_proto_to_add.name(), + " in the initializer list."); + tensor_proto = std::move(tensor_proto_to_add); + } + }; + // Process 'Constant' nodes // Put the 'TensorProto' stored in the 'Constant' nodes attribute into the graphs initializer list for (auto& node : graph_proto_->node()) { @@ -1250,6 +1272,8 @@ Graph::Graph(const Model& owning_model, } } + put_large_tensor_in_ort_value(*tensor); + // Ensure initializers are also graph inputs. if (ir_version_ < 4) { TypeProto t{utils::TypeProtoFromTensorProto(*tensor)}; @@ -1326,7 +1350,25 @@ Graph::Graph(const Model& owning_model, } // Copy initial tensors to a map. - for (auto& tensor : graph_proto_->initializer()) { + for (int i = 0, lim = graph_proto_->initializer_size(); i < lim; ++i) { + auto& tensor = *graph_proto_->mutable_initializer(i); + // If data is on disk, it will be loaded either by optimizers + // or during session state finalization. + // If data is already in memory, do nothing. + if (!utils::HasExternalData(tensor)) { + // sparse_tensor_names_ contain references to strings to save memory + // in case we replace the tensor_proto, we want to make sure we remove + // the old reference first, and then add a new one. + const bool is_sparse = sparse_tensor_names_.count(tensor.name()); + if (is_sparse) { + sparse_tensor_names_.erase(tensor.name()); + } + put_large_tensor_in_ort_value(tensor); + if (is_sparse) { + sparse_tensor_names_.emplace(tensor.name()); + } + } + auto p = name_to_initial_tensor_.emplace(tensor.name(), &tensor); if (!p.second) { LOGS(logger_, WARNING) << "Duplicate initializer (dense, sparse or ConstantNode): '" << tensor.name() @@ -3415,38 +3457,6 @@ Status Graph::Resolve(const ResolveOptions& options) { return ForThisAndAllSubgraphs(all_subgraphs, finalize_func); } -Status Graph::ConvertInitializersIntoOrtValues() { - std::vector all_subgraphs; - FindAllSubgraphs(all_subgraphs); - - auto put_weights_maybe_in_memory_func = [&](Graph& graph) -> Status { - // if we have any initializers that are not in memory, put them there. - const auto& model_path = graph.ModelPath(); - auto& graph_proto = *graph.graph_proto_; - for (int i = 0, lim = graph_proto.initializer_size(); i < lim; ++i) { - auto& tensor_proto = *graph_proto.mutable_initializer(i); - if (utils::HasExternalData(tensor_proto)) { - continue; // ignore data on disk, that will be loaded either by EP or at session_state finalize - } - - size_t size_in_bytes = 0; - ORT_RETURN_IF_ERROR(utils::GetSizeInBytesFromTensorProto<0>(tensor_proto, &size_in_bytes)); - if (size_in_bytes > utils::kSmallTensorExternalDataThreshold) { - OrtValue ort_value; - ORT_RETURN_IF_ERROR(utils::TensorProtoToOrtValue(Env::Default(), model_path, tensor_proto, - CPUAllocator::DefaultInstance(), ort_value)); - constexpr const bool use_tensor_buffer_true = true; - auto tensor_proto_to_add = utils::TensorToTensorProto(ort_value.Get(), tensor_proto.name(), - use_tensor_buffer_true); - ORT_RETURN_IF_ERROR(graph.ReplaceInitializedTensor(tensor_proto_to_add, ort_value)); - } - } - return Status::OK(); - }; - - return ForThisAndAllSubgraphs(all_subgraphs, put_weights_maybe_in_memory_func); -} - void Graph::SetName(const std::string& name) { graph_proto_->set_name(name); } diff --git a/onnxruntime/core/graph/graph_utils.cc b/onnxruntime/core/graph/graph_utils.cc index c38e1fcff46b3..0480263befdd1 100644 --- a/onnxruntime/core/graph/graph_utils.cc +++ b/onnxruntime/core/graph/graph_utils.cc @@ -285,7 +285,7 @@ NodeArg& AddInitializer(Graph& graph, const ONNX_NAMESPACE::TensorProto& new_ini return GetOrCreateNodeArg(graph, new_initializer); } -NodeArg& AddInitializerWithExternalData(Graph& graph, const ONNX_NAMESPACE::TensorProto& new_initializer) { +NodeArg& AddInitializerWithOrtValue(Graph& graph, const ONNX_NAMESPACE::TensorProto& new_initializer) { const bool has_external_data = utils::HasExternalData(new_initializer); ORT_ENFORCE(!has_external_data, "Expecting an initializer that contains data inline"); @@ -293,11 +293,11 @@ NodeArg& AddInitializerWithExternalData(Graph& graph, const ONNX_NAMESPACE::Tens ORT_THROW_IF_ERROR(utils::CreateTensorFromTensorProto(Env::Default(), graph.ModelPath(), new_initializer, tensor)); auto tensor_proto_with_ptr = utils::TensorToTensorProto(tensor, new_initializer.name(), true); - return AddInitializerWithExternalData(graph, tensor_proto_with_ptr, std::move(tensor)); + return AddInitializerWithOrtValue(graph, tensor_proto_with_ptr, std::move(tensor)); } -NodeArg& AddInitializerWithExternalData(Graph& graph, const ONNX_NAMESPACE::TensorProto& new_initializer, - Tensor&& tensor) { +NodeArg& AddInitializerWithOrtValue(Graph& graph, const ONNX_NAMESPACE::TensorProto& new_initializer, + Tensor&& tensor) { OrtValue ort_value; if (utils::HasExternalDataInMemory(new_initializer)) { Tensor::InitOrtValue(std::move(tensor), ort_value); @@ -307,8 +307,8 @@ NodeArg& AddInitializerWithExternalData(Graph& graph, const ONNX_NAMESPACE::Tens return GetOrCreateNodeArg(graph, new_initializer); } -NodeArg& AddInitializerWithExternalData(Graph& graph, const ONNX_NAMESPACE::TensorProto& new_initializer, - OrtValue ort_value) { +NodeArg& AddInitializerWithOrtValue(Graph& graph, const ONNX_NAMESPACE::TensorProto& new_initializer, + OrtValue ort_value) { ORT_THROW_IF_ERROR(graph.AddInitializedOrtValue(new_initializer, ort_value)); return GetOrCreateNodeArg(graph, new_initializer); } diff --git a/onnxruntime/core/graph/graph_utils.h b/onnxruntime/core/graph/graph_utils.h index b6bf5927a3c6c..256a6fc81495d 100644 --- a/onnxruntime/core/graph/graph_utils.h +++ b/onnxruntime/core/graph/graph_utils.h @@ -45,8 +45,8 @@ NodeArg& AddInitializer(Graph& graph, const ONNX_NAMESPACE::TensorProto& new_ini /// TensorProto with external data contained in ort_value /// ort_value with data /// -NodeArg& AddInitializerWithExternalData(Graph& graph, const ONNX_NAMESPACE::TensorProto& new_initializer, - OrtValue ort_value); +NodeArg& AddInitializerWithOrtValue(Graph& graph, const ONNX_NAMESPACE::TensorProto& new_initializer, + OrtValue ort_value); /** Add a new initializer to 'graph'. * Checks that new_initializer does not already exist in 'graph' before adding it. @@ -55,7 +55,7 @@ NodeArg& AddInitializerWithExternalData(Graph& graph, const ONNX_NAMESPACE::Tens * @returns The NodeArg for the new initializer. * @remarks No matching graph input is created, so the initializer will be constant. */ -NodeArg& AddInitializerWithExternalData(Graph& graph, const ONNX_NAMESPACE::TensorProto& new_initializer, Tensor&& tensor); +NodeArg& AddInitializerWithOrtValue(Graph& graph, const ONNX_NAMESPACE::TensorProto& new_initializer, Tensor&& tensor); /** Add a new initializer to 'graph'. * The function unpacks data into a tensor and converts new_initializer to a TensorProto with external data in memory. @@ -67,7 +67,7 @@ NodeArg& AddInitializerWithExternalData(Graph& graph, const ONNX_NAMESPACE::Tens * @returns The NodeArg for the new initializer. * @remarks No matching graph input is created, so the initializer will be constant. */ -NodeArg& AddInitializerWithExternalData(Graph& graph, const ONNX_NAMESPACE::TensorProto& new_initializer); +NodeArg& AddInitializerWithOrtValue(Graph& graph, const ONNX_NAMESPACE::TensorProto& new_initializer); /// /// If the initializer with the given name does not exist in the destination graph, but exists in the diff --git a/onnxruntime/core/optimizer/attention_fusion.cc b/onnxruntime/core/optimizer/attention_fusion.cc index 3f9b58f71bd23..9fd71b3b00cd0 100644 --- a/onnxruntime/core/optimizer/attention_fusion.cc +++ b/onnxruntime/core/optimizer/attention_fusion.cc @@ -111,7 +111,7 @@ static NodeArg& MergeQkvWeights(Graph& graph, int64_t hidden_size, utils::SetRawDataInTensorProto(initializer, result.data(), gsl::narrow(element_count) * sizeof(MLFloat16)); } - return graph_utils::AddInitializer(graph, initializer); + return graph_utils::AddInitializerWithOrtValue(graph, initializer); } static NodeArg* ConvertMaskToInt32(Graph& graph, NodeArg* mask_input, ProviderType provider_type, diff --git a/onnxruntime/core/optimizer/compute_optimizer/shared_utils.cc b/onnxruntime/core/optimizer/compute_optimizer/shared_utils.cc index 86a7a4d6afbf8..87af11808506d 100644 --- a/onnxruntime/core/optimizer/compute_optimizer/shared_utils.cc +++ b/onnxruntime/core/optimizer/compute_optimizer/shared_utils.cc @@ -189,7 +189,7 @@ NodeArg* CreateInitializerFromVector(Graph& graph, "total_count: ", total_count, " values.size(): ", values.size()); utils::SetRawDataInTensorProto(const_tensor, values.data(), values.size() * sizeof(int64_t)); - return &graph_utils::AddInitializer(graph, const_tensor); + return &graph_utils::AddInitializerWithOrtValue(graph, const_tensor); } NodeArg* InsertNodesForValidIndices(Graph& graph, diff --git a/onnxruntime/core/optimizer/constant_folding.cc b/onnxruntime/core/optimizer/constant_folding.cc index 16e8955cb4486..9db3e85585035 100644 --- a/onnxruntime/core/optimizer/constant_folding.cc +++ b/onnxruntime/core/optimizer/constant_folding.cc @@ -95,7 +95,7 @@ static bool ConstantFoldShapeNode(Graph& graph, Node& node) { ONNX_NAMESPACE::TensorShapeProto result_shape; result_shape.add_dim()->set_dim_value(clamped_slice_length); constant_arg_out->SetShape(result_shape); - graph_utils::AddInitializer(graph, shape_constant); + graph_utils::AddInitializerWithOrtValue(graph, shape_constant); } return is_concrete_shape; // convert to constant if this is true @@ -317,11 +317,11 @@ Status ConstantFolding::ApplyImpl(Graph& graph, bool& modified, int graph_level, // Build the TensorProto that corresponds to the computed OrtValue and add it as initializer to the graph. auto* constant_arg_out = node->MutableOutputDefs()[fetch_idx]; const Tensor& out_tensor = ort_value.Get(); - constexpr const bool use_tensor_buffer_false = false; + constexpr const bool use_tensor_buffer_true = true; ONNX_NAMESPACE::TensorProto out_tensorproto = utils::TensorToTensorProto( out_tensor, constant_arg_out->Name(), - use_tensor_buffer_false); + use_tensor_buffer_true); ONNX_NAMESPACE::TensorShapeProto result_shape; for (auto& dim : out_tensor.Shape().GetDims()) { @@ -329,7 +329,12 @@ Status ConstantFolding::ApplyImpl(Graph& graph, bool& modified, int graph_level, } constant_arg_out->SetShape(result_shape); - graph.AddInitializedTensor(out_tensorproto); + // The data is too small and has been inlined. + if (!utils::HasExternalData(out_tensorproto)) { + ORT_THROW_IF_ERROR(graph.AddInitializedOrtValue(out_tensorproto, OrtValue())); + } else { + ORT_THROW_IF_ERROR(graph.AddInitializedOrtValue(out_tensorproto, ort_value)); + } } } } diff --git a/onnxruntime/core/optimizer/conv_add_fusion.cc b/onnxruntime/core/optimizer/conv_add_fusion.cc index 6478fa7d29d5b..e1fd199bfa943 100644 --- a/onnxruntime/core/optimizer/conv_add_fusion.cc +++ b/onnxruntime/core/optimizer/conv_add_fusion.cc @@ -79,7 +79,7 @@ Status ConvAddFusion::Apply(Graph& graph, Node& node, RewriteRuleEffect& modifie auto new_name = graph.GenerateNodeArgName("ConvAddFusion_B_" + B_input_name); new_conv_B_tensor_proto.set_name(new_name); - NodeArg& new_conv_B_node_arg = graph_utils::AddInitializer(graph, new_conv_B_tensor_proto); + NodeArg& new_conv_B_node_arg = graph_utils::AddInitializerWithOrtValue(graph, new_conv_B_tensor_proto); graph_utils::ReplaceNodeInput(node, 2, new_conv_B_node_arg); } else { @@ -94,7 +94,7 @@ Status ConvAddFusion::Apply(Graph& graph, Node& node, RewriteRuleEffect& modifie auto new_name = graph.GenerateNodeArgName("ConvAddFusion_Add_B_" + add_B_tensor_proto->name()); new_conv_B_tensor_proto.set_name(new_name); - NodeArg& new_add_B_node_arg = graph_utils::AddInitializer(graph, new_conv_B_tensor_proto); + NodeArg& new_add_B_node_arg = graph_utils::AddInitializerWithOrtValue(graph, new_conv_B_tensor_proto); graph_utils::AddNodeInput(node, 2, new_add_B_node_arg); } diff --git a/onnxruntime/core/optimizer/conv_bn_fusion.cc b/onnxruntime/core/optimizer/conv_bn_fusion.cc index a14639631d7a1..4c493f45a2b61 100644 --- a/onnxruntime/core/optimizer/conv_bn_fusion.cc +++ b/onnxruntime/core/optimizer/conv_bn_fusion.cc @@ -120,10 +120,10 @@ Status ConvBNFusion::Apply(Graph& graph, Node& node, RewriteRuleEffect& rule_eff new_conv_W_tensor_proto.set_name(new_W_name); new_conv_B_tensor_proto.set_name(new_B_name); - NodeArg& new_conv_W_node_arg = graph_utils::AddInitializer(graph, new_conv_W_tensor_proto); + NodeArg& new_conv_W_node_arg = graph_utils::AddInitializerWithOrtValue(graph, new_conv_W_tensor_proto); graph_utils::ReplaceNodeInput(node, 1, new_conv_W_node_arg); - auto& new_conv_B_node_arg = graph_utils::AddInitializer(graph, new_conv_B_tensor_proto); + auto& new_conv_B_node_arg = graph_utils::AddInitializerWithOrtValue(graph, new_conv_B_tensor_proto); if (conv_inputs.size() == 3) { graph_utils::ReplaceNodeInput(node, 2, new_conv_B_node_arg); diff --git a/onnxruntime/core/optimizer/conv_mul_fusion.cc b/onnxruntime/core/optimizer/conv_mul_fusion.cc index e91a00729e9db..9563415ad56b6 100644 --- a/onnxruntime/core/optimizer/conv_mul_fusion.cc +++ b/onnxruntime/core/optimizer/conv_mul_fusion.cc @@ -90,7 +90,7 @@ Status ConvMulFusion::Apply(Graph& graph, Node& node, RewriteRuleEffect& rule_ef new_conv_W_tensor_proto.set_name(new_W_name); // Replace initializers of conv node - NodeArg& new_conv_W_node_arg = graph_utils::AddInitializer(graph, new_conv_W_tensor_proto); + NodeArg& new_conv_W_node_arg = graph_utils::AddInitializerWithOrtValue(graph, new_conv_W_tensor_proto); graph_utils::ReplaceNodeInput(conv_node, 1, new_conv_W_node_arg); if (is_3d) { @@ -100,7 +100,7 @@ Status ConvMulFusion::Apply(Graph& graph, Node& node, RewriteRuleEffect& rule_ef auto new_B_name = graph.GenerateNodeArgName("ConvMulFusion_Mul_B_" + mul_B_tensor_proto->name()); new_conv_B_tensor_proto.set_name(new_B_name); - NodeArg& new_conv_B_node_arg = graph_utils::AddInitializer(graph, new_conv_B_tensor_proto); + NodeArg& new_conv_B_node_arg = graph_utils::AddInitializerWithOrtValue(graph, new_conv_B_tensor_proto); graph_utils::ReplaceNodeInput(conv_node, 2, new_conv_B_node_arg); } diff --git a/onnxruntime/core/optimizer/double_qdq_pairs_remover.cc b/onnxruntime/core/optimizer/double_qdq_pairs_remover.cc index 96f75f07e32e1..6ea2a17d26125 100644 --- a/onnxruntime/core/optimizer/double_qdq_pairs_remover.cc +++ b/onnxruntime/core/optimizer/double_qdq_pairs_remover.cc @@ -53,7 +53,7 @@ static void ApplyNewInputValue(Graph& graph, Node& node, QDQ::InputIndex index, auto new_name = graph.GenerateNodeArgName("DoubleQDQRemoved_" + node.InputDefs()[index]->Name()); new_input_tensor.set_name(new_name); new_input_tensor.add_dims(1); - NodeArg& new_input = graph_utils::AddInitializer(graph, new_input_tensor); + NodeArg& new_input = graph_utils::AddInitializerWithOrtValue(graph, new_input_tensor); graph_utils::ReplaceNodeInput(node, index, new_input); } diff --git a/onnxruntime/core/optimizer/embed_layer_norm_fusion.cc b/onnxruntime/core/optimizer/embed_layer_norm_fusion.cc index f8fd807084d38..9e35550e2f845 100644 --- a/onnxruntime/core/optimizer/embed_layer_norm_fusion.cc +++ b/onnxruntime/core/optimizer/embed_layer_norm_fusion.cc @@ -474,7 +474,7 @@ static NodeArg* ExtractEmbedding(Graph& graph, utils::SetRawDataInTensorProto(initializer, data, gsl::narrow(element_count) * sizeof(MLFloat16)); } - NodeArg& node_arg = graph_utils::AddInitializer(graph, initializer); + NodeArg& node_arg = graph_utils::AddInitializerWithOrtValue(graph, initializer); modified = true; return &node_arg; } diff --git a/onnxruntime/core/optimizer/fuse_initializers_transformer.cc b/onnxruntime/core/optimizer/fuse_initializers_transformer.cc index e604c688ee033..9a24687d9a4d9 100644 --- a/onnxruntime/core/optimizer/fuse_initializers_transformer.cc +++ b/onnxruntime/core/optimizer/fuse_initializers_transformer.cc @@ -137,8 +137,12 @@ static void FuseInitializerWithNode(Graph& graph, graph.RemoveEdge(node.Index(), next_node.Index(), 0, static_cast(next_node_arg_index)); // Add the new converted Tensor in next node as initializer potentially with external data - ONNX_NAMESPACE::TensorProto dst_tensor = utils::TensorToTensorProto(new_data.Get(), new_arg_name, false); - auto& new_arg = graph_utils::AddInitializer(graph, dst_tensor); + ONNX_NAMESPACE::TensorProto dst_tensor = utils::TensorToTensorProto(new_data.Get(), new_arg_name, true); + if (!utils::HasExternalData(dst_tensor)) { + new_data = OrtValue(); // Data is inline + } + + auto& new_arg = graph_utils::AddInitializerWithOrtValue(graph, dst_tensor, std::move(new_data)); graph_utils::ReplaceNodeInput(next_node, static_cast(next_node_arg_index), new_arg); } diff --git a/onnxruntime/core/optimizer/gather_fusion.cc b/onnxruntime/core/optimizer/gather_fusion.cc index bd730683a4c91..32a45e548ca0a 100644 --- a/onnxruntime/core/optimizer/gather_fusion.cc +++ b/onnxruntime/core/optimizer/gather_fusion.cc @@ -256,7 +256,7 @@ Status GatherSliceToSplitFusion::ApplyImpl(Graph& graph, bool& modified, int gra axes_initializer_proto.add_dims(static_cast(1)); axes_initializer_proto.set_data_type(ONNX_NAMESPACE::TensorProto_DataType_INT64); axes_initializer_proto.add_int64_data(axis); - NodeArg* axes_arg = &graph_utils::AddInitializer(graph, axes_initializer_proto); + NodeArg* axes_arg = &graph_utils::AddInitializerWithOrtValue(graph, axes_initializer_proto); Node& squeeze_node = graph.AddNode(graph.GenerateNodeName("Squeeze"), "Squeeze", "Squeeze for Fused Gather nodes", {split_output_arg, axes_arg}, {original_output_arg}); @@ -272,7 +272,7 @@ Status GatherSliceToSplitFusion::ApplyImpl(Graph& graph, bool& modified, int gra split_initializer_proto.set_data_type(ONNX_NAMESPACE::TensorProto_DataType_INT64); split_initializer_proto.add_dims(static_cast(split_values.size())); split_initializer_proto.mutable_int64_data()->Add(split_values.begin(), split_values.end()); - NodeArg* split_initializer_arg = &graph_utils::AddInitializer(graph, split_initializer_proto); + NodeArg* split_initializer_arg = &graph_utils::AddInitializerWithOrtValue(graph, split_initializer_proto); const auto split_node_name = graph.GenerateNodeName(nodes_to_fuse[0].get().Name() + "/GatherSliceToSplitFusion"); Node& split_node = graph.AddNode(split_node_name, "Split", "Split for Fused Gather nodes", {graph.GetNodeArg(node_arg->Name()), split_initializer_arg}, split_outputs); @@ -359,7 +359,7 @@ Status GatherToSliceFusion::ApplyImpl(Graph& graph, bool& modified, int graph_le unsqueeze_axes_initializer_proto.add_dims(static_cast(1)); unsqueeze_axes_initializer_proto.set_data_type(ONNX_NAMESPACE::TensorProto_DataType_INT64); unsqueeze_axes_initializer_proto.add_int64_data(static_cast(0)); - NodeArg* unsqueeze_axes_arg = &graph_utils::AddInitializer(graph, unsqueeze_axes_initializer_proto); + NodeArg* unsqueeze_axes_arg = &graph_utils::AddInitializerWithOrtValue(graph, unsqueeze_axes_initializer_proto); for (size_t i = 0; i < range_input_defs.size(); ++i) { Node& unsqueeze_node = graph.AddNode(graph.GenerateNodeName("Unsqueeze_" + std::to_string(i)), "Unsqueeze", @@ -386,7 +386,7 @@ Status GatherToSliceFusion::ApplyImpl(Graph& graph, bool& modified, int graph_le } else { slice_axes_initializer_proto.add_int32_data(static_cast(axis)); } - NodeArg* slice_axes_arg = &graph_utils::AddInitializer(graph, slice_axes_initializer_proto); + NodeArg* slice_axes_arg = &graph_utils::AddInitializerWithOrtValue(graph, slice_axes_initializer_proto); Node& slice_node = graph.AddNode(graph.GenerateNodeName("Slice"), "Slice", "Slice for Fused Gather nodes", {gather_node.MutableInputDefs()[0], unsqueeze_outputs[0], unsqueeze_outputs[1], slice_axes_arg, unsqueeze_outputs[2]}, diff --git a/onnxruntime/core/optimizer/group_query_attention_fusion.cc b/onnxruntime/core/optimizer/group_query_attention_fusion.cc index fcb744bea4df1..f6bfd29315c58 100644 --- a/onnxruntime/core/optimizer/group_query_attention_fusion.cc +++ b/onnxruntime/core/optimizer/group_query_attention_fusion.cc @@ -129,8 +129,8 @@ static std::vector MergeQkvWeightsForMatMulNBits( utils::SetRawDataInTensorProto(qkv_weight_initializer, merged_qkv_weight.data(), element_count * sizeof(uint8_t)); utils::SetRawDataInTensorProto(qkv_scale_initializer, merged_qkv_scale.data(), scale_elements_count * sizeof(MLFloat16)); - NodeArg& qkv_weight_arg = graph_utils::AddInitializer(graph, qkv_weight_initializer); - NodeArg& qkv_scale_arg = graph_utils::AddInitializer(graph, qkv_scale_initializer); + NodeArg& qkv_weight_arg = graph_utils::AddInitializerWithOrtValue(graph, qkv_weight_initializer); + NodeArg& qkv_scale_arg = graph_utils::AddInitializerWithOrtValue(graph, qkv_scale_initializer); std::vector result_node_args = {&qkv_weight_arg, &qkv_scale_arg}; @@ -160,7 +160,7 @@ static std::vector MergeQkvWeightsForMatMulNBits( utils::SetRawDataInTensorProto(qkv_zp_initializer, merged_qkv_zp.data(), zp_elements_count * sizeof(uint8_t)); - NodeArg& qkv_zp_arg = graph_utils::AddInitializer(graph, qkv_zp_initializer); + NodeArg& qkv_zp_arg = graph_utils::AddInitializerWithOrtValue(graph, qkv_zp_initializer); result_node_args.push_back(&qkv_zp_arg); } diff --git a/onnxruntime/core/optimizer/matmul_add_fusion.cc b/onnxruntime/core/optimizer/matmul_add_fusion.cc index fed72db71332a..5db61877811aa 100644 --- a/onnxruntime/core/optimizer/matmul_add_fusion.cc +++ b/onnxruntime/core/optimizer/matmul_add_fusion.cc @@ -194,7 +194,7 @@ Status MatMulAddFusion::ApplyImpl(Graph& graph, bool& modified, int graph_level, shape_initializer_proto.add_dims(static_cast(shape.size())); shape_initializer_proto.set_data_type(ONNX_NAMESPACE::TensorProto_DataType_INT64); utils::SetRawDataInTensorProto(shape_initializer_proto, shape.data(), shape.size() * sizeof(int64_t)); - NodeArg* shape_arg = &graph_utils::AddInitializer(graph, shape_initializer_proto); + NodeArg* shape_arg = &graph_utils::AddInitializerWithOrtValue(graph, shape_initializer_proto); ONNX_NAMESPACE::TypeProto new_arg_type; const ONNX_NAMESPACE::TensorProto_DataType element_type = static_cast( gemm_input_defs[0]->TypeAsProto()->tensor_type().elem_type()); diff --git a/onnxruntime/core/optimizer/matmul_bn_fusion.cc b/onnxruntime/core/optimizer/matmul_bn_fusion.cc index 367fb42d7928d..63a15ad630ce9 100644 --- a/onnxruntime/core/optimizer/matmul_bn_fusion.cc +++ b/onnxruntime/core/optimizer/matmul_bn_fusion.cc @@ -212,14 +212,14 @@ Status MatmulBNFusion::Apply(Graph& graph, Node& matmul_node, RewriteRuleEffect& matmul_b.ToProto(new_gemm_b_tensor); const std::string new_gemm_b_name = graph.GenerateNodeArgName("MatMulBnFusion_GemmB_" + matmul_b_tensor->name()); new_gemm_b_tensor.set_name(new_gemm_b_name); - NodeArg& new_gemm_b_node_arg = graph_utils::AddInitializer(graph, new_gemm_b_tensor); + NodeArg& new_gemm_b_node_arg = graph_utils::AddInitializerWithOrtValue(graph, new_gemm_b_tensor); // create bias tensorProto for new Gemm node from initializer. ONNX_NAMESPACE::TensorProto new_gemm_bias_tensor; bias.ToProto(new_gemm_bias_tensor); const std::string new_gemm_bias_name = graph.GenerateNodeArgName("MatMulBnFusion_GemmBias"); new_gemm_bias_tensor.set_name(new_gemm_bias_name); - NodeArg& new_gemm_bias_node_arg = graph_utils::AddInitializer(graph, new_gemm_bias_tensor); + NodeArg& new_gemm_bias_node_arg = graph_utils::AddInitializerWithOrtValue(graph, new_gemm_bias_tensor); Node& gemm_node = graph.AddNode( graph.GenerateNodeArgName("MatMulBnFusion_Gemm"), diff --git a/onnxruntime/core/optimizer/nchwc_transformer.cc b/onnxruntime/core/optimizer/nchwc_transformer.cc index 3d1e5ccfdc4d5..bff9d2990118a 100644 --- a/onnxruntime/core/optimizer/nchwc_transformer.cc +++ b/onnxruntime/core/optimizer/nchwc_transformer.cc @@ -437,7 +437,7 @@ void NchwcTransformerImpl::TransformConv(Node& node) { nchwc_conv_W_tensor_proto.add_dims(conv_W_dims[i]); } - nchwc_conv_W_arg = &graph_utils::AddInitializer(graph_, nchwc_conv_W_tensor_proto); + nchwc_conv_W_arg = &graph_utils::AddInitializerWithOrtValue(graph_, nchwc_conv_W_tensor_proto); filters_map->emplace(input_defs[1], nchwc_conv_W_arg); } @@ -464,7 +464,7 @@ void NchwcTransformerImpl::TransformConv(Node& node) { nchwc_conv_B_tensor_proto.add_dims(nchwc_output_channels); - nchwc_conv_B_arg = &graph_utils::AddInitializer(graph_, nchwc_conv_B_tensor_proto); + nchwc_conv_B_arg = &graph_utils::AddInitializerWithOrtValue(graph_, nchwc_conv_B_tensor_proto); aligned_biases_.emplace(input_defs[2], nchwc_conv_B_arg); } } @@ -580,7 +580,7 @@ Node& NchwcTransformerImpl::InsertReshape(NodeArg* input_arg, } shape_tensor_proto.add_dims(split_channels ? kNchwcDims + 1 : kNchwcDims); - shape_arg = &graph_utils::AddInitializer(graph_, shape_tensor_proto); + shape_arg = &graph_utils::AddInitializerWithOrtValue(graph_, shape_tensor_proto); } Node& reshape_node = graph_.AddNode(graph_.GenerateNodeName("Reshape"), @@ -896,7 +896,7 @@ void NchwcTransformerImpl::TransformBatchNormalization(Node& node) { nchwc_conv_W_tensor_proto.add_dims(1); nchwc_conv_W_tensor_proto.add_dims(1); - auto* nchwc_conv_W_arg = &graph_utils::AddInitializer(graph_, nchwc_conv_W_tensor_proto); + auto* nchwc_conv_W_arg = &graph_utils::AddInitializerWithOrtValue(graph_, nchwc_conv_W_tensor_proto); std::copy_n(bn_B.data(), channels, padded_buffer.data()); @@ -907,7 +907,7 @@ void NchwcTransformerImpl::TransformBatchNormalization(Node& node) { gsl::narrow(nchwc_channels) * sizeof(float)); nchwc_conv_B_tensor_proto.add_dims(nchwc_channels); - auto* nchwc_conv_B_arg = &graph_utils::AddInitializer(graph_, nchwc_conv_B_tensor_proto); + auto* nchwc_conv_B_arg = &graph_utils::AddInitializerWithOrtValue(graph_, nchwc_conv_B_tensor_proto); // Create the replacement node. std::string nchwc_node_name = graph_.GenerateNodeName(output_defs[0]->Name() + "_bn_nchwc"); diff --git a/onnxruntime/core/optimizer/qdq_transformer/avx2_weight_s8_to_u8.cc b/onnxruntime/core/optimizer/qdq_transformer/avx2_weight_s8_to_u8.cc index 42d27de632b91..d0c88886e5a06 100644 --- a/onnxruntime/core/optimizer/qdq_transformer/avx2_weight_s8_to_u8.cc +++ b/onnxruntime/core/optimizer/qdq_transformer/avx2_weight_s8_to_u8.cc @@ -130,22 +130,22 @@ static bool TryConvertDynamicQuantizeLSTM(Node& op_node, Graph& graph, const log weights_proto_u8.set_name(weight_tensor_proto->name() + "_s8_2_u8"); weights_proto_u8.mutable_dims()->CopyFrom(weight_tensor_proto->dims()); utils::SetRawDataInTensorProto(weights_proto_u8, w_temp.data(), static_cast(w_temp.size())); - input_defs[w_idx] = &graph_utils::AddInitializer(graph, weights_proto_u8); + input_defs[w_idx] = &graph_utils::AddInitializerWithOrtValue(graph, weights_proto_u8); ONNX_NAMESPACE::TensorProto weight_zp_proto_u8; QDQ::Int8TensorProto2Uint8(weight_zp_tensor_proto, weight_zp_proto_u8, graph, true); - input_defs[w_zp_idx] = &graph_utils::AddInitializer(graph, weight_zp_proto_u8); + input_defs[w_zp_idx] = &graph_utils::AddInitializerWithOrtValue(graph, weight_zp_proto_u8); ONNX_NAMESPACE::TensorProto r_proto_u8; r_proto_u8.set_data_type(ONNX_NAMESPACE::TensorProto_DataType_UINT8); r_proto_u8.set_name(r_tensor_proto->name() + "_s8_2_u8"); r_proto_u8.mutable_dims()->CopyFrom(r_tensor_proto->dims()); utils::SetRawDataInTensorProto(r_proto_u8, r_temp.data(), static_cast(r_temp.size())); - input_defs[r_idx] = &graph_utils::AddInitializer(graph, r_proto_u8); + input_defs[r_idx] = &graph_utils::AddInitializerWithOrtValue(graph, r_proto_u8); ONNX_NAMESPACE::TensorProto r_zp_proto_u8; QDQ::Int8TensorProto2Uint8(r_zp_tensor_proto, r_zp_proto_u8, graph, true); - input_defs[r_zp_idx] = &graph_utils::AddInitializer(graph, r_zp_proto_u8); + input_defs[r_zp_idx] = &graph_utils::AddInitializerWithOrtValue(graph, r_zp_proto_u8); return true; } diff --git a/onnxruntime/core/optimizer/qdq_transformer/qdq_s8_to_u8.cc b/onnxruntime/core/optimizer/qdq_transformer/qdq_s8_to_u8.cc index 828165e99d840..bf1c8949e3883 100644 --- a/onnxruntime/core/optimizer/qdq_transformer/qdq_s8_to_u8.cc +++ b/onnxruntime/core/optimizer/qdq_transformer/qdq_s8_to_u8.cc @@ -61,7 +61,7 @@ static bool QDQ_S8_to_U8(Graph& graph, Node& q_node, Node& dq_node) { zp_tensor_proto_u8.set_data_type(ONNX_NAMESPACE::TensorProto_DataType_UINT8); zp_tensor_proto_u8.set_name(graph.GenerateNodeArgName("qdq_s8_to_u8_zp_conversion")); utils::SetRawDataInTensorProto(zp_tensor_proto_u8, &q_zp_value, sizeof(uint8_t)); - NodeArg* zp_u8_arg = &graph_utils::AddInitializer(graph, zp_tensor_proto_u8); + NodeArg* zp_u8_arg = &graph_utils::AddInitializerWithOrtValue(graph, zp_tensor_proto_u8); auto q_output_node_arg_name = graph.GenerateNodeArgName("qdq_s8_to_u8_quant"); NodeArg* q_output_arg = &graph.GetOrCreateNodeArg(q_output_node_arg_name, nullptr); diff --git a/onnxruntime/core/optimizer/qdq_transformer/s8_to_u8.cc b/onnxruntime/core/optimizer/qdq_transformer/s8_to_u8.cc index f094f3c199f2a..101fedfb3e28f 100644 --- a/onnxruntime/core/optimizer/qdq_transformer/s8_to_u8.cc +++ b/onnxruntime/core/optimizer/qdq_transformer/s8_to_u8.cc @@ -43,12 +43,12 @@ bool ConvertS8WeightToU8(Graph& graph, Node& op_node, // The weights fits into S7, overflow is not a problem, no need to convert to U8 return false; } - input_defs[weights_idx] = &graph_utils::AddInitializer(graph, weights_proto_u8); + input_defs[weights_idx] = &graph_utils::AddInitializerWithOrtValue(graph, weights_proto_u8); // Convert weight zero point to uint8 ONNX_NAMESPACE::TensorProto weight_zp_proto_u8; Int8TensorProto2Uint8(weight_zp_tensor_proto, weight_zp_proto_u8, graph, true); - input_defs[weight_zp_idx] = &graph_utils::AddInitializer(graph, weight_zp_proto_u8); + input_defs[weight_zp_idx] = &graph_utils::AddInitializerWithOrtValue(graph, weight_zp_proto_u8); return true; } diff --git a/onnxruntime/core/optimizer/qdq_transformer/selectors_actions/qdq_actions.cc b/onnxruntime/core/optimizer/qdq_transformer/selectors_actions/qdq_actions.cc index 34d7ba3c79775..dddf80252f727 100644 --- a/onnxruntime/core/optimizer/qdq_transformer/selectors_actions/qdq_actions.cc +++ b/onnxruntime/core/optimizer/qdq_transformer/selectors_actions/qdq_actions.cc @@ -439,23 +439,23 @@ Status DQMatMulToMatMulNBitsAction::ProcessNewNode(Graph& graph, } } - auto weight_T_tp = utils::TensorToTensorProto(weight_dst, weight_dst_name, false); - auto scale_T_tp = utils::TensorToTensorProto(scale_dst, scale_dst_name, false); + auto weight_T_tp = utils::TensorToTensorProto(weight_dst, weight_dst_name, true); + auto scale_T_tp = utils::TensorToTensorProto(scale_dst, scale_dst_name, true); std::optional zp_T_tp; if (zp_dst) { - zp_T_tp.emplace(utils::TensorToTensorProto(*zp_dst, zp_dst_name, false)); + zp_T_tp.emplace(utils::TensorToTensorProto(*zp_dst, zp_dst_name, true)); } auto& input_defs = replacement_node.MutableInputDefs(); - input_defs.push_back(&graph_utils::AddInitializer(graph, weight_T_tp)); + input_defs.push_back(&graph_utils::AddInitializerWithOrtValue(graph, weight_T_tp, std::move(weight_dst))); replacement_node.MutableInputArgsCount().push_back(1); - input_defs.push_back(&graph_utils::AddInitializer(graph, scale_T_tp)); + input_defs.push_back(&graph_utils::AddInitializerWithOrtValue(graph, scale_T_tp, std::move(scale_dst))); replacement_node.MutableInputArgsCount().push_back(1); if (zp_T_tp) { - input_defs.push_back(&graph_utils::AddInitializer(graph, zp_T_tp.value())); + input_defs.push_back(&graph_utils::AddInitializerWithOrtValue(graph, zp_T_tp.value(), std::move(*zp_dst))); replacement_node.MutableInputArgsCount().push_back(1); } diff --git a/onnxruntime/core/optimizer/qdq_transformer/weight_bias_quantization.cc b/onnxruntime/core/optimizer/qdq_transformer/weight_bias_quantization.cc index c6898ca1da2e5..31cdc6e7fbc5c 100644 --- a/onnxruntime/core/optimizer/qdq_transformer/weight_bias_quantization.cc +++ b/onnxruntime/core/optimizer/qdq_transformer/weight_bias_quantization.cc @@ -170,14 +170,14 @@ Status WeightBiasQuantization::ApplyImpl(Graph& graph, bool& modified, int graph weight_scale_proto.set_name(graph.GenerateNodeArgName(node.Name() + "_weight_scale")); weight_scale_proto.set_data_type(ONNX_NAMESPACE::TensorProto_DataType_FLOAT); weight_scale_proto.mutable_float_data()->Add(scale); - weight_scale_arg = &graph_utils::AddInitializer(graph, weight_scale_proto); + weight_scale_arg = &graph_utils::AddInitializerWithOrtValue(graph, weight_scale_proto); // Weight zero point initializer. ONNX_NAMESPACE::TensorProto weight_zp_proto; weight_zp_proto.set_name(graph.GenerateNodeArgName(node.Name() + "_weight_zp")); weight_zp_proto.set_data_type(ONNX_NAMESPACE::TensorProto_DataType_INT8); weight_zp_proto.mutable_int32_data()->Add(static_cast(zp)); - NodeArg& weight_zp_arg = graph_utils::AddInitializer(graph, weight_zp_proto); + NodeArg& weight_zp_arg = graph_utils::AddInitializerWithOrtValue(graph, weight_zp_proto); // Q from float32 to int8. ONNX_NAMESPACE::TypeProto weight_q_type_proto; diff --git a/onnxruntime/core/optimizer/qdq_transformer/where_dummy_dq.cc b/onnxruntime/core/optimizer/qdq_transformer/where_dummy_dq.cc index 3eb3ee7e75c75..9bd91e7916ecb 100644 --- a/onnxruntime/core/optimizer/qdq_transformer/where_dummy_dq.cc +++ b/onnxruntime/core/optimizer/qdq_transformer/where_dummy_dq.cc @@ -119,9 +119,9 @@ Status WhereDummyDq::InsertDummyDQ(Node& node, Graph& graph, bool& modified, con } // Start editing the graph - NodeArg& dummy_data_arg = graph_utils::AddInitializer(graph, dummy_data_proto); - NodeArg& dummy_scale_arg = graph_utils::AddInitializer(graph, dummy_scale_proto); - NodeArg& dummy_zp_arg = graph_utils::AddInitializer(graph, dummy_zp_proto); + NodeArg& dummy_data_arg = graph_utils::AddInitializerWithOrtValue(graph, dummy_data_proto); + NodeArg& dummy_scale_arg = graph_utils::AddInitializerWithOrtValue(graph, dummy_scale_proto); + NodeArg& dummy_zp_arg = graph_utils::AddInitializerWithOrtValue(graph, dummy_zp_proto); ONNX_NAMESPACE::TypeProto dummy_dq_type_proto = utils::TypeProtoFromTensorProto(*const_node_data_proto); dummy_dq_type_proto.mutable_tensor_type()->set_elem_type(const_node_data_proto->data_type()); diff --git a/onnxruntime/core/optimizer/relu_clip_fusion.cc b/onnxruntime/core/optimizer/relu_clip_fusion.cc index 07902fde04930..494c646778d10 100644 --- a/onnxruntime/core/optimizer/relu_clip_fusion.cc +++ b/onnxruntime/core/optimizer/relu_clip_fusion.cc @@ -97,7 +97,7 @@ Status FuseReluClip::Apply(Graph& graph, Node& node, RewriteRuleEffect& rule_eff mutable_next_node->AddAttribute("min", 0.f); } else { // Add the initialized tensor to the graph - auto* replacement_min_nodearg = &graph_utils::AddInitializer(graph, replacement_min); + auto* replacement_min_nodearg = &graph_utils::AddInitializerWithOrtValue(graph, replacement_min); // Replace the input def at the appropriate index of the Clip node auto& mutable_input_defs = mutable_next_node->MutableInputDefs(); diff --git a/onnxruntime/core/optimizer/reshape_fusion.cc b/onnxruntime/core/optimizer/reshape_fusion.cc index 324905f953eec..daab9bba278aa 100644 --- a/onnxruntime/core/optimizer/reshape_fusion.cc +++ b/onnxruntime/core/optimizer/reshape_fusion.cc @@ -438,7 +438,7 @@ bool ReshapeFusion::Fuse_Subgraph(Node& reshape, Graph& graph, const logging::Lo shape_initializer_proto.add_dims(static_cast(shape_value.size())); shape_initializer_proto.set_data_type(ONNX_NAMESPACE::TensorProto_DataType_INT64); utils::SetRawDataInTensorProto(shape_initializer_proto, shape_value.data(), shape_value.size() * sizeof(int64_t)); - auto& new_node_arg = graph_utils::AddInitializer(graph, shape_initializer_proto); + auto& new_node_arg = graph_utils::AddInitializerWithOrtValue(graph, shape_initializer_proto); // Safely remove concat parent nodes which have only one output for (int i = 0; i < concat_input_count; ++i) { @@ -492,7 +492,7 @@ bool ReshapeFusion::FuseContiguousReshapes(Node& reshape, Graph& graph) { shape_initializer_proto.add_dims(static_cast(shape_value.size())); shape_initializer_proto.set_data_type(ONNX_NAMESPACE::TensorProto_DataType_INT64); utils::SetRawDataInTensorProto(shape_initializer_proto, shape_value.data(), shape_value.size() * sizeof(int64_t)); - NodeArg* shape_arg = &graph_utils::AddInitializer(graph, shape_initializer_proto); + NodeArg* shape_arg = &graph_utils::AddInitializerWithOrtValue(graph, shape_initializer_proto); Node& reshape_node = graph.AddNode(graph.GenerateNodeName(name + "_new_reshape"), "Reshape", "Reshape for " + name, {contiguous_reshapes[0].get().MutableInputDefs()[0], shape_arg}, {contiguous_reshapes.back().get().MutableOutputDefs()[0]}); diff --git a/onnxruntime/core/optimizer/stft_decomposition.cc b/onnxruntime/core/optimizer/stft_decomposition.cc index 5c09e5225ab9c..60ab064465f2f 100644 --- a/onnxruntime/core/optimizer/stft_decomposition.cc +++ b/onnxruntime/core/optimizer/stft_decomposition.cc @@ -46,7 +46,7 @@ NodeArg* AddInitializer(Graph& graph, const char* name, const int64_t (&shape)[T proto.add_dims(shape[i]); } utils::SetRawDataInTensorProto(proto, begin, element_count * sizeof(TDataType)); - return &graph_utils::AddInitializer(graph, proto); + return &graph_utils::AddInitializerWithOrtValue(graph, proto); } template @@ -225,8 +225,8 @@ Status STFTDecomposition::ApplyImpl(Graph& graph, bool& modified, int graph_leve } const int64_t weight_shape[] = {dft_unique_bins, 1, 1, dft_size}; - auto real_weights = AddInitializer(graph, "stft_real_conv_weights", weight_shape, real_weights_data.data()); - auto imaginary_weights = AddInitializer(graph, "stft_imaginary_conv_weights", weight_shape, imag_weights_data.data()); + auto* real_weights = AddInitializer(graph, "stft_real_conv_weights", weight_shape, real_weights_data.data()); + auto* imaginary_weights = AddInitializer(graph, "stft_imaginary_conv_weights", weight_shape, imag_weights_data.data()); const int64_t signal_reshaped[] = {batch_size, 1, 1, signal_length}; auto signal_shape = AddShapeInitializer(graph, "stft_signal_shape", signal_reshaped); diff --git a/onnxruntime/core/optimizer/transformer_memcpy.cc b/onnxruntime/core/optimizer/transformer_memcpy.cc index 46311303639ab..00b3dc4dd8b4e 100644 --- a/onnxruntime/core/optimizer/transformer_memcpy.cc +++ b/onnxruntime/core/optimizer/transformer_memcpy.cc @@ -433,9 +433,23 @@ bool TransformerMemcpyImpl::ProcessInitializers(const KernelRegistryManager& ker auto& new_def = graph_.GetOrCreateNodeArg(new_def_name, provider_def->TypeAsProto()); TensorProto new_tensor_proto = *tensor_proto; - *(new_tensor_proto.mutable_name()) = new_def_name; - - ORT_IGNORE_RETURN_VALUE(graph_utils::AddInitializer(graph_, new_tensor_proto)); + *(new_tensor_proto.mutable_name()) = std::move(new_def_name); + + // Query any OrtValue existing for the original initializer + // We are checking outer scope because GetInitializer is called with true, therefore, we potentially + // have references to parent graphs. + // We are doing this so the same OrtValue is re-used in subgraphs and no copies made for big items. + constexpr const bool check_outer_scope_true = true; + OrtValue ort_value; + // The initializer can be in memory with OrtValue or it can be a flatbuffer mapped. + if (utils::HasExternalDataInMemory(new_tensor_proto) && + graph_.GetOrtValueInitializer(name, ort_value, check_outer_scope_true)) { + // Re-use the same ort_value and proto that points to the same buffer + ORT_IGNORE_RETURN_VALUE(graph_utils::AddInitializerWithOrtValue(graph_, new_tensor_proto, + std::move(ort_value))); + } else { + ORT_IGNORE_RETURN_VALUE(graph_utils::AddInitializer(graph_, new_tensor_proto)); + } replacements.insert(std::make_pair(provider_def, &new_def)); } diff --git a/onnxruntime/core/optimizer/transpose_optimization/ort_optimizer_api_impl.cc b/onnxruntime/core/optimizer/transpose_optimization/ort_optimizer_api_impl.cc index 96c5ec8562a03..6a02ca3578da2 100644 --- a/onnxruntime/core/optimizer/transpose_optimization/ort_optimizer_api_impl.cc +++ b/onnxruntime/core/optimizer/transpose_optimization/ort_optimizer_api_impl.cc @@ -588,10 +588,10 @@ void ApiGraph::TransposeInitializer(std::string_view name, const std::vector& shape) { @@ -624,7 +624,7 @@ void ApiGraph::ReshapeInitializer(std::string_view name, const std::vector()->Reshape(new_shape); + } + + auto& new_node_arg = graph_utils::AddInitializerWithOrtValue(graph, new_tensor_proto, ort_value); graph_utils::ReplaceNodeWithInitializer(graph, node, new_node_arg); // Remove the Unsqueeze node and replace it with the initializer. diff --git a/onnxruntime/core/providers/shared_library/provider_api.h b/onnxruntime/core/providers/shared_library/provider_api.h index 27e9f82a43557..5be46cd480004 100644 --- a/onnxruntime/core/providers/shared_library/provider_api.h +++ b/onnxruntime/core/providers/shared_library/provider_api.h @@ -446,7 +446,7 @@ inline bool HasExternalDataInMemory(const ONNX_NAMESPACE::TensorProto& ten_proto } // namespace utils namespace graph_utils { -inline NodeArg& AddInitializerWithExternalData(Graph& graph, const ONNX_NAMESPACE::TensorProto& new_initializer) { +inline NodeArg& AddInitializerWithOrtValue(Graph& graph, const ONNX_NAMESPACE::TensorProto& new_initializer) { return g_host->GraphUtils__AddInitializerWithExternalData(graph, new_initializer); } inline void MakeInitializerCopyIfNotExist(const Graph& src_graph, Graph& dst_graph, const std::string& name, diff --git a/onnxruntime/core/session/inference_session.cc b/onnxruntime/core/session/inference_session.cc index e3291cdce62c5..14f0892687ad1 100644 --- a/onnxruntime/core/session/inference_session.cc +++ b/onnxruntime/core/session/inference_session.cc @@ -1421,29 +1421,6 @@ common::Status InferenceSession::TransformGraph(onnxruntime::Graph& graph, bool } } - // We choose to convert initializers into OrtValues before partitioning here so plug-in EPs could - // take advantage of the initializers being in OrtValue format and not to deal with protobuf. - // - // The initializers data is transferred to an OrtValue. The original TensorProto is replaced - // with a TensorProto that has the same data type, shape and name. However, its external data - // is used in a non-standard way. The location is set to a string constant utils::kTensorProtoMemoryAddressTag, - // The file offset is set to the address of the OrtValue's data buffer, and the length is set to the size of the - // OrtValue's data buffer. Because this external location is non-standard, onnx code can not handle it, so we choose - // to do it as late as possible but before the partitioning so type and shape inference accesses the initializers - // before they are converted to OrtValues. - // - // If any transformations are applied later, they would not introduce any in-memory initializers, - // type and shape inference would run only on any newly added nodes and any new initializers - // will be converted at session finalization time. - // - // The conversion is performed using the following steps (within ConvertInitializersIntoOrtValues()) - // constexpr const bool use_tensor_buffer_true = true; - // auto tensor_proto_to_add = utils::TensorToTensorProto(ort_value.Get(), tensor_proto.name(), - // use_tensor_buffer_true); - // ORT_RETURN_IF_ERROR(graph.ReplaceInitializedTensor(tensor_proto_to_add, ort_value)); - - ORT_RETURN_IF_ERROR_SESSIONID_(graph.ConvertInitializersIntoOrtValues()); - // Do partitioning based on execution providers' capabilities. ORT_RETURN_IF_ERROR_SESSIONID_(partitioner.Partition(graph, session_state_->GetMutableFuncMgr(), transform_layout_fn, session_options_.config_options, *session_logger_, diff --git a/onnxruntime/core/session/provider_bridge_ort.cc b/onnxruntime/core/session/provider_bridge_ort.cc index 40ab0de5abace..dfa05e7b45105 100644 --- a/onnxruntime/core/session/provider_bridge_ort.cc +++ b/onnxruntime/core/session/provider_bridge_ort.cc @@ -1433,7 +1433,7 @@ struct ProviderHostImpl : ProviderHost { NodeArg& GraphUtils__AddInitializerWithExternalData(Graph& graph, const ONNX_NAMESPACE::TensorProto& new_initializer) override { - return graph_utils::AddInitializerWithExternalData(graph, new_initializer); + return graph_utils::AddInitializerWithOrtValue(graph, new_initializer); } void GraphUtils__MakeInitializerCopyIfNotExist(const Graph& src_graph, Graph& dst_graph, diff --git a/onnxruntime/test/framework/allocation_planner_test.cc b/onnxruntime/test/framework/allocation_planner_test.cc index bcd6b62e649be..c3d8f2631feb4 100644 --- a/onnxruntime/test/framework/allocation_planner_test.cc +++ b/onnxruntime/test/framework/allocation_planner_test.cc @@ -1017,7 +1017,7 @@ TEST_F(PlannerTest, LocationPlanningForInitializersOnlyUsedInANestedSubgraph) { tensor.add_float_data(1.0f); tensor.set_data_type(TensorProto_DataType_FLOAT); tensor.set_name("init_data"); - graph_utils::AddInitializerWithExternalData(main_graph, tensor); + graph_utils::AddInitializerWithOrtValue(main_graph, tensor); // Main graph's inputs/outputs main_graph.SetInputs({&abs_data_in, &if_in}); @@ -1124,7 +1124,7 @@ TEST_F(PlannerTest, LocationPlanningForInitializersUsedOnDifferentDevicesInMainG tensor.add_int64_data(1); tensor.set_data_type(TensorProto_DataType_INT64); tensor.set_name("init_data"); - graph_utils::AddInitializerWithExternalData(main_graph, tensor); + graph_utils::AddInitializerWithOrtValue(main_graph, tensor); // Main graph's inputs/outputs main_graph.SetInputs({&abs_data_in, &if_in}); @@ -1549,7 +1549,7 @@ TEST_F(PlannerTest, ParaPlanCreation) { for (int i = 0; i < 64 * 3 * 7 * 7; ++i) conv_0_weight_tensor.add_float_data(0.234f); conv_0_weight_tensor.set_data_type(TensorProto_DataType_FLOAT); conv_0_weight_tensor.set_name("conv_0_weight"); - graph_utils::AddInitializerWithExternalData(main_graph, conv_0_weight_tensor); + graph_utils::AddInitializerWithOrtValue(main_graph, conv_0_weight_tensor); ONNX_NAMESPACE::TensorProto conv_1_weight_tensor; conv_1_weight_tensor.add_dims(64L); @@ -1559,7 +1559,7 @@ TEST_F(PlannerTest, ParaPlanCreation) { conv_1_weight_tensor.set_data_type(TensorProto_DataType_FLOAT); for (int i = 0; i < 64 * 64; ++i) conv_1_weight_tensor.add_float_data(1.017f); conv_1_weight_tensor.set_name("conv_1_weight"); - graph_utils::AddInitializerWithExternalData(main_graph, conv_1_weight_tensor); + graph_utils::AddInitializerWithOrtValue(main_graph, conv_1_weight_tensor); ONNX_NAMESPACE::TensorProto conv_2_weight_tensor; conv_2_weight_tensor.add_dims(64L); @@ -1569,7 +1569,7 @@ TEST_F(PlannerTest, ParaPlanCreation) { for (int i = 0; i < 64 * 64 * 3 * 3; ++i) conv_2_weight_tensor.add_float_data(2.317f); conv_2_weight_tensor.set_data_type(TensorProto_DataType_FLOAT); conv_2_weight_tensor.set_name("conv_2_weight"); - graph_utils::AddInitializerWithExternalData(main_graph, conv_2_weight_tensor); + graph_utils::AddInitializerWithOrtValue(main_graph, conv_2_weight_tensor); ONNX_NAMESPACE::TensorProto conv_3_weight_tensor; conv_3_weight_tensor.add_dims(256L); @@ -1579,7 +1579,7 @@ TEST_F(PlannerTest, ParaPlanCreation) { for (int i = 0; i < 256 * 64; ++i) conv_3_weight_tensor.add_float_data(1.256f); conv_3_weight_tensor.set_data_type(TensorProto_DataType_FLOAT); conv_3_weight_tensor.set_name("conv_3_weight"); - graph_utils::AddInitializerWithExternalData(main_graph, conv_3_weight_tensor); + graph_utils::AddInitializerWithOrtValue(main_graph, conv_3_weight_tensor); ONNX_NAMESPACE::TensorProto conv_4_weight_tensor; conv_4_weight_tensor.add_dims(256L); @@ -1589,7 +1589,7 @@ TEST_F(PlannerTest, ParaPlanCreation) { for (int i = 0; i < 256 * 64; ++i) conv_4_weight_tensor.add_float_data(1.913f); conv_4_weight_tensor.set_data_type(TensorProto_DataType_FLOAT); conv_4_weight_tensor.set_name("conv_4_weight"); - graph_utils::AddInitializerWithExternalData(main_graph, conv_4_weight_tensor); + graph_utils::AddInitializerWithOrtValue(main_graph, conv_4_weight_tensor); auto& conv_0_weight = main_graph.GetOrCreateNodeArg("conv_0_weight", &conv_0_weight_type); auto& conv_1_weight = main_graph.GetOrCreateNodeArg("conv_1_weight", &conv_1_weight_type); @@ -1602,35 +1602,35 @@ TEST_F(PlannerTest, ParaPlanCreation) { conv_0_bias_tensor.set_data_type(TensorProto_DataType_FLOAT); conv_0_bias_tensor.set_name("conv_0_bias"); for (int i = 0; i < 64; ++i) conv_0_bias_tensor.add_float_data(1.123f); - graph_utils::AddInitializerWithExternalData(main_graph, conv_0_bias_tensor); + graph_utils::AddInitializerWithOrtValue(main_graph, conv_0_bias_tensor); ONNX_NAMESPACE::TensorProto conv_1_bias_tensor; conv_1_bias_tensor.add_dims(64L); for (int i = 0; i < 64; ++i) conv_1_bias_tensor.add_float_data(2.234f); conv_1_bias_tensor.set_data_type(TensorProto_DataType_FLOAT); conv_1_bias_tensor.set_name("conv_1_bias"); - graph_utils::AddInitializerWithExternalData(main_graph, conv_1_bias_tensor); + graph_utils::AddInitializerWithOrtValue(main_graph, conv_1_bias_tensor); ONNX_NAMESPACE::TensorProto conv_2_bias_tensor; conv_2_bias_tensor.add_dims(64L); for (int i = 0; i < 64; ++i) conv_2_bias_tensor.add_float_data(0.121f); conv_2_bias_tensor.set_data_type(TensorProto_DataType_FLOAT); conv_2_bias_tensor.set_name("conv_2_bias"); - graph_utils::AddInitializerWithExternalData(main_graph, conv_2_bias_tensor); + graph_utils::AddInitializerWithOrtValue(main_graph, conv_2_bias_tensor); ONNX_NAMESPACE::TensorProto conv_3_bias_tensor; conv_3_bias_tensor.add_dims(256L); for (int i = 0; i < 256; ++i) conv_3_bias_tensor.add_float_data(1.201f); conv_3_bias_tensor.set_data_type(TensorProto_DataType_FLOAT); conv_3_bias_tensor.set_name("conv_3_bias"); - graph_utils::AddInitializerWithExternalData(main_graph, conv_3_bias_tensor); + graph_utils::AddInitializerWithOrtValue(main_graph, conv_3_bias_tensor); ONNX_NAMESPACE::TensorProto conv_4_bias_tensor; conv_4_bias_tensor.add_dims(256L); for (int i = 0; i < 256; ++i) conv_4_bias_tensor.add_float_data(0.897f); conv_4_bias_tensor.set_data_type(TensorProto_DataType_FLOAT); conv_4_bias_tensor.set_name("conv_4_bias"); - graph_utils::AddInitializerWithExternalData(main_graph, conv_4_bias_tensor); + graph_utils::AddInitializerWithOrtValue(main_graph, conv_4_bias_tensor); auto& conv_0_bias = main_graph.GetOrCreateNodeArg("conv_0_bias", &conv_0_bias_type); auto& conv_1_bias = main_graph.GetOrCreateNodeArg("conv_1_bias", &conv_1_bias_type); diff --git a/onnxruntime/test/framework/cuda/fence_cuda_test.cc b/onnxruntime/test/framework/cuda/fence_cuda_test.cc index 1553469c52df7..13e379f1dacfc 100644 --- a/onnxruntime/test/framework/cuda/fence_cuda_test.cc +++ b/onnxruntime/test/framework/cuda/fence_cuda_test.cc @@ -67,7 +67,7 @@ static common::Status LoadInferenceSessionFromModel(FenceCudaTestInferenceSessio tensor_proto.set_data_type(PROTO_DATATYPE); \ for (auto v : value) tensor_proto.PROTO_ADD_DATA(v); \ tensor_proto.set_name(name); \ - return graph_utils::AddInitializer(graph, tensor_proto); \ + return graph_utils::AddInitializerWithOrtValue(graph, tensor_proto); \ } CREATE_INITIALIZER_FUNC(float, TensorProto_DataType_FLOAT, add_float_data) diff --git a/onnxruntime/test/framework/session_state_test.cc b/onnxruntime/test/framework/session_state_test.cc index cdcd3c2327421..9bdc0898c81c1 100644 --- a/onnxruntime/test/framework/session_state_test.cc +++ b/onnxruntime/test/framework/session_state_test.cc @@ -311,35 +311,30 @@ TEST_P(SessionStateTestP, TestInitializerProcessing) { } } +#ifdef USE_CUDA // Test that we allocate memory for an initializer from non-arena memory even if we provide an arena-based allocator // if the relevant session option config flag is set TEST(SessionStateTest, TestInitializerMemoryAllocatedUsingNonArenaMemory) { - // For this test we need to enable the arena-based allocator. - if (!DoesCpuAllocatorSupportArenaUsage()) { - GTEST_SKIP() << "CPU allocator does not support arena usage."; - } - AllocatorPtr cpu_allocator = CPUAllocator::DefaultInstance(); - // Part 1: Feature turned ON (i.e.) allocate from non-arena memory - { - std::basic_ostringstream oss; - oss << ORT_TSTR("testdata/mul_1.onnx"); - Status status; - std::shared_ptr model; - ASSERT_TRUE((status = Model::Load(oss.str(), model, nullptr, DefaultLoggingManager().DefaultLogger())).IsOK()) - << status; - Graph& graph = model->MainGraph(); + const auto& default_logger = DefaultLoggingManager().DefaultLogger(); + auto setup_and_run_test = [&cpu_allocator, &default_logger](Model& model, bool use_device_allocator) -> AllocatorStats { + Graph& graph = model.MainGraph(); + DataTransferManager dtm; ExecutionProviders execution_providers; - CPUExecutionProviderInfo epi{true}; // use an arena-based allocator for this EP - status = execution_providers.Add(onnxruntime::kCpuExecutionProvider, std::make_unique(epi)); - ASSERT_TRUE(status.IsOK()) << status; - + auto tmp_cpu_execution_provider = DefaultCudaExecutionProvider(); + tmp_cpu_execution_provider->SetLogger(&default_logger); + EXPECT_STATUS_OK(dtm.RegisterDataTransfer(tmp_cpu_execution_provider->GetDataTransfer())); + EXPECT_STATUS_OK(execution_providers.Add(kCudaExecutionProvider, std::move(tmp_cpu_execution_provider))); + + // Make sure CPU allocator is registered + auto cpu_execution_provider = DefaultCpuExecutionProvider(); + cpu_execution_provider->SetLogger(&default_logger); + EXPECT_STATUS_OK(dtm.RegisterDataTransfer(cpu_execution_provider->GetDataTransfer())); + EXPECT_STATUS_OK(execution_providers.Add(kCpuExecutionProvider, std::move(cpu_execution_provider))); KernelRegistryManager krm; - status = krm.RegisterKernels(execution_providers); - ASSERT_TRUE(status.IsOK()) << status; + EXPECT_STATUS_OK(krm.RegisterKernels(execution_providers)); - DataTransferManager dtm; ExternalDataLoaderManager edlm; profiling::Profiler profiler; @@ -348,20 +343,23 @@ TEST(SessionStateTest, TestInitializerMemoryAllocatedUsingNonArenaMemory) { sess_options.execution_mode = ExecutionMode::ORT_SEQUENTIAL; sess_options.use_deterministic_compute = false; sess_options.enable_mem_reuse = true; - // disable allocating initialized tensor memory from the arena(by default it will be allocated by the arena) - ASSERT_STATUS_OK(sess_options.config_options.AddConfigEntry(kOrtSessionOptionsUseDeviceAllocatorForInitializers, - "1")); + + if (use_device_allocator) { + // disable allocating initialized tensor memory from the arena(by default it will be allocated by the arena) + EXPECT_STATUS_OK(sess_options.config_options.AddConfigEntry(kOrtSessionOptionsUseDeviceAllocatorForInitializers, + "1")); + } SessionState session_state(graph, execution_providers, nullptr, nullptr, dtm, edlm, - DefaultLoggingManager().DefaultLogger(), profiler, sess_options); + default_logger, profiler, sess_options); // Create GraphOptimizerRegistry instance for providing predefined graph optimizers and selection functions for EPs to lookup auto graph_optimizer_registry = std::make_unique(&sess_options, - execution_providers.Get(onnxruntime::kCpuExecutionProvider), - &DefaultLoggingManager().DefaultLogger()); + execution_providers.Get(kCudaExecutionProvider), + &default_logger); // Partition the graph GraphPartitioner partitioner(krm, execution_providers, std::move(graph_optimizer_registry)); - ASSERT_STATUS_OK(partitioner.Partition( + EXPECT_STATUS_OK(partitioner.Partition( graph, session_state.GetMutableFuncMgr(), [&cpu_allocator](Graph& graph, bool& modified, const IExecutionProvider& execution_provider, const layout_transformation::DebugGraphFn& debug_graph_fn) -> Status { @@ -369,95 +367,49 @@ TEST(SessionStateTest, TestInitializerMemoryAllocatedUsingNonArenaMemory) { cpu_allocator, debug_graph_fn); }, sess_options.config_options, - DefaultLoggingManager().DefaultLogger())); + default_logger)); - ASSERT_STATUS_OK(session_state.FinalizeSessionState(oss.str(), krm)); + EXPECT_STATUS_OK(session_state.FinalizeSessionState(model.ModelPath(), krm)); - // Fetch the CPU arena-allocator from the session state - OrtMemoryInfo mem_info(CPU, OrtArenaAllocator); + // Fetch the CUDA arena-allocator from the session state + OrtMemoryInfo mem_info(CUDA, OrtArenaAllocator); AllocatorPtr alloc = session_state.GetAllocator(mem_info); - ASSERT_TRUE(alloc != nullptr); + EXPECT_NE(alloc, nullptr); - // Get stats for the CPU arena-based allocator + // Get stats for the CUDA arena-based allocator AllocatorStats alloc_stats; static_cast(alloc.get())->GetStats(&alloc_stats); - // Assert that we have made 1 Reserve() call (for allocating memory for the sole initializer in the model) - ASSERT_EQ(alloc_stats.num_reserves, 1); - } + return alloc_stats; + }; - // Part 2: Feature turned OFF (i.e.) allocate from arena memory (default behavior) + const ORTCHAR_T* model_path = ORT_TSTR("testdata/mul_1.onnx"); + // Part 1: Feature turned ON (i.e.) allocate from non-arena memory { - std::basic_ostringstream oss; - oss << ORT_TSTR("testdata/mul_1.onnx"); - Status status; std::shared_ptr model; - ASSERT_TRUE((status = Model::Load(oss.str(), model, nullptr, DefaultLoggingManager().DefaultLogger())).IsOK()) - << status; - Graph& graph = model->MainGraph(); + ASSERT_STATUS_OK(Model::Load(model_path, model, nullptr, default_logger)); - ExecutionProviders execution_providers; - CPUExecutionProviderInfo epi{true}; // use an arena-based allocator for this EP - status = execution_providers.Add(onnxruntime::kCpuExecutionProvider, std::make_unique(epi)); - ASSERT_TRUE(status.IsOK()) << status; + auto alloc_stats = setup_and_run_test(*model, /*use_device_allocator=*/true); - KernelRegistryManager krm; - status = krm.RegisterKernels(execution_providers); - ASSERT_TRUE(status.IsOK()) << status; - - DataTransferManager dtm; - ExternalDataLoaderManager edlm; - profiling::Profiler profiler; - - SessionOptions sess_options; - sess_options.enable_mem_pattern = false; - sess_options.execution_mode = ExecutionMode::ORT_SEQUENTIAL; - sess_options.use_deterministic_compute = false; - sess_options.enable_mem_reuse = true; - - SessionState session_state(graph, execution_providers, nullptr, nullptr, dtm, edlm, - DefaultLoggingManager().DefaultLogger(), profiler, sess_options); - - // Create GraphOptimizerRegistry instance for providing predefined graph optimizers and selection functions for EPs to lookup - auto graph_optimizer_registry = std::make_unique(&sess_options, - execution_providers.Get(onnxruntime::kCpuExecutionProvider), - &DefaultLoggingManager().DefaultLogger()); - - // Partition the graph - GraphPartitioner partitioner(krm, execution_providers, std::move(graph_optimizer_registry)); - ASSERT_STATUS_OK(partitioner.Partition( - graph, session_state.GetMutableFuncMgr(), - [&cpu_allocator](Graph& graph, bool& modified, - const IExecutionProvider& execution_provider, - const layout_transformation::DebugGraphFn& debug_graph_fn) -> Status { - return layout_transformation::TransformLayoutForEP( - graph, modified, execution_provider, cpu_allocator, debug_graph_fn); - }, - sess_options.config_options, - DefaultLoggingManager().DefaultLogger())); - - // Finalize the session state - ASSERT_STATUS_OK(session_state.FinalizeSessionState(oss.str(), krm)); + // Assert that we have made 1 Reserve() call (for allocating memory for the sole initializer in the model) + ASSERT_EQ(1, alloc_stats.num_reserves); + } - // Fetch the CPU arena-allocator from the session state - OrtMemoryInfo mem_info(CPU, OrtArenaAllocator); - AllocatorPtr alloc = session_state.GetAllocator(mem_info); - ASSERT_TRUE(alloc != nullptr); + // Part 2: Feature turned OFF (i.e.) allocate from arena memory (default behavior) + { + std::shared_ptr model; + ASSERT_STATUS_OK(Model::Load(model_path, model, nullptr, default_logger)); - // Get stats for the CPU arena-based allocator - AllocatorStats alloc_stats; - static_cast(alloc.get())->GetStats(&alloc_stats); + auto alloc_stats = setup_and_run_test(*model, /*use_device_allocator=*/false); - // Assert that we have made no Reserve() calls - ASSERT_EQ(alloc_stats.num_reserves, 0); + // One reserve call should have been made (for allocating memory for the sole initializer in the model) + ASSERT_EQ(1, alloc_stats.num_reserves); - // Assert to ensure an allocation was made for the initializer through the arena allocator (Alloc() was invoked) - ASSERT_EQ(alloc_stats.num_allocs, 1); + // This counter comes from Reserve(). The actual call for arena based allocator went to StreamAwareArena instance + ASSERT_EQ(1, alloc_stats.num_allocs); } } -#ifdef USE_CUDA - namespace { using ParitionVerifierFn = std::function; diff --git a/onnxruntime/test/ir/graph_test.cc b/onnxruntime/test/ir/graph_test.cc index 7371ad5cf0ded..6a3f2f974b9f5 100644 --- a/onnxruntime/test/ir/graph_test.cc +++ b/onnxruntime/test/ir/graph_test.cc @@ -2808,11 +2808,6 @@ TEST_F(GraphTest, ShapeInferenceAfterInitializerExternalization) { // First resolve should succeed ASSERT_STATUS_OK(graph.Resolve()); - // Now trigger the in-memory externalization - // This converts initializers > 127 bytes to OrtValues with external data references - Status convert_status = graph.ConvertInitializersIntoOrtValues(); - ASSERT_TRUE(convert_status.IsOK()) << "ConvertInitializersIntoOrtValues failed: " << convert_status.ErrorMessage(); - // Check if the initializer was actually externalized const ONNX_NAMESPACE::TensorProto* initializer_after = nullptr; ASSERT_TRUE(graph.GetInitializedTensor("split_sizes", initializer_after)); diff --git a/onnxruntime/test/providers/tensorrt/tensorrt_basic_test.cc b/onnxruntime/test/providers/tensorrt/tensorrt_basic_test.cc index a746493d779f8..6a6545c68cb4f 100644 --- a/onnxruntime/test/providers/tensorrt/tensorrt_basic_test.cc +++ b/onnxruntime/test/providers/tensorrt/tensorrt_basic_test.cc @@ -299,7 +299,9 @@ void RunWithOneSessionMultiThreadsInference(PathString model_name, std::string s ASSERT_TRUE(HasCacheFileWithPrefix(params.trt_engine_cache_prefix)); } -TEST(TensorrtExecutionProviderTest, SessionCreationWithMultiThreadsAndInferenceWithMultiThreads) { +// The test is disabled due to the issue described at +// https://github.com/microsoft/onnxruntime/issues/26366 +TEST(TensorrtExecutionProviderTest, DISABLED_SessionCreationWithMultiThreadsAndInferenceWithMultiThreads) { std::vector threads; PathString model_name = ORT_TSTR("trt_execution_provider_multithreading_test.onnx"); std::string graph_name = "multithreading_test"; diff --git a/onnxruntime/test/shared_lib/test_inference.cc b/onnxruntime/test/shared_lib/test_inference.cc index f2a7ee71a363a..c4a92e959b273 100644 --- a/onnxruntime/test/shared_lib/test_inference.cc +++ b/onnxruntime/test/shared_lib/test_inference.cc @@ -3486,7 +3486,7 @@ TEST(CApiTest, TestSharedAllocators) { ASSERT_TRUE(num_allocations == 6); size_t num_reserve_allocations = custom_allocator.NumReserveAllocations(); - ASSERT_TRUE(num_reserve_allocations == 1); + ASSERT_EQ(3, num_reserve_allocations); // Ensure that there was no leak custom_allocator.LeakCheck(); diff --git a/orttraining/orttraining/core/optimizer/conv1d_replacement.cc b/orttraining/orttraining/core/optimizer/conv1d_replacement.cc index ff220fcb067b8..56e4cc273b1df 100644 --- a/orttraining/orttraining/core/optimizer/conv1d_replacement.cc +++ b/orttraining/orttraining/core/optimizer/conv1d_replacement.cc @@ -121,7 +121,7 @@ void Conv1dToMatmul(Graph& graph, Node& conv, const std::string transformer_name initializer_proto.set_data_type(ONNX_NAMESPACE::TensorProto_DataType_INT64); InlinedVector initializer_proto_value{weight_squeeze_axis}; initializer_proto.set_raw_data(initializer_proto_value.data(), initializer_proto_value.size() * sizeof(int64_t)); - auto& axes_input = graph_utils::AddInitializer(graph, initializer_proto); + auto& axes_input = graph_utils::AddInitializerWithOrtValue(graph, initializer_proto); // Squeeze node doesn't have opschema here, so we need to set input args count manually weight_squeeze.MutableInputArgsCount().resize(2); graph_utils::AddNodeInput(weight_squeeze, 1, axes_input); diff --git a/orttraining/orttraining/core/optimizer/megatron_transformer.cc b/orttraining/orttraining/core/optimizer/megatron_transformer.cc index 7c429ae5cb643..837820ef2f9a1 100644 --- a/orttraining/orttraining/core/optimizer/megatron_transformer.cc +++ b/orttraining/orttraining/core/optimizer/megatron_transformer.cc @@ -453,15 +453,15 @@ Status MegatronTransformer::TransformGPT2MLP(Graph& graph, bool& modified, return skip_status; } - NodeArg& a_weight_partition_arg = graph_utils::AddInitializer(graph, a_weight_initializer_partition); + NodeArg& a_weight_partition_arg = graph_utils::AddInitializerWithOrtValue(graph, a_weight_initializer_partition); graph_utils::ReplaceNodeInput(node, 1, a_weight_partition_arg); updated_weight_names_.insert({a_weight_arg->Name(), a_weight_partition_arg.Name()}); - NodeArg& a_bias_partition_arg = graph_utils::AddInitializer(graph, a_bias_initializer_partition); + NodeArg& a_bias_partition_arg = graph_utils::AddInitializerWithOrtValue(graph, a_bias_initializer_partition); graph_utils::ReplaceNodeInput(add_node, 1, a_bias_partition_arg); updated_weight_names_.insert({b_weight_arg->Name(), a_bias_partition_arg.Name()}); - NodeArg& b_weight_partition_arg = graph_utils::AddInitializer(graph, b_weight_initializer_partition); + NodeArg& b_weight_partition_arg = graph_utils::AddInitializerWithOrtValue(graph, b_weight_initializer_partition); graph_utils::ReplaceNodeInput(matmul2_node, 1, b_weight_partition_arg); updated_weight_names_.insert({a_bias_arg->Name(), b_weight_partition_arg.Name()}); @@ -600,15 +600,15 @@ Status MegatronTransformer::TransformBARTMLP(Graph& graph, bool& modified, return skip_status; } - NodeArg& dense_wi_weight_partition_arg = graph_utils::AddInitializer(graph, dense_wi_weight_initializer_partition); + NodeArg& dense_wi_weight_partition_arg = graph_utils::AddInitializerWithOrtValue(graph, dense_wi_weight_initializer_partition); graph_utils::ReplaceNodeInput(*second_op, 0, dense_wi_weight_partition_arg); updated_weight_names_.insert({dense_wi_weight_arg->Name(), dense_wi_weight_partition_arg.Name()}); - NodeArg& dense_wi_bias_partition_arg = graph_utils::AddInitializer(graph, dense_wi_bias_initializer_partition); + NodeArg& dense_wi_bias_partition_arg = graph_utils::AddInitializerWithOrtValue(graph, dense_wi_bias_initializer_partition); graph_utils::ReplaceNodeInput(biasgelu_node, 1, dense_wi_bias_partition_arg); updated_weight_names_.insert({dense_wi_bias_arg->Name(), dense_wi_bias_partition_arg.Name()}); - NodeArg& dense_wo_weight_partition_arg = graph_utils::AddInitializer(graph, dense_wo_weight_initializer_partition); + NodeArg& dense_wo_weight_partition_arg = graph_utils::AddInitializerWithOrtValue(graph, dense_wo_weight_initializer_partition); graph_utils::ReplaceNodeInput(*transpose_op_ptr, 0, dense_wo_weight_partition_arg); updated_weight_names_.insert({dense_wo_weight_arg->Name(), dense_wo_weight_partition_arg.Name()}); @@ -814,15 +814,15 @@ Status MegatronTransformer::TransformGPT2Attention(Graph& graph, bool& modified, [](Node* node_ptr) { return node_ptr != nullptr; }); // Replace by the partition weights. - NodeArg& qkv_weight_partition_arg = graph_utils::AddInitializer(graph, qkv_weight_initializer_partition); + NodeArg& qkv_weight_partition_arg = graph_utils::AddInitializerWithOrtValue(graph, qkv_weight_initializer_partition); graph_utils::ReplaceNodeInput(node, 1, qkv_weight_partition_arg); updated_weight_names_.insert({qkv_weight_arg->Name(), qkv_weight_partition_arg.Name()}); - NodeArg& qkv_bias_partition_arg = graph_utils::AddInitializer(graph, qkv_bias_initializer_partition); + NodeArg& qkv_bias_partition_arg = graph_utils::AddInitializerWithOrtValue(graph, qkv_bias_initializer_partition); graph_utils::ReplaceNodeInput(add_node, 1, qkv_bias_partition_arg); updated_weight_names_.insert({qkv_bias_arg->Name(), qkv_bias_partition_arg.Name()}); - NodeArg& dense_weight_partition_arg = graph_utils::AddInitializer(graph, dense_weight_initializer_partition); + NodeArg& dense_weight_partition_arg = graph_utils::AddInitializerWithOrtValue(graph, dense_weight_initializer_partition); graph_utils::ReplaceNodeInput(matmul_node, 1, dense_weight_partition_arg); updated_weight_names_.insert({dense_weight_arg->Name(), dense_weight_partition_arg.Name()}); @@ -849,7 +849,7 @@ Status MegatronTransformer::TransformGPT2Attention(Graph& graph, bool& modified, val_partition.insert(val_partition.end(), val, val + size); val_partition[2] /= horizontal_parallel_size_; tensor_partition.set_raw_data(val_partition.data(), size * sizeof(int64_t)); - NodeArg& node_arg_partition = graph_utils::AddInitializer(graph, tensor_partition); + NodeArg& node_arg_partition = graph_utils::AddInitializerWithOrtValue(graph, tensor_partition); graph_utils::ReplaceNodeInput(*node_ptr, 1, node_arg_partition); graph.RemoveInitializedTensor(shape_arg->Name()); } @@ -1130,7 +1130,7 @@ Status MegatronTransformer::TransformBARTAttention(Graph& graph, bool& modified, size_t i = 0; for (auto trans_ptr : weight_transpose_node_ptrs) { auto weight_name = trans_ptr->MutableInputDefs()[0]->Name(); - NodeArg& qkv_weight_partition_arg = graph_utils::AddInitializer(graph, qkv_weight_initializer_partitions[i]); + NodeArg& qkv_weight_partition_arg = graph_utils::AddInitializerWithOrtValue(graph, qkv_weight_initializer_partitions[i]); graph_utils::ReplaceNodeInput(*trans_ptr, 0, qkv_weight_partition_arg); graph.RemoveInitializedTensor(weight_name); updated_weight_names_.insert({weight_name, qkv_weight_partition_arg.Name()}); @@ -1139,14 +1139,14 @@ Status MegatronTransformer::TransformBARTAttention(Graph& graph, bool& modified, i = 0; for (auto add_ptr : bias_add_node_ptrs) { auto bias_name = add_ptr->MutableInputDefs()[1]->Name(); - NodeArg& qkv_bias_partition_arg = graph_utils::AddInitializer(graph, qkv_bias_initializer_partitions[i]); + NodeArg& qkv_bias_partition_arg = graph_utils::AddInitializerWithOrtValue(graph, qkv_bias_initializer_partitions[i]); graph_utils::ReplaceNodeInput(*add_ptr, 1, qkv_bias_partition_arg); graph.RemoveInitializedTensor(bias_name); updated_weight_names_.insert({bias_name, qkv_bias_partition_arg.Name()}); i++; } - NodeArg& dense_weight_partition_arg = graph_utils::AddInitializer(graph, dense_weight_initializer_partition); + NodeArg& dense_weight_partition_arg = graph_utils::AddInitializerWithOrtValue(graph, dense_weight_initializer_partition); graph_utils::ReplaceNodeInput(*last_transpose, 0, dense_weight_partition_arg); graph.RemoveInitializedTensor(dense_weight_arg->Name()); updated_weight_names_.insert({dense_weight_arg->Name(), dense_weight_partition_arg.Name()}); @@ -1178,7 +1178,7 @@ Status MegatronTransformer::TransformBARTAttention(Graph& graph, bool& modified, val_partition.insert(val_partition.end(), val, val + size); val_partition[idx] /= horizontal_parallel_size_; tensor_partition.set_raw_data(val_partition.data(), size * sizeof(int64_t)); - NodeArg& node_arg_partition = graph_utils::AddInitializer(graph, tensor_partition); + NodeArg& node_arg_partition = graph_utils::AddInitializerWithOrtValue(graph, tensor_partition); graph_utils::ReplaceNodeInput(*node_ptr, 1, node_arg_partition); graph.RemoveInitializedTensor(shape_arg->Name()); } diff --git a/orttraining/orttraining/core/optimizer/qdq_fusion.cc b/orttraining/orttraining/core/optimizer/qdq_fusion.cc index 42720dbbb11e5..6219d1cfafae1 100644 --- a/orttraining/orttraining/core/optimizer/qdq_fusion.cc +++ b/orttraining/orttraining/core/optimizer/qdq_fusion.cc @@ -45,7 +45,7 @@ int ReplaceOrCreateZeroPointInitializer(Graph& graph, Node& quantize_node) { // Since the quantize node has the zero point initializer input, replace it graph_utils::ReplaceNodeInput(quantize_node, 2, - graph_utils::AddInitializer(graph, zero_point_tensor_float)); + graph_utils::AddInitializerWithOrtValue(graph, zero_point_tensor_float)); } else { // The quantize node does not have the zero point optional input. // Create the zero point initializer to be 0. @@ -55,7 +55,7 @@ int ReplaceOrCreateZeroPointInitializer(Graph& graph, Node& quantize_node) { // Since the input did not exist, add the newly created initializer as an input graph_utils::AddNodeInput(quantize_node, 2, - graph_utils::AddInitializer(graph, zero_point_tensor_float)); + graph_utils::AddInitializerWithOrtValue(graph, zero_point_tensor_float)); } return zero_point_type; diff --git a/orttraining/orttraining/core/optimizer/sce_loss_grad_bias_fusion.cc b/orttraining/orttraining/core/optimizer/sce_loss_grad_bias_fusion.cc index 84bf715c7c85a..3ab1636460adf 100644 --- a/orttraining/orttraining/core/optimizer/sce_loss_grad_bias_fusion.cc +++ b/orttraining/orttraining/core/optimizer/sce_loss_grad_bias_fusion.cc @@ -83,7 +83,7 @@ Status SceLossGradBiasFusion::ApplyImpl(Graph& graph, bool& modified, int graph_ ignore_index_initializer_proto.set_name(graph.GenerateNodeArgName("sce_grad_ignore_index")); ignore_index_initializer_proto.set_data_type(ONNX_NAMESPACE::TensorProto_DataType_INT64); ignore_index_initializer_proto.add_int64_data(static_cast(-1)); - new_scegrad_node_inputs.emplace_back(&graph_utils::AddInitializer(graph, ignore_index_initializer_proto)); + new_scegrad_node_inputs.emplace_back(&graph_utils::AddInitializerWithOrtValue(graph, ignore_index_initializer_proto)); } new_scegrad_node_inputs.emplace_back(bias_def); if (!p_reshape) { From fc3bc097c941c812f481cff42594f2da1ae79097 Mon Sep 17 00:00:00 2001 From: Adrian Lizarraga Date: Thu, 30 Oct 2025 10:58:08 -0700 Subject: [PATCH 24/33] Fix memleak due to improper deletion of onnx::TypeProto wrapper in provider-bridge API (#26448) ### Description There is a memory leak whenever an EP uses the provider-bridge API to create a `std::unique_ptr`. The `onnx::TypeProto` is not properly deleted due to a missing `operator delete()` override for the `TypeProto` wrapper class. This delete operator override is necessary because the onnx library may use custom allocators. Affected EPs: Run `git grep -rn "TypeProto::Create()" onnxruntime/core/providers/` - QNN EP: Happens when QNN EP creates an EPContext model. To reproduce, run the `onnxruntime_provider_tests` with `--gtest_filter=*ContextBinary*`. - https://github.com/microsoft/onnxruntime/blob/860d0853a6eefdf19e21b0e9982bde2ffbc8a65d/onnxruntime/core/providers/qnn/builder/onnx_ctx_model_helper.cc#L73. - OpenVINO EP: Happens during QDQ stripping: - https://github.com/microsoft/onnxruntime/blob/860d0853a6eefdf19e21b0e9982bde2ffbc8a65d/onnxruntime/core/providers/openvino/qdq_transformations/qdq_stripping.cc#L76 - https://github.com/microsoft/onnxruntime/blob/860d0853a6eefdf19e21b0e9982bde2ffbc8a65d/onnxruntime/core/providers/openvino/qdq_transformations/qdq_stripping.cc#L473 - https://github.com/microsoft/onnxruntime/blob/860d0853a6eefdf19e21b0e9982bde2ffbc8a65d/onnxruntime/core/providers/openvino/qdq_transformations/qdq_stripping.cc#L654 - NV EP: - https://github.com/microsoft/onnxruntime/blob/860d0853a6eefdf19e21b0e9982bde2ffbc8a65d/onnxruntime/core/providers/nv_tensorrt_rtx/nv_execution_provider_helper.cc#L213 - VitisAI EP: - https://github.com/microsoft/onnxruntime/blob/860d0853a6eefdf19e21b0e9982bde2ffbc8a65d/onnxruntime/core/providers/vitisai/imp/node_arg.cc#L94 ### Motivation and Context --- onnxruntime/core/providers/shared_library/provider_interfaces.h | 1 + .../core/providers/shared_library/provider_wrappedtypes.h | 1 + onnxruntime/core/session/provider_bridge_ort.cc | 1 + 3 files changed, 3 insertions(+) diff --git a/onnxruntime/core/providers/shared_library/provider_interfaces.h b/onnxruntime/core/providers/shared_library/provider_interfaces.h index 7e56886b1f558..f1d545d0c6b17 100644 --- a/onnxruntime/core/providers/shared_library/provider_interfaces.h +++ b/onnxruntime/core/providers/shared_library/provider_interfaces.h @@ -381,6 +381,7 @@ struct ProviderHost { // TypeProto virtual std::unique_ptr TypeProto__construct() = 0; + virtual void TypeProto__operator_delete(ONNX_NAMESPACE::TypeProto* p) = 0; virtual void TypeProto__CopyFrom(ONNX_NAMESPACE::TypeProto* p, const ONNX_NAMESPACE::TypeProto* other) = 0; virtual bool TypeProto__has_tensor_type(const ONNX_NAMESPACE::TypeProto* p) = 0; virtual const ONNX_NAMESPACE::TypeProto_Tensor& TypeProto__tensor_type(const ONNX_NAMESPACE::TypeProto* p) = 0; diff --git a/onnxruntime/core/providers/shared_library/provider_wrappedtypes.h b/onnxruntime/core/providers/shared_library/provider_wrappedtypes.h index cdbd0c074f443..c7400c276f912 100644 --- a/onnxruntime/core/providers/shared_library/provider_wrappedtypes.h +++ b/onnxruntime/core/providers/shared_library/provider_wrappedtypes.h @@ -366,6 +366,7 @@ struct TypeProto_Sequence final { struct TypeProto final { static std::unique_ptr Create() { return g_host->TypeProto__construct(); } + static void operator delete(void* p) { g_host->TypeProto__operator_delete(reinterpret_cast(p)); } bool has_tensor_type() const { return g_host->TypeProto__has_tensor_type(this); } const TypeProto_Tensor& tensor_type() const { return g_host->TypeProto__tensor_type(this); } diff --git a/onnxruntime/core/session/provider_bridge_ort.cc b/onnxruntime/core/session/provider_bridge_ort.cc index dfa05e7b45105..c6f65fe62ef94 100644 --- a/onnxruntime/core/session/provider_bridge_ort.cc +++ b/onnxruntime/core/session/provider_bridge_ort.cc @@ -516,6 +516,7 @@ struct ProviderHostImpl : ProviderHost { // TypeProto (wrapped) std::unique_ptr TypeProto__construct() override { return std::make_unique(); } + void TypeProto__operator_delete(ONNX_NAMESPACE::TypeProto* p) override { delete p; } void TypeProto__CopyFrom(ONNX_NAMESPACE::TypeProto* p, const ONNX_NAMESPACE::TypeProto* other) override { p->CopyFrom(*other); } bool TypeProto__has_tensor_type(const ONNX_NAMESPACE::TypeProto* p) override { return p->has_tensor_type(); } const ONNX_NAMESPACE::TypeProto_Tensor& TypeProto__tensor_type(const ONNX_NAMESPACE::TypeProto* p) override { return p->tensor_type(); } From ec9b8fef019909534ddf744404877ae45be66424 Mon Sep 17 00:00:00 2001 From: Adrian Lizarraga Date: Fri, 31 Oct 2025 14:43:43 -0700 Subject: [PATCH 25/33] Fix early check that prevents a compiled model from being overwritten (#26439) ### Description Fixes https://github.com/microsoft/onnxruntime/issues/26294 When using the old model compilation approach (session option configuration), ORT should verify that the generated output model does not already exist. Importantly, this check should be done _before_ calling an EP's compile() method. This PR fixes this check, which was unintentionally disabled by a [previous PR.](https://github.com/microsoft/onnxruntime/pull/25455). Note that this check also (correctly) happens _after_ calling the EP's compile() method, but it is better to catch it early if we can. ### Motivation and Context Fixes a regression in the older compilation workflow. --- .../core/framework/ep_context_options.cc | 12 ++-- onnxruntime/core/session/utils.cc | 29 +++++++--- onnxruntime/test/autoep/test_execution.cc | 57 +++++++++++++++++++ 3 files changed, 83 insertions(+), 15 deletions(-) diff --git a/onnxruntime/core/framework/ep_context_options.cc b/onnxruntime/core/framework/ep_context_options.cc index abfd3cf89cecf..e922438fa20bc 100644 --- a/onnxruntime/core/framework/ep_context_options.cc +++ b/onnxruntime/core/framework/ep_context_options.cc @@ -15,15 +15,15 @@ namespace epctx { ModelGenOptions::ModelGenOptions() = default; +// This constructor is only used when using the older compilation approach that uses +// session configuration options to enable and configure compilation (i.e., not OrtCompileApi). +// This initializes ModelGenOptions from the session config options. ModelGenOptions::ModelGenOptions(const ConfigOptions& config_options) { enable = config_options.GetConfigOrDefault(kOrtSessionOptionEpContextEnable, "0") == "1"; - std::string output_model_path = config_options.GetConfigOrDefault(kOrtSessionOptionEpContextFilePath, ""); - if (!output_model_path.empty()) { - output_model_location = std::filesystem::path(output_model_path); - } else { - output_model_location = std::monostate{}; - } + // Note: the older compilation approach only supports compiling to an output file. + output_model_location = std::filesystem::path( + config_options.GetConfigOrDefault(kOrtSessionOptionEpContextFilePath, "")); std::string external_initializers_file_path = config_options.GetConfigOrDefault( kOrtSessionOptionsEpContextModelExternalInitializersFileName, ""); diff --git a/onnxruntime/core/session/utils.cc b/onnxruntime/core/session/utils.cc index 4a50bab5e8cbc..6189e6ca7f012 100644 --- a/onnxruntime/core/session/utils.cc +++ b/onnxruntime/core/session/utils.cc @@ -134,18 +134,29 @@ static OrtStatus* CreateSessionAndLoadModelImpl(_In_ const OrtSessionOptions* op bool load_config_from_model = os_env.GetEnvironmentVar(inference_session_utils::kOrtLoadConfigFromModelEnvVar) == "1"; - // If ep.context_enable is set, then ep.context_file_path is expected, otherwise ORT don't know where to generate the _ctx.onnx file + // Check EPContext model generation options when the input model is loaded from memory (no input model path). if (options && model_path == nullptr) { epctx::ModelGenOptions ep_ctx_gen_options = options->value.GetEpContextGenerationOptions(); - // This is checked by the OrtCompileApi's CompileModel() function, but we check again here in case - // the user used the older SessionOptions' configuration entries to generate a compiled model. - if (ep_ctx_gen_options.enable && !ep_ctx_gen_options.HasOutputModelLocation()) { - return OrtApis::CreateStatus(ORT_FAIL, - "Inference session was configured with EPContext model generation enabled but " - "without a valid location (e.g., file or buffer) for the output model. " - "Please specify a valid ep.context_file_path via SessionOption configs " - "or use the OrtCompileApi to compile a model to a file or buffer."); + if (ep_ctx_gen_options.enable) { + auto* output_model_path = ep_ctx_gen_options.TryGetOutputModelPath(); + + // If the user does not provide an output model location, ORT normally generates an output model file path based + // on the input model's path (i.e., replace ".onnx" with "_ctx.onnx"). However, because there is no input model + // path, we require the application to explicitly set the output model's location. + // + // Note: This is checked by the OrtCompileApi's CompileModel() function, but we check again here in case + // the user used the older SessionOptions' configuration entries to generate a compiled model. + if (!ep_ctx_gen_options.HasOutputModelLocation() || // No output model location (file, buffer, etc.) + (output_model_path != nullptr && output_model_path->empty()) // Has an output file, but it is empty. + ) { + return OrtApis::CreateStatus(ORT_FAIL, + "Inference session with a model loaded from bytes was configured with EPContext " + "model generation enabled but without a valid location (e.g., file or buffer) " + "for the output model. Please specify a valid ep.context_file_path via " + "SessionOption configs or use the OrtCompileApi to compile a model to a " + "file or buffer."); + } } } diff --git a/onnxruntime/test/autoep/test_execution.cc b/onnxruntime/test/autoep/test_execution.cc index 3bca932623dec..42e3aa742d9f6 100644 --- a/onnxruntime/test/autoep/test_execution.cc +++ b/onnxruntime/test/autoep/test_execution.cc @@ -10,6 +10,7 @@ #include #include "core/session/onnxruntime_cxx_api.h" +#include "core/session/onnxruntime_session_options_config_keys.h" #include "test/autoep/test_autoep_utils.h" #include "test/shared_lib/utils.h" @@ -184,6 +185,62 @@ TEST(OrtEpLibrary, PluginEp_VirtGpu_GenEpContextModel) { ASSERT_TRUE(std::filesystem::exists(output_model_file)); } } + +// Uses the original compiling approach with session option configs (instead of explicit compile API). +// Test that ORT does not overwrite an output model if it already exists. +// Notably, this tests the case in which ORT automatically generates the output model name. +TEST(OrtEpLibrary, PluginEp_GenEpContextModel_ErrorOutputModelExists_AutoGenOutputModelName) { + const ORTCHAR_T* input_model_file = ORT_TSTR("testdata/mul_1.onnx"); + const ORTCHAR_T* expected_output_model_file = ORT_TSTR("testdata/mul_1_ctx.onnx"); + std::filesystem::remove(expected_output_model_file); + + RegisteredEpDeviceUniquePtr example_ep; + Utils::RegisterAndGetExampleEp(*ort_env, Utils::example_ep_info, example_ep); + Ort::ConstEpDevice plugin_ep_device(example_ep.get()); + std::unordered_map ep_options; + + // Compile a model and let ORT set the output model name. This should succeed. + { + Ort::SessionOptions so; + so.AddConfigEntry(kOrtSessionOptionEpContextEnable, "1"); + // Don't specify an output model path to let ORT automatically generate it! + // so.AddConfigEntry(kOrtSessionOptionEpContextFilePath, ""); + + so.AppendExecutionProvider_V2(*ort_env, {plugin_ep_device}, ep_options); + + Ort::Session session(*ort_env, input_model_file, so); + ASSERT_TRUE(std::filesystem::exists(expected_output_model_file)); // check compiled model was generated. + } + + auto modify_time_1 = std::filesystem::last_write_time(expected_output_model_file); + + // Try compiling the model again. ORT should return an error because the output model already exists. + // Original compiled model should not be modified. + { + Ort::SessionOptions so; + so.AddConfigEntry(kOrtSessionOptionEpContextEnable, "1"); + // Don't specify an output model path to let ORT automatically generate it! + // so.AddConfigEntry(kOrtSessionOptionEpContextFilePath, ""); + + so.AppendExecutionProvider_V2(*ort_env, {plugin_ep_device}, ep_options); + + try { + Ort::Session session(*ort_env, input_model_file, so); + FAIL(); // Should not get here! + } catch (const Ort::Exception& excpt) { + ASSERT_EQ(excpt.GetOrtErrorCode(), ORT_FAIL); + ASSERT_THAT(excpt.what(), + testing::HasSubstr("exists already. " + "Please remove the EP context model if you want to re-generate it.")); + + ASSERT_TRUE(std::filesystem::exists(expected_output_model_file)); + auto modify_time_2 = std::filesystem::last_write_time(expected_output_model_file); + ASSERT_EQ(modify_time_2, modify_time_1); // Check that file was not modified + } + } + + std::filesystem::remove(expected_output_model_file); +} } // namespace test } // namespace onnxruntime From 310ff93b67b0c12cd4042078e90cc46c7d901dc2 Mon Sep 17 00:00:00 2001 From: Yulong Wang <7679871+fs-eire@users.noreply.github.com> Date: Fri, 31 Oct 2025 15:59:18 -0700 Subject: [PATCH 26/33] [node] Fix logging mutex crash at exit on macOS (#26445) ### Description This change fixes a bug that causes crash on macOS (and also potentially other platforms using libc) at `OrtReleaseEnv`. Instead of using static variables, now they are function local static so that compiler can handle the destruction order correctly. ### Motivation and Context Fixes #24579 --------- Co-authored-by: Copilot <175728472+Copilot@users.noreply.github.com> --- js/node/src/inference_session_wrap.cc | 9 +- js/node/src/ort_instance_data.cc | 29 +------ js/node/src/ort_instance_data.h | 18 ---- js/node/src/ort_singleton_data.cc | 22 +++++ js/node/src/ort_singleton_data.h | 40 +++++++++ .../{e2e => api}/inference-session-run.ts | 2 +- .../simple-api-tests.ts} | 2 +- js/node/test/{e2e => api}/worker-test.ts | 2 +- js/node/test/standalone/README.md | 23 +++++ js/node/test/standalone/index.ts | 86 +++++++++++++++++++ js/node/test/standalone/main.ts | 51 +++++++++++ js/node/test/test-main.ts | 11 ++- 12 files changed, 240 insertions(+), 55 deletions(-) create mode 100644 js/node/src/ort_singleton_data.cc create mode 100644 js/node/src/ort_singleton_data.h rename js/node/test/{e2e => api}/inference-session-run.ts (93%) rename js/node/test/{e2e/simple-e2e-tests.ts => api/simple-api-tests.ts} (98%) rename js/node/test/{e2e => api}/worker-test.ts (97%) create mode 100644 js/node/test/standalone/README.md create mode 100644 js/node/test/standalone/index.ts create mode 100644 js/node/test/standalone/main.ts diff --git a/js/node/src/inference_session_wrap.cc b/js/node/src/inference_session_wrap.cc index 8db91f792cb06..1e9aabc660c4b 100644 --- a/js/node/src/inference_session_wrap.cc +++ b/js/node/src/inference_session_wrap.cc @@ -6,6 +6,7 @@ #include "common.h" #include "inference_session_wrap.h" #include "ort_instance_data.h" +#include "ort_singleton_data.h" #include "run_options_helper.h" #include "session_options_helper.h" #include "tensor_helper.h" @@ -76,7 +77,7 @@ Napi::Value InferenceSessionWrap::LoadModel(const Napi::CallbackInfo& info) { Napi::String value = info[0].As(); ParseSessionOptions(info[1].As(), sessionOptions); - this->session_.reset(new Ort::Session(*OrtInstanceData::OrtEnv(), + this->session_.reset(new Ort::Session(OrtSingletonData::Env(), #ifdef _WIN32 reinterpret_cast(value.Utf16Value().c_str()), #else @@ -91,7 +92,7 @@ Napi::Value InferenceSessionWrap::LoadModel(const Napi::CallbackInfo& info) { int64_t bytesLength = info[2].As().Int64Value(); ParseSessionOptions(info[3].As(), sessionOptions); - this->session_.reset(new Ort::Session(*OrtInstanceData::OrtEnv(), + this->session_.reset(new Ort::Session(OrtSingletonData::Env(), reinterpret_cast(buffer) + bytesOffset, bytesLength, sessionOptions)); } else { @@ -211,7 +212,7 @@ Napi::Value InferenceSessionWrap::Run(const Napi::CallbackInfo& info) { ParseRunOptions(info[2].As(), runOptions); } if (preferredOutputLocations_.size() == 0) { - session_->Run(runOptions == nullptr ? *OrtInstanceData::OrtDefaultRunOptions() : runOptions, + session_->Run(runOptions == nullptr ? OrtSingletonData::DefaultRunOptions() : runOptions, inputIndex == 0 ? nullptr : &inputNames_cstr[0], inputIndex == 0 ? nullptr : &inputValues[0], inputIndex, outputIndex == 0 ? nullptr : &outputNames_cstr[0], outputIndex == 0 ? nullptr : &outputValues[0], outputIndex); @@ -240,7 +241,7 @@ Napi::Value InferenceSessionWrap::Run(const Napi::CallbackInfo& info) { } } - session_->Run(runOptions == nullptr ? *OrtInstanceData::OrtDefaultRunOptions() : runOptions, *ioBinding_); + session_->Run(runOptions == nullptr ? OrtSingletonData::DefaultRunOptions() : runOptions, *ioBinding_); auto outputs = ioBinding_->GetOutputValues(); ORT_NAPI_THROW_ERROR_IF(outputs.size() != outputIndex, env, "Output count mismatch."); diff --git a/js/node/src/ort_instance_data.cc b/js/node/src/ort_instance_data.cc index d9b66909f1291..6303f92a163af 100644 --- a/js/node/src/ort_instance_data.cc +++ b/js/node/src/ort_instance_data.cc @@ -6,27 +6,10 @@ #include "common.h" #include "ort_instance_data.h" +#include "ort_singleton_data.h" #include "onnxruntime_cxx_api.h" -std::unique_ptr OrtInstanceData::ortEnv; -std::unique_ptr OrtInstanceData::ortDefaultRunOptions; -std::mutex OrtInstanceData::ortEnvMutex; -std::atomic OrtInstanceData::ortEnvRefCount; -std::atomic OrtInstanceData::ortEnvDestroyed; - OrtInstanceData::OrtInstanceData() { - ++ortEnvRefCount; -} - -OrtInstanceData::~OrtInstanceData() { - if (--ortEnvRefCount == 0) { - std::lock_guard lock(ortEnvMutex); - if (ortEnv) { - ortDefaultRunOptions.reset(nullptr); - ortEnv.reset(); - ortEnvDestroyed = true; - } - } } void OrtInstanceData::Create(Napi::Env env, Napi::Function inferenceSessionWrapperFunction) { @@ -42,14 +25,8 @@ void OrtInstanceData::InitOrt(Napi::Env env, int log_level, Napi::Function tenso data->ortTensorConstructor = Napi::Persistent(tensorConstructor); - if (!ortEnv) { - std::lock_guard lock(ortEnvMutex); - if (!ortEnv) { - ORT_NAPI_THROW_ERROR_IF(ortEnvDestroyed, env, "OrtEnv already destroyed."); - ortEnv.reset(new Ort::Env{OrtLoggingLevel(log_level), "onnxruntime-node"}); - ortDefaultRunOptions.reset(new Ort::RunOptions{}); - } - } + // Only the first time call to OrtSingletonData::GetOrCreateOrtObjects() will create the Ort::Env + OrtSingletonData::GetOrCreateOrtObjects(log_level); } const Napi::FunctionReference& OrtInstanceData::TensorConstructor(Napi::Env env) { diff --git a/js/node/src/ort_instance_data.h b/js/node/src/ort_instance_data.h index bb70ac8e87d3a..0d581cf895a3b 100644 --- a/js/node/src/ort_instance_data.h +++ b/js/node/src/ort_instance_data.h @@ -8,11 +8,6 @@ /** * The OrtInstanceData class is designed to manage the lifecycle of necessary instance data, including: - * - The Ort::Env singleton instance. - * This is a global singleton that is shared across all InferenceSessionWrap instances. It is created when the first - * time `InferenceSession.initOrtOnce()` is called. It is destroyed when the last active NAPI Env is destroyed. - * Once destroyed, it cannot be created again. - * * - The Object reference of the InferenceSessionWrap class and the Tensor constructor. * This is a per-env data that has the same lifecycle as the Napi::Env. If there are worker threads, each thread will * have its own handle to the InferenceSessionWrap class and the Tensor constructor. @@ -27,12 +22,6 @@ struct OrtInstanceData { static void InitOrt(Napi::Env env, int log_level, Napi::Function tensorConstructor); // Get the Tensor constructor reference for the Napi::Env static const Napi::FunctionReference& TensorConstructor(Napi::Env env); - // Get the global Ort::Env - static const Ort::Env* OrtEnv() { return ortEnv.get(); } - // Get the default Ort::RunOptions - static Ort::RunOptions* OrtDefaultRunOptions() { return ortDefaultRunOptions.get(); } - - ~OrtInstanceData(); private: OrtInstanceData(); @@ -40,11 +29,4 @@ struct OrtInstanceData { // per env persistent constructors Napi::FunctionReference wrappedSessionConstructor; Napi::FunctionReference ortTensorConstructor; - - // ORT env (global singleton) - static std::unique_ptr ortEnv; - static std::unique_ptr ortDefaultRunOptions; - static std::mutex ortEnvMutex; - static std::atomic ortEnvRefCount; - static std::atomic ortEnvDestroyed; }; diff --git a/js/node/src/ort_singleton_data.cc b/js/node/src/ort_singleton_data.cc new file mode 100644 index 0000000000000..11dcb18a5e665 --- /dev/null +++ b/js/node/src/ort_singleton_data.cc @@ -0,0 +1,22 @@ +// Copyright (c) Microsoft Corporation. All rights reserved. +// Licensed under the MIT License. + +#include "ort_singleton_data.h" + +OrtSingletonData::OrtObjects::OrtObjects(int log_level) + : env{OrtLoggingLevel(log_level), "onnxruntime-node"}, + default_run_options{} { +} + +OrtSingletonData::OrtObjects& OrtSingletonData::GetOrCreateOrtObjects(int log_level) { + static OrtObjects ort_objects(log_level); + return ort_objects; +} + +const Ort::Env& OrtSingletonData::Env() { + return GetOrCreateOrtObjects().env; +} + +const Ort::RunOptions& OrtSingletonData::DefaultRunOptions() { + return GetOrCreateOrtObjects().default_run_options; +} diff --git a/js/node/src/ort_singleton_data.h b/js/node/src/ort_singleton_data.h new file mode 100644 index 0000000000000..a8857aa8ab442 --- /dev/null +++ b/js/node/src/ort_singleton_data.h @@ -0,0 +1,40 @@ +// Copyright (c) Microsoft Corporation. All rights reserved. +// Licensed under the MIT License. + +#pragma once + +#include +#include "onnxruntime_cxx_api.h" + +/** + * The OrtSingletonData class is designed to manage the lifecycle of necessary singleton instance data, including: + * + * - The Ort::Env singleton instance. + * This is a global singleton that is shared across all InferenceSessionWrap instances. It is created when the first + * time `InferenceSession.initOrtOnce()` is called. + * + * - The Ort::RunOptions singleton instance. + * This is an empty default RunOptions instance. It is created once to allow reuse across all session inference runs. + * + * The OrtSingletonData class uses the "Meyers Singleton" pattern to ensure thread-safe lazy initialization, as well as + * proper destruction order at program exit. + */ +struct OrtSingletonData { + struct OrtObjects { + Ort::Env env; + Ort::RunOptions default_run_options; + + private: + // The following pattern ensures that OrtObjects can only be created by OrtSingletonData + OrtObjects(int log_level); + friend struct OrtSingletonData; + }; + + static OrtObjects& GetOrCreateOrtObjects(int log_level = ORT_LOGGING_LEVEL_WARNING); + + // Get the global Ort::Env + static const Ort::Env& Env(); + + // Get the default Ort::RunOptions + static const Ort::RunOptions& DefaultRunOptions(); +}; diff --git a/js/node/test/e2e/inference-session-run.ts b/js/node/test/api/inference-session-run.ts similarity index 93% rename from js/node/test/e2e/inference-session-run.ts rename to js/node/test/api/inference-session-run.ts index 820dec0945a8e..7a4cc25410330 100644 --- a/js/node/test/e2e/inference-session-run.ts +++ b/js/node/test/api/inference-session-run.ts @@ -6,7 +6,7 @@ import * as path from 'path'; import { assertTensorEqual, SQUEEZENET_INPUT0_DATA, SQUEEZENET_OUTPUT0_DATA, TEST_DATA_ROOT } from '../test-utils'; -describe('E2E Tests - InferenceSession.run()', async () => { +describe('API Tests - InferenceSession.run()', async () => { let session: InferenceSession; const input0 = new Tensor('float32', SQUEEZENET_INPUT0_DATA, [1, 3, 224, 224]); const expectedOutput0 = new Tensor('float32', SQUEEZENET_OUTPUT0_DATA, [1, 1000, 1, 1]); diff --git a/js/node/test/e2e/simple-e2e-tests.ts b/js/node/test/api/simple-api-tests.ts similarity index 98% rename from js/node/test/e2e/simple-e2e-tests.ts rename to js/node/test/api/simple-api-tests.ts index 6841dae316304..da7adecc3d4e4 100644 --- a/js/node/test/e2e/simple-e2e-tests.ts +++ b/js/node/test/api/simple-api-tests.ts @@ -87,7 +87,7 @@ const MODEL_TEST_TYPES_CASES: Array<{ }, ]; -describe('E2E Tests - simple E2E tests', () => { +describe('API Tests - simple API tests', () => { MODEL_TEST_TYPES_CASES.forEach((testCase) => { it(`${testCase.model}`, async () => { const session = await InferenceSession.create(testCase.model); diff --git a/js/node/test/e2e/worker-test.ts b/js/node/test/api/worker-test.ts similarity index 97% rename from js/node/test/e2e/worker-test.ts rename to js/node/test/api/worker-test.ts index 3b803c86d8b5b..1e4907db9fd5b 100644 --- a/js/node/test/e2e/worker-test.ts +++ b/js/node/test/api/worker-test.ts @@ -7,7 +7,7 @@ import { assertTensorEqual, SQUEEZENET_INPUT0_DATA, SQUEEZENET_OUTPUT0_DATA, TES import * as path from 'path'; if (isMainThread) { - describe('E2E Tests - worker test', () => { + describe('API Tests - worker test', () => { it('should run in worker', (done) => { const worker = new Worker(__filename, { stdout: true, diff --git a/js/node/test/standalone/README.md b/js/node/test/standalone/README.md new file mode 100644 index 0000000000000..dbd184471452d --- /dev/null +++ b/js/node/test/standalone/README.md @@ -0,0 +1,23 @@ +# Process Exit Tests + +These tests verify that the ORT Node.js binding handles various process exit scenarios without crashing, specifically addressing the mutex crash issue reported in [#24579](https://github.com/microsoft/onnxruntime/issues/24579). + +## What This Tests + +- **Normal process exit** - Verifies clean shutdown without mutex crashes +- **`process.exit()` calls** - Tests the primary crash scenario that was fixed +- **Uncaught exceptions** - Ensures crashes don't occur during unexpected exits +- **Session cleanup** - Tests both explicit `session.release()` and automatic cleanup +- **Stability** - Multiple runs to ensure consistent behavior + +## How It Works + +Each test runs in a separate Node.js process to isolate the test environment. Tests use command-line flags to control behavior: + +- `--process-exit`: Triggers `process.exit(0)` +- `--throw-exception`: Throws an uncaught exception +- `--release`: Calls `session.release()` before exit + +## Expected Result + +All tests should pass without `mutex lock failed` or `std::__1::system_error` messages in stderr. diff --git a/js/node/test/standalone/index.ts b/js/node/test/standalone/index.ts new file mode 100644 index 0000000000000..3125d9d51466c --- /dev/null +++ b/js/node/test/standalone/index.ts @@ -0,0 +1,86 @@ +// Copyright (c) Microsoft Corporation. All rights reserved. +// Licensed under the MIT License. + +import { spawn } from 'child_process'; +import * as assert from 'assert'; +import * as path from 'path'; + +describe('Standalone Process Tests', () => { + // Helper function to run test script in a separate process + const runTest = async (args: string[] = []): Promise<{ code: number; stdout: string; stderr: string }> => + new Promise((resolve, reject) => { + // Use the compiled main.js file from the lib directory + const testFile = path.join(__dirname, './main.js'); + + const child = spawn('node', [testFile, ...args], { stdio: 'pipe' }); + + let stdout = ''; + let stderr = ''; + + child.stdout.on('data', (data) => (stdout += data.toString())); + child.stderr.on('data', (data) => (stderr += data.toString())); + + child.on('close', (code) => { + resolve({ code: code || 0, stdout, stderr }); + }); + + child.on('error', reject); + }); + + // Helper function to check basic success criteria + const assertSuccess = (result: { code: number; stdout: string; stderr: string }) => { + assert.strictEqual(result.code, 0); + assert.ok(result.stdout.includes('SUCCESS: Inference completed')); + assert.ok(!result.stderr.includes('mutex lock failed')); + }; + + // Helper function to check that no mutex crashes occurred + const assertNoMutexErrors = (stderr: string) => { + assert.ok(!stderr.includes('mutex lock failed')); + assert.ok(!stderr.includes('std::__1::system_error')); + }; + + it('should handle normal process exit', async () => { + const result = await runTest([]); + assertSuccess(result); + }); + + it('should handle process.exit() call', async () => { + const result = await runTest(['--process-exit']); + assertSuccess(result); + }); + + it('should handle uncaught exceptions', async () => { + const result = await runTest(['--throw-exception']); + + assert.notStrictEqual(result.code, 0); + assert.ok(result.stdout.includes('SUCCESS: Inference completed')); + assert.ok(result.stderr.includes('Test exception')); + assertNoMutexErrors(result.stderr); + }); + + it('should handle multiple process exits consistently', async () => { + for (let i = 0; i < 3; i++) { + const result = await runTest(['--process-exit']); + assertSuccess(result); + } + }); + + it('should handle session.release() before normal exit', async () => { + const result = await runTest(['--release']); + assertSuccess(result); + assert.ok(result.stdout.includes('Session released')); + }); + + it('should handle session.release() before process.exit()', async () => { + const result = await runTest(['--release', '--process-exit']); + assertSuccess(result); + assert.ok(result.stdout.includes('Session released')); + }); + + it('should handle no session.release() before process.exit()', async () => { + const result = await runTest(['--process-exit']); + assertSuccess(result); + assert.ok(result.stdout.includes('Session NOT released')); + }); +}); diff --git a/js/node/test/standalone/main.ts b/js/node/test/standalone/main.ts new file mode 100644 index 0000000000000..dceb7ceff3ef0 --- /dev/null +++ b/js/node/test/standalone/main.ts @@ -0,0 +1,51 @@ +// Copyright (c) Microsoft Corporation. All rights reserved. +// Licensed under the MIT License. + +import * as path from 'path'; +const ort = require(path.join(__dirname, '../../')); +import * as process from 'process'; + +const modelData = + 'CAMSDGJhY2tlbmQtdGVzdDpiChEKAWEKAWISAWMiBk1hdE11bBIOdGVzdF9tYXRtdWxfMmRaEwoBYRIOCgwIARIICgIIAwoCCARaEwoBYhIOCgwIARIICgIIBAoCCANiEwoBYxIOCgwIARIICgIIAwoCCANCAhAJ'; +const shouldProcessExit = process.argv.includes('--process-exit'); +const shouldThrowException = process.argv.includes('--throw-exception'); +const shouldRelease = process.argv.includes('--release'); + +async function main() { + try { + const modelBuffer = Buffer.from(modelData, 'base64'); + const session = await ort.InferenceSession.create(modelBuffer); + + const dataA = Float32Array.from([1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12]); + const dataB = Float32Array.from([10, 20, 30, 40, 50, 60, 70, 80, 90, 100, 110, 120]); + const tensorA = new ort.Tensor('float32', dataA, [3, 4]); + const tensorB = new ort.Tensor('float32', dataB, [4, 3]); + + const results = await session.run({ a: tensorA, b: tensorB }); + console.log('SUCCESS: Inference completed'); + console.log(`Result: ${results.c.data}`); + + if (shouldRelease) { + await session.release(); + console.log('Session released'); + } else { + console.log('Session NOT released (testing cleanup behavior)'); + } + + if (shouldThrowException) { + setTimeout(() => { + throw new Error('Test exception'); + }, 10); + return; + } + + if (shouldProcessExit) { + process.exit(0); + } + } catch (e) { + console.error(`ERROR: ${e}`); + process.exit(1); + } +} + +void main(); diff --git a/js/node/test/test-main.ts b/js/node/test/test-main.ts index ec7d4e2fc12d0..d4599eecf7253 100644 --- a/js/node/test/test-main.ts +++ b/js/node/test/test-main.ts @@ -18,10 +18,13 @@ require('./unittests/lib/inference-session'); require('./unittests/lib/model-metadata'); require('./unittests/lib/tensor'); -// E2E tests -require('./e2e/simple-e2e-tests'); -require('./e2e/inference-session-run'); -require('./e2e/worker-test'); +// API tests +require('./api/simple-api-tests'); +require('./api/inference-session-run'); +require('./api/worker-test'); + +// standalone tests +require('./standalone/index'); // Test ONNX spec tests import { run as runTestRunner } from './test-runner'; From 002539f090eb102b8e6c31ce1fdf48e224a02449 Mon Sep 17 00:00:00 2001 From: borg323 <39573933+borg323@users.noreply.github.com> Date: Sat, 1 Nov 2025 01:53:36 +0200 Subject: [PATCH 27/33] coreml: Add a few missing operators (#26462) ### Description Adds `Elu`, `Exp` and `Softplus` to coreml. ### Motivation and Context We use them in LeelaChessZero. --------- Co-authored-by: borg323 --- .../builders/impl/activation_op_builder.cc | 24 +++++++++++++++---- .../coreml/builders/impl/base_op_builder.cc | 2 +- .../coreml/builders/impl/unary_op_builder.cc | 8 +++++-- .../coreml/builders/op_builder_factory.cc | 3 +++ .../apple/coreml_supported_mlprogram_ops.md | 3 +++ 5 files changed, 32 insertions(+), 8 deletions(-) diff --git a/onnxruntime/core/providers/coreml/builders/impl/activation_op_builder.cc b/onnxruntime/core/providers/coreml/builders/impl/activation_op_builder.cc index 3fffc6d0a68c4..957790f61e227 100644 --- a/onnxruntime/core/providers/coreml/builders/impl/activation_op_builder.cc +++ b/onnxruntime/core/providers/coreml/builders/impl/activation_op_builder.cc @@ -118,6 +118,11 @@ Status ActivationOpBuilder::AddToModelBuilderImpl(ModelBuilder& model_builder, } else if (op_type == "PRelu") { coreml_op_type = "prelu"; add_alpha = true; + } else if (op_type == "Softplus") { + coreml_op_type = "softplus"; + } else if (op_type == "Elu") { + coreml_op_type = "elu"; + add_alpha = true; } else { return ORT_MAKE_STATUS(ONNXRUNTIME, INVALID_ARGUMENT, "ActivationOpBuilder::AddToModelBuilderImpl, unknown op: ", op_type); @@ -141,7 +146,7 @@ Status ActivationOpBuilder::AddToModelBuilderImpl(ModelBuilder& model_builder, } } else { NodeAttrHelper helper(node); - const auto alpha = helper.Get("alpha", 0.01f); + const auto alpha = helper.Get("alpha", "Elu" == op_type ? 1.0f : 0.01f); if (input_dtype == ONNX_NAMESPACE::TensorProto_DataType_FLOAT) { AddOperationInput(*op, "alpha", model_builder.AddScalarConstant(op->type(), "alpha", alpha)); @@ -259,8 +264,10 @@ bool ActivationOpBuilder::IsOpSupportedImpl(const Node& node, const OpBuilderInp const logging::Logger& logger) const { const auto& op_type = node.OpType(); - if (op_type == "Gelu" && !input_params.create_mlprogram) { - return false; + if (!input_params.create_mlprogram) { + if (op_type == "Gelu" || op_type == "Softplus" || op_type == "Elu") { + return false; + } } if (op_type == "PRelu") { return IsPReluOpSupported(node, input_params, logger); @@ -269,8 +276,13 @@ bool ActivationOpBuilder::IsOpSupportedImpl(const Node& node, const OpBuilderInp return true; } -int ActivationOpBuilder::GetMinSupportedOpSet(const Node& /* node */) const { - // All ops opset 5- uses consumed_inputs attribute which is not supported for now +int ActivationOpBuilder::GetMinSupportedOpSet(const Node& node) const { + const auto& op_type(node.OpType()); + // Softplus was unmodified from opset 1 to 21 (with no attributes). + if (op_type == "Softplus") { + return 1; + } + // All other ops opset 5- uses consumed_inputs attribute which is not supported for now. return 6; } @@ -286,6 +298,8 @@ void CreateActivationOpBuilder(const std::string& op_type, OpBuilderRegistration "PRelu", "LeakyRelu", "Gelu", + "Softplus", + "Elu", }; op_registrations.builders.push_back(std::make_unique()); diff --git a/onnxruntime/core/providers/coreml/builders/impl/base_op_builder.cc b/onnxruntime/core/providers/coreml/builders/impl/base_op_builder.cc index b9c525380eecc..51182c6f7b04b 100644 --- a/onnxruntime/core/providers/coreml/builders/impl/base_op_builder.cc +++ b/onnxruntime/core/providers/coreml/builders/impl/base_op_builder.cc @@ -105,7 +105,7 @@ bool BaseOpBuilder::HasSupportedInputsImpl(const Node& node, const OpBuilderInpu bool BaseOpBuilder::HasSupportedOpSet(const Node& node, const logging::Logger& logger) const { auto since_version = node.SinceVersion(); if (since_version < GetMinSupportedOpSet(node) || since_version > GetMaxSupportedOpSet(node)) { - LOGS(logger, VERBOSE) << node.OpType() << "is only supported for opset [" + LOGS(logger, VERBOSE) << node.OpType() << " is only supported for opset [" << GetMinSupportedOpSet(node) << ", " << GetMaxSupportedOpSet(node) << "]"; return false; diff --git a/onnxruntime/core/providers/coreml/builders/impl/unary_op_builder.cc b/onnxruntime/core/providers/coreml/builders/impl/unary_op_builder.cc index dd495894ab8bb..09ce25fd29778 100644 --- a/onnxruntime/core/providers/coreml/builders/impl/unary_op_builder.cc +++ b/onnxruntime/core/providers/coreml/builders/impl/unary_op_builder.cc @@ -37,6 +37,8 @@ Status UnaryOpBuilder::AddToModelBuilderImpl(ModelBuilder& model_builder, const coreml_op_type = "erf"; } else if (op_type == "Round") { coreml_op_type = "round"; + } else if (op_type == "Exp") { + coreml_op_type = "exp"; } else { return ORT_MAKE_STATUS(ONNXRUNTIME, INVALID_ARGUMENT, "UnaryOpBuilder::AddToModelBuilderImpl, unexpected op: ", op_type); @@ -79,8 +81,10 @@ Status UnaryOpBuilder::AddToModelBuilderImpl(ModelBuilder& model_builder, const bool UnaryOpBuilder::IsOpSupportedImpl(const Node& node, const OpBuilderInputParams& input_params, const logging::Logger& /*logger*/) const { - if (!input_params.create_mlprogram && (node.OpType() == "Erf" || node.OpType() == "Round")) { - return false; + if (!input_params.create_mlprogram) { + if (node.OpType() == "Erf" || node.OpType() == "Round" || node.OpType() == "Exp") { + return false; + } } return true; } diff --git a/onnxruntime/core/providers/coreml/builders/op_builder_factory.cc b/onnxruntime/core/providers/coreml/builders/op_builder_factory.cc index 6e7df20a06097..52d56f6ba63ad 100644 --- a/onnxruntime/core/providers/coreml/builders/op_builder_factory.cc +++ b/onnxruntime/core/providers/coreml/builders/op_builder_factory.cc @@ -22,12 +22,15 @@ static OpBuilderRegistrations CreateOpBuilderRegistrations() { CreateActivationOpBuilder("PRelu", op_registrations); CreateActivationOpBuilder("LeakyRelu", op_registrations); CreateActivationOpBuilder("Gelu", op_registrations); + CreateActivationOpBuilder("Softplus", op_registrations); + CreateActivationOpBuilder("Elu", op_registrations); // Unary ops CreateUnaryOpBuilder("Erf", op_registrations); CreateUnaryOpBuilder("Reciprocal", op_registrations); CreateUnaryOpBuilder("Round", op_registrations); CreateUnaryOpBuilder("Sqrt", op_registrations); + CreateUnaryOpBuilder("Exp", op_registrations); // Binary elementwise ops CreateBinaryOpBuilder("Add", op_registrations); diff --git a/tools/ci_build/github/apple/coreml_supported_mlprogram_ops.md b/tools/ci_build/github/apple/coreml_supported_mlprogram_ops.md index 4991b4329646f..5f3fcd9be3497 100644 --- a/tools/ci_build/github/apple/coreml_supported_mlprogram_ops.md +++ b/tools/ci_build/github/apple/coreml_supported_mlprogram_ops.md @@ -13,7 +13,9 @@ Keep in sync with doco generated from /docs/execution-providers/CoreML-Execution |ai.onnx:ConvTranspose|Weight and bias must be constant.
padding_type of SAME_UPPER/SAME_LOWER is not supported.
kernel_shape must have default values.
output_shape is not supported.
output_padding must have default values.| |ai.onnx:DepthToSpace|If 'mode' is 'CRD' the input must have a fixed shape.| |ai.onnx:Div|| +|ai.onnx:Elu|| |ai.onnx:Erf|| +|ai.onnx:Exp|| |ai.onnx:Gemm|Input B must be constant.| |ai.onnx:Gelu|| |ai.onnx:GlobalAveragePool|Only 2D Pool is supported currently. 3D and 5D support can be added if needed.| @@ -39,6 +41,7 @@ Keep in sync with doco generated from /docs/execution-providers/CoreML-Execution |ai.onnx:Round|| |ai.onnx:Shape|| |ai.onnx:Slice|starts/ends/axes/steps must be constant initializers.| +|ai.onnx:Softplus|| |ai.onnx:Split|If provided, `splits` must be constant.| |ai.onnx:Sub|| |ai.onnx:Sigmoid|| From 06ac0d48759b46ac802d8771ca0878715254226c Mon Sep 17 00:00:00 2001 From: Edward Chen <18449977+edgchen1@users.noreply.github.com> Date: Fri, 31 Oct 2025 17:47:01 -0700 Subject: [PATCH 28/33] Update out-of-support net8.0 MAUI targets to net9.0 (#26463) ### Description .NET MAUI 8 is out of support. See here: https://dotnet.microsoft.com/en-us/platform/support/policy/maui We started seeing errors about this in the NuGet packaging pipeline. ``` ##[error]C:\Program Files\dotnet\sdk\9.0.306\Sdks\Microsoft.NET.Sdk\targets\Microsoft.NET.EolTargetFrameworks.targets(38,5): Error NETSDK1202: The workload 'net8.0-ios' is out of support and will not receive security updates in the future. Please refer to https://aka.ms/maui-support-policy for more information about the support policy. ``` This change updates net8.0 mobile target framework monikers to net9.0. ### Motivation and Context Fix packaging pipeline. --- ...ML.OnnxRuntime.InferenceSample.Maui.csproj | 2 +- .../Microsoft.ML.OnnxRuntime.csproj | 4 +- .../targets.xml | 0 .../{net8.0-ios => net9.0-ios}/targets.xml | 0 .../README.md | 0 .../_._ | 0 .../README.md | 14 +-- .../browserstack.yml | 2 +- ...Microsoft.ML.OnnxRuntime.Tests.MAUI.csproj | 2 +- .../MauiModelTester/MauiModelTester.csproj | 2 +- .../nuget/templates/test_android.yml | 4 +- .../nuget/generate_nuspec_for_native_nuget.py | 113 +++++++++++------- 12 files changed, 84 insertions(+), 59 deletions(-) rename csharp/src/Microsoft.ML.OnnxRuntime/targets/{net8.0-android => net9.0-android}/targets.xml (100%) rename csharp/src/Microsoft.ML.OnnxRuntime/targets/{net8.0-ios => net9.0-ios}/targets.xml (100%) rename csharp/src/Microsoft.ML.OnnxRuntime/targets/{net8.0-maccatalyst => net9.0-maccatalyst}/README.md (100%) rename csharp/src/Microsoft.ML.OnnxRuntime/targets/{net8.0-maccatalyst => net9.0-maccatalyst}/_._ (100%) diff --git a/csharp/sample/InferenceSample/Microsoft.ML.OnnxRuntime.InferenceSample.Maui/Microsoft.ML.OnnxRuntime.InferenceSample.Maui.csproj b/csharp/sample/InferenceSample/Microsoft.ML.OnnxRuntime.InferenceSample.Maui/Microsoft.ML.OnnxRuntime.InferenceSample.Maui.csproj index 73a535999672c..310aaf98ae08d 100644 --- a/csharp/sample/InferenceSample/Microsoft.ML.OnnxRuntime.InferenceSample.Maui/Microsoft.ML.OnnxRuntime.InferenceSample.Maui.csproj +++ b/csharp/sample/InferenceSample/Microsoft.ML.OnnxRuntime.InferenceSample.Maui/Microsoft.ML.OnnxRuntime.InferenceSample.Maui.csproj @@ -1,7 +1,7 @@  - net8.0-android;net8.0-ios;net8.0-maccatalyst + net9.0-android;net9.0-ios;net9.0-maccatalyst $(TargetFrameworks);net8.0-windows10.0.19041.0 Exe Microsoft.ML.OnnxRuntime.InferenceSample.Maui diff --git a/csharp/src/Microsoft.ML.OnnxRuntime/Microsoft.ML.OnnxRuntime.csproj b/csharp/src/Microsoft.ML.OnnxRuntime/Microsoft.ML.OnnxRuntime.csproj index be0e8d2ee58a4..193be042ae420 100644 --- a/csharp/src/Microsoft.ML.OnnxRuntime/Microsoft.ML.OnnxRuntime.csproj +++ b/csharp/src/Microsoft.ML.OnnxRuntime/Microsoft.ML.OnnxRuntime.csproj @@ -19,12 +19,12 @@ - net8.0-android;net8.0-ios;net8.0-maccatalyst + net9.0-android;net9.0-ios;net9.0-maccatalyst - net8.0-android + net9.0-android diff --git a/csharp/src/Microsoft.ML.OnnxRuntime/targets/net8.0-android/targets.xml b/csharp/src/Microsoft.ML.OnnxRuntime/targets/net9.0-android/targets.xml similarity index 100% rename from csharp/src/Microsoft.ML.OnnxRuntime/targets/net8.0-android/targets.xml rename to csharp/src/Microsoft.ML.OnnxRuntime/targets/net9.0-android/targets.xml diff --git a/csharp/src/Microsoft.ML.OnnxRuntime/targets/net8.0-ios/targets.xml b/csharp/src/Microsoft.ML.OnnxRuntime/targets/net9.0-ios/targets.xml similarity index 100% rename from csharp/src/Microsoft.ML.OnnxRuntime/targets/net8.0-ios/targets.xml rename to csharp/src/Microsoft.ML.OnnxRuntime/targets/net9.0-ios/targets.xml diff --git a/csharp/src/Microsoft.ML.OnnxRuntime/targets/net8.0-maccatalyst/README.md b/csharp/src/Microsoft.ML.OnnxRuntime/targets/net9.0-maccatalyst/README.md similarity index 100% rename from csharp/src/Microsoft.ML.OnnxRuntime/targets/net8.0-maccatalyst/README.md rename to csharp/src/Microsoft.ML.OnnxRuntime/targets/net9.0-maccatalyst/README.md diff --git a/csharp/src/Microsoft.ML.OnnxRuntime/targets/net8.0-maccatalyst/_._ b/csharp/src/Microsoft.ML.OnnxRuntime/targets/net9.0-maccatalyst/_._ similarity index 100% rename from csharp/src/Microsoft.ML.OnnxRuntime/targets/net8.0-maccatalyst/_._ rename to csharp/src/Microsoft.ML.OnnxRuntime/targets/net9.0-maccatalyst/_._ diff --git a/csharp/test/Microsoft.ML.OnnxRuntime.Tests.BrowserStack.Android/README.md b/csharp/test/Microsoft.ML.OnnxRuntime.Tests.BrowserStack.Android/README.md index 9c4e2307d8f70..d92bb394210f6 100644 --- a/csharp/test/Microsoft.ML.OnnxRuntime.Tests.BrowserStack.Android/README.md +++ b/csharp/test/Microsoft.ML.OnnxRuntime.Tests.BrowserStack.Android/README.md @@ -2,11 +2,11 @@ This project will run the Android MAUI tests on BrowserStack, which allows you to run automated tests on a variety of mobile devices. ## Context -Microsoft.ML.OnnxRuntime.Tests.MAUI uses DeviceRunners.VisualRunners to allow running the unit tests (found in Microsoft.ML.OnnxRuntime.Tests.Common) across multiple devices. DeviceRunners.VisualRunners provides a simple UI with a button that will run the unit tests and a panel with the unit test results. +Microsoft.ML.OnnxRuntime.Tests.MAUI uses DeviceRunners.VisualRunners to allow running the unit tests (found in Microsoft.ML.OnnxRuntime.Tests.Common) across multiple devices. DeviceRunners.VisualRunners provides a simple UI with a button that will run the unit tests and a panel with the unit test results. In order to automate the process of running the unit tests across mobile devices, Appium is used for UI testing orchestration (it provides a way to interact with the UI), and BrowserStack automatically runs these Appium tests across different mobile devices. -This project does not include the capability to start an Appium server locally or attach to a local emulator or device. +This project does not include the capability to start an Appium server locally or attach to a local emulator or device. ## Build & run instructions ### Requirements @@ -22,8 +22,8 @@ This project does not include the capability to start an Appium server locally o ### Run instructions 1. Build the Microsoft.ML.OnnxRuntime.Tests.MAUI project into a signed APK. - 1. Run the following: `dotnet publish -c Release -f net8.0-android` in the Microsoft.ML.OnnxRuntime.Tests.MAUI directory. - 2. Search for the APK files generated. They should be located in `bin\Release\net8.0-android\publish`. + 1. Run the following: `dotnet publish -c Release -f net9.0-android` in the Microsoft.ML.OnnxRuntime.Tests.MAUI directory. + 2. Search for the APK files generated. They should be located in `bin\Release\net9.0-android\publish`. 3. If they're in a different location, edit the `browserstack.yml` file to target the path to the signed APK. 2. Ensure you've set the BrowserStack credentials as environment variables. 3. Run the following in the Microsoft.ML.OnnxRuntime.Tests.Android.BrowserStack directory: `dotnet test` @@ -36,13 +36,13 @@ This project does not include the capability to start an Appium server locally o - [Integration guide](https://www.browserstack.com/docs/app-automate/appium/getting-started/c-sharp/nunit/integrate-your-tests#CLI) ### Troubleshooting -- Issues building the MAUI app: +- Issues building the MAUI app: - Make sure that the maui and maui-android workloads are installed correctly by running `dotnet workload list` - If you believe the issues are workload related, you can also try running `dotnet workload repair` (this has personally never worked for me) - - Try running `dotnet clean`. However, this does not fully remove all the previous intermediaries. If you're still running into the errors, manually deleting the bin and obj folders can sometimes resolve them. + - Try running `dotnet clean`. However, this does not fully remove all the previous intermediaries. If you're still running into the errors, manually deleting the bin and obj folders can sometimes resolve them. - After building the MAUI app, try installing on an emulator and clicking the "Run All" button to ensure that everything is working. (If you are missing the ONNXRuntime package, it will not show up as an error until you click "Run All".) - Running the MAUI app from Visual Studio will not replicate running it through BrowserStack. Instead, use `adb install [path to signed apk]` to install the app then use the emulator to launch the app. - Issues with the Android.BrowserStack test app: there is an Appium Doctor package on npm -- run `npm install @appium/doctor --location=global` then `appium-doctor --android` and follow the directed instructions. Some errors with Appium on Android will not appear until runtime. - Connection refused by Appium server: this can happen if you already have an Appium server running locally. If you do, stop the Appium server then try `dotnet test` again. -- App is crashing on BrowserStack or it emits an error that it cannot run this APK file: make sure that you are passing in the correct signed APK from the publish folder. +- App is crashing on BrowserStack or it emits an error that it cannot run this APK file: make sure that you are passing in the correct signed APK from the publish folder. - It appears that a test runs on CLI but a build is not launched on BrowserStack: this happens when the BrowserStack Test Adapter cannot find the browserstack.yml file (which has to be named "browserstack.yml" -- do not be tricked by BrowserStack's article on custom-named configuration files) diff --git a/csharp/test/Microsoft.ML.OnnxRuntime.Tests.BrowserStack.Android/browserstack.yml b/csharp/test/Microsoft.ML.OnnxRuntime.Tests.BrowserStack.Android/browserstack.yml index 0afa8ca9c7fae..d9866901fd95c 100644 --- a/csharp/test/Microsoft.ML.OnnxRuntime.Tests.BrowserStack.Android/browserstack.yml +++ b/csharp/test/Microsoft.ML.OnnxRuntime.Tests.BrowserStack.Android/browserstack.yml @@ -1,4 +1,4 @@ -app: ..\Microsoft.ML.OnnxRuntime.Tests.MAUI\bin\Release\net8.0-android\publish\ORT.CSharp.Tests.MAUI-Signed.apk +app: ..\Microsoft.ML.OnnxRuntime.Tests.MAUI\bin\Release\net9.0-android\publish\ORT.CSharp.Tests.MAUI-Signed.apk platforms: - platformName: android deviceName: Samsung Galaxy S22 Ultra diff --git a/csharp/test/Microsoft.ML.OnnxRuntime.Tests.MAUI/Microsoft.ML.OnnxRuntime.Tests.MAUI.csproj b/csharp/test/Microsoft.ML.OnnxRuntime.Tests.MAUI/Microsoft.ML.OnnxRuntime.Tests.MAUI.csproj index cd50b2a57407f..b181767aaf247 100644 --- a/csharp/test/Microsoft.ML.OnnxRuntime.Tests.MAUI/Microsoft.ML.OnnxRuntime.Tests.MAUI.csproj +++ b/csharp/test/Microsoft.ML.OnnxRuntime.Tests.MAUI/Microsoft.ML.OnnxRuntime.Tests.MAUI.csproj @@ -14,7 +14,7 @@ Disabling those targets until the issues are resolved. --> - net8.0-android + net9.0-android $(TargetFrameworks);net8.0-windows10.0.19041.0