From 912cba3a9eab52d0eeb3067e2552a458a6e1dd2e Mon Sep 17 00:00:00 2001 From: "zhangxu.709" Date: Fri, 28 Nov 2025 12:46:31 +0800 Subject: [PATCH] refactor: replace all TORCH_CHECK with CHECK. --- xllm/core/framework/eplb/eplb_policy.cpp | 4 ++-- xllm/core/framework/parallel_state/npu_process_group.cpp | 2 +- xllm/core/layers/common/tests/tests_utils.cpp | 4 ++-- xllm/core/layers/mlu/deepseek_v2_attention.cpp | 4 ++-- xllm/core/layers/npu/npu_deepseek_v2_decoder_layer_impl.h | 7 ++----- xllm/models/dit/dit.h | 2 +- xllm/models/dit/pipeline_flux_base.h | 2 +- xllm/models/vlm/minicpmv.h | 6 +++--- 8 files changed, 14 insertions(+), 17 deletions(-) diff --git a/xllm/core/framework/eplb/eplb_policy.cpp b/xllm/core/framework/eplb/eplb_policy.cpp index f20ac0e58..c57e9da3d 100644 --- a/xllm/core/framework/eplb/eplb_policy.cpp +++ b/xllm/core/framework/eplb/eplb_policy.cpp @@ -76,7 +76,7 @@ std::pair> EplbPolicy::rebalance_experts( torch::Tensor EplbPolicy::compute_balanced_pack( const torch::Tensor& expert_loads) { // Parameter Validation - TORCH_CHECK(expert_loads.dim() == 1, "expert_loads must be 1D tensor"); + CHECK_EQ(expert_loads.dim(), 1) << "expert_loads must be 1D tensor"; const int64_t num_experts = expert_loads.size(0); // Generate Redundant Experts @@ -139,7 +139,7 @@ std::pair EplbPolicy::update_origin_weights( torch::Tensor expert_loads, int32_t redundancy_experts) { // Parameter Validation - TORCH_CHECK(expert_loads.dim() == 1, "expert_loads must be 1D tensor"); + CHECK_EQ(expert_loads.dim(), 1) << "expert_loads must be 1D tensor"; const int64_t num_experts = expert_loads.size(0); // Initialize Data Structures diff --git a/xllm/core/framework/parallel_state/npu_process_group.cpp b/xllm/core/framework/parallel_state/npu_process_group.cpp index eff999223..fceaa9d00 100644 --- a/xllm/core/framework/parallel_state/npu_process_group.cpp +++ b/xllm/core/framework/parallel_state/npu_process_group.cpp @@ -69,7 +69,7 @@ HcclDataType to_hccl_data_type(const torch::Tensor& input) { case at::kBFloat16: return HCCL_DATA_TYPE_BFP16; default: - TORCH_CHECK(false, "Unconvertible HCCL type ", type); + LOG(FATAL) << "Unconvertible HCCL type: " << type; } } diff --git a/xllm/core/layers/common/tests/tests_utils.cpp b/xllm/core/layers/common/tests/tests_utils.cpp index 7d47e9b9c..753ee507e 100644 --- a/xllm/core/layers/common/tests/tests_utils.cpp +++ b/xllm/core/layers/common/tests/tests_utils.cpp @@ -249,10 +249,10 @@ torch::Tensor seeded_tensor(const std::string& key, out_cpu = map_mod_span(int64_t{}); break; default: - TORCH_CHECK(false, "Unsupported integer dtype: ", dtype); + LOG(FATAL) << "Unsupported integer dtype: " << dtype; } } else { - TORCH_CHECK(false, "Unsupported dtype for seeded_tensor"); + LOG(FATAL) << "Unsupported dtype for seeded_tensor"; } // Shape & device diff --git a/xllm/core/layers/mlu/deepseek_v2_attention.cpp b/xllm/core/layers/mlu/deepseek_v2_attention.cpp index fdf597045..90d2b9ff8 100644 --- a/xllm/core/layers/mlu/deepseek_v2_attention.cpp +++ b/xllm/core/layers/mlu/deepseek_v2_attention.cpp @@ -43,8 +43,8 @@ DeepseekV2AttentionImpl::DeepseekV2AttentionImpl( int64_t max_position_embeddings = args.max_position_embeddings(); qk_head_dim_ = qk_nope_head_dim_ + qk_rope_head_dim_; - TORCH_CHECK(num_heads % tp_size == 0, - "num_heads must be divisible by tensor parallel size"); + CHECK_EQ(num_heads % tp_size, 0) + << "num_heads must be divisible by tensor parallel size"; num_local_heads_ = num_heads / tp_size; float scaling = std::pow(qk_head_dim_, -0.5f); diff --git a/xllm/core/layers/npu/npu_deepseek_v2_decoder_layer_impl.h b/xllm/core/layers/npu/npu_deepseek_v2_decoder_layer_impl.h index c57964882..80a826fde 100644 --- a/xllm/core/layers/npu/npu_deepseek_v2_decoder_layer_impl.h +++ b/xllm/core/layers/npu/npu_deepseek_v2_decoder_layer_impl.h @@ -80,11 +80,8 @@ class ExpertBuffer { } else { auto validate_shape = [](const torch::Tensor& t, const std::vector& expected) { - TORCH_CHECK(t.sizes() == expected, - "Shape mismatch. Expected ", - expected, - " got ", - t.sizes()); + CHECK_EQ(t.sizes(), expected) + << "Shape mismatch. Expected " << expected << " got " << t.sizes(); }; validate_shape(gateup_weight, gateup_weight_shape); diff --git a/xllm/models/dit/dit.h b/xllm/models/dit/dit.h index d333758d5..570a4ec4f 100644 --- a/xllm/models/dit/dit.h +++ b/xllm/models/dit/dit.h @@ -592,7 +592,7 @@ inline torch::Tensor get_timestep_embedding(const torch::Tensor& timesteps, float downscale_freq_shift = 1.0f, float scale = 1.0f, int64_t max_period = 10000) { - TORCH_CHECK(timesteps.dim() == 1, "Timesteps should be a 1d-array"); + CHECK_EQ(timesteps.dim(), 1) << "Timesteps should be a 1d-array"; int64_t half_dim = embedding_dim / 2; // -ln(max_period) * [0, 1, ..., half_dim-1] / (half_dim - // downscale_freq_shift diff --git a/xllm/models/dit/pipeline_flux_base.h b/xllm/models/dit/pipeline_flux_base.h index 4b3895586..9a7602f12 100644 --- a/xllm/models/dit/pipeline_flux_base.h +++ b/xllm/models/dit/pipeline_flux_base.h @@ -85,7 +85,7 @@ torch::Tensor get_1d_rotary_pos_embed( float ntk_factor = 1.0, bool repeat_interleave_real = true, torch::Dtype freqs_dtype = torch::kFloat32) { - TORCH_CHECK(dim % 2 == 0, "Dimension must be even"); + CHECK_EQ(dim % 2, 0) << "Dimension must be even"; torch::Tensor pos_tensor = pos; if (pos.dim() == 0) { diff --git a/xllm/models/vlm/minicpmv.h b/xllm/models/vlm/minicpmv.h index 89920461b..b36859cf8 100644 --- a/xllm/models/vlm/minicpmv.h +++ b/xllm/models/vlm/minicpmv.h @@ -306,7 +306,7 @@ torch::Tensor get_1d_sincos_pos_embed_from_grid(int embed_dim, std::pair version = { 2, 0}) { - TORCH_CHECK(embed_dim % 2 == 0, "embed_dim must be even"); + CHECK_EQ(embed_dim % 2, 0) << "embed_dim must be even"; // compute omega auto omega = torch::arange(embed_dim / 2, torch::kFloat32); @@ -332,7 +332,7 @@ torch::Tensor get_2d_sincos_pos_embed_from_grid(int embed_dim, std::pair version = { 2, 0}) { - TORCH_CHECK(embed_dim % 2 == 0, "embed_dim must be even"); + CHECK_EQ(embed_dim % 2, 0) << "embed_dim must be even"; auto emb_h = get_1d_sincos_pos_embed_from_grid(embed_dim / 2, grid[0], version); @@ -382,7 +382,7 @@ class Resampler2_5Impl : public BaseResamplerImpl { } torch::Tensor forward(torch::Tensor x, torch::Tensor tgt_sizes) { - TORCH_CHECK(x.size(0) == tgt_sizes.size(0), "Batch size mismatch!"); + CHECK_EQ(x.size(0), tgt_sizes.size(0)) << "Batch size mismatch!"; int64_t batch_size = x.size(0); auto device = x.device();