Try to find an allocator when the engine is not assigned a device. #21508
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| /* Copyright 2018 The TensorFlow Authors. All Rights Reserved. | ||
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| Licensed under the Apache License, Version 2.0 (the "License"); | ||
| you may not use this file except in compliance with the License. | ||
| You may obtain a copy of the License at | ||
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| http://www.apache.org/licenses/LICENSE-2.0 | ||
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| Unless required by applicable law or agreed to in writing, software | ||
| distributed under the License is distributed on an "AS IS" BASIS, | ||
| WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. | ||
| See the License for the specific language governing permissions and | ||
| limitations under the License. | ||
| ==============================================================================*/ | ||
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| #include "tensorflow/contrib/tensorrt/convert/convert_graph.h" | ||
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| #include "tensorflow/contrib/tensorrt/convert/convert_nodes.h" | ||
| #include "tensorflow/core/common_runtime/device_mgr.h" | ||
| #include "tensorflow/core/common_runtime/device_set.h" | ||
| #include "tensorflow/core/grappler/clusters/cluster.h" | ||
| #include "tensorflow/core/grappler/grappler_item.h" | ||
| #include "tensorflow/core/lib/core/status.h" | ||
| #include "tensorflow/core/lib/core/status_test_util.h" | ||
| #include "tensorflow/core/platform/test.h" | ||
| #include "tensorflow/core/protobuf/config.pb.h" // NOLINT | ||
| #include "tensorflow/core/public/session.h" | ||
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| #if GOOGLE_CUDA | ||
| #if GOOGLE_TENSORRT | ||
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| namespace tensorflow { | ||
| namespace tensorrt { | ||
| namespace convert { | ||
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| class FakeCluster : public grappler::Cluster { | ||
| public: | ||
| FakeCluster() : Cluster(0) {} | ||
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| void SetDeviceSet(const DeviceSet* device_set) { device_set_ = device_set; } | ||
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| const DeviceSet* GetDeviceSet() const override { return device_set_; } | ||
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| string type() const override { return ""; } | ||
| Status Provision() override { return Status::OK(); } | ||
| Status Initialize(const grappler::GrapplerItem& item) override { | ||
| return Status::OK(); | ||
| } | ||
| virtual Status Run(const GraphDef& graph_def, | ||
| const std::vector<std::pair<string, Tensor>>& feed, | ||
| const std::vector<string>& fetch, | ||
| RunMetadata* metadata) override { | ||
| return Status::OK(); | ||
| } | ||
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| private: | ||
| const DeviceSet* device_set_; | ||
| }; | ||
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| TEST(ConvertGraphTest, GetDeviceAndAllocator) { | ||
| ConversionParams params; | ||
| EngineInfo engine_info; | ||
| { | ||
| // params.cluster is not set, and no gpu device is available. | ||
| auto result = GetDeviceAndAllocator(params, engine_info); | ||
| EXPECT_EQ(-1, result.first); | ||
| EXPECT_EQ(nullptr, result.second); | ||
| } | ||
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| // Create a session with two (virtual) gpu device. | ||
| SessionOptions options; | ||
| ConfigProto* config = &options.config; | ||
| GPUOptions* gpu_options = config->mutable_gpu_options(); | ||
| auto virtual_devices = | ||
| gpu_options->mutable_experimental()->add_virtual_devices(); | ||
| virtual_devices->add_memory_limit_mb(200); | ||
| virtual_devices->add_memory_limit_mb(200); | ||
| std::unique_ptr<Session> session(NewSession(options)); | ||
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| { | ||
| // params.cluster is not set, should find and return first gpu id and | ||
| // corresponding allocator. | ||
| auto result = GetDeviceAndAllocator(params, engine_info); | ||
| EXPECT_EQ(0, result.first); | ||
| EXPECT_NE(nullptr, result.second); | ||
| EXPECT_EQ("GPU_0_bfc", result.second->Name()); | ||
| } | ||
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| FakeCluster cluster; | ||
| params.cluster = &cluster; | ||
| { | ||
| // params.cluster->GetDeviceSet() returns null, should find and return first | ||
| // gpu id and corresponding allocator. | ||
| auto result = GetDeviceAndAllocator(params, engine_info); | ||
| EXPECT_EQ(0, result.first); | ||
| EXPECT_NE(nullptr, result.second); | ||
| EXPECT_EQ("GPU_0_bfc", result.second->Name()); | ||
| } | ||
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| // Build the DeviceSet. | ||
| DeviceSet device_set; | ||
| const DeviceMgr* device_mgr = nullptr; | ||
| TF_ASSERT_OK(session->LocalDeviceManager(&device_mgr)); | ||
| for (auto d : device_mgr->ListDevices()) { | ||
| device_set.AddDevice(d); | ||
| } | ||
| cluster.SetDeviceSet(&device_set); | ||
| { | ||
| // engine_info.device is not set, should find and return first gpu id and | ||
| // corresponding allocator. | ||
| auto result = GetDeviceAndAllocator(params, engine_info); | ||
| EXPECT_EQ(0, result.first); | ||
| EXPECT_NE(nullptr, result.second); | ||
| EXPECT_EQ("GPU_0_bfc", result.second->Name()); | ||
| } | ||
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| engine_info.device = "/GPU:1"; | ||
| { | ||
| // Set to use second device. | ||
| auto result = GetDeviceAndAllocator(params, engine_info); | ||
| EXPECT_EQ(0, result.first); | ||
| EXPECT_NE(nullptr, result.second); | ||
| EXPECT_EQ("GPU_1_bfc", result.second->Name()); | ||
| } | ||
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| engine_info.device = "/GPU:3"; | ||
| { | ||
| // Set to use nonexistent device. | ||
| auto result = GetDeviceAndAllocator(params, engine_info); | ||
| EXPECT_EQ(-1, result.first); | ||
| EXPECT_EQ(nullptr, result.second); | ||
| } | ||
| } | ||
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| } // namespace convert | ||
| } // namespace tensorrt | ||
| } // namespace tensorflow | ||
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| #endif // GOOGLE_TENSORRT | ||
| #endif // GOOGLE_CUDA |
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The max is hard coded to 100.
How would this work in a virtual environment (e.g. with kubernetes) where a single GPU can be shared by possibly more than 100 users?
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That's a good point. Currently TfGpuId is always starting from 0, so if there are any gpu device initialized before, gpu 0 should always be available. Note that TfGpuId is a virtual identifier of the gpu device owned by the process, not the physical gpu id. But if we hard coded 0 here, changes to BaseGpuDevice initialization flow can break the integration, so I added the loop here to reduce that risk.
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Got it. Looks okay.