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Fix #41630: include max_seq_length in cudnn descriptor cache key
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| Original file line number | Diff line number | Diff line change |
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| @@ -0,0 +1,101 @@ | ||
| /* Copyright 2016 The TensorFlow Authors. All Rights Reserved. | ||
| 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 | ||
| http://www.apache.org/licenses/LICENSE-2.0 | ||
| 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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|
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| #ifndef TENSORFLOW_CORE_KERNELS_CUDNN_RNN_OPS_H | ||
| #define TENSORFLOW_CORE_KERNELS_CUDNN_RNN_OPS_H 1 | ||
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| #include "tensorflow/core/framework/tensor.h" | ||
| #include "tensorflow/core/framework/tensor_shape.h" | ||
| #include "tensorflow/core/framework/tensor_types.h" | ||
| #include "tensorflow/core/lib/strings/stringprintf.h" | ||
| #include "tensorflow/core/util/use_cudnn.h" | ||
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| #if GOOGLE_CUDA || TENSORFLOW_USE_ROCM | ||
| #include "tensorflow/core/platform/stream_executor.h" | ||
| #include "tensorflow/core/util/stream_executor_util.h" | ||
| #endif // GOOGLE_CUDA || TENSORFLOW_USE_ROCM | ||
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| namespace tensorflow { | ||
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| namespace { | ||
| using se::dnn::AlgorithmConfig; | ||
| using se::dnn::AlgorithmDesc; | ||
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| uint64 HashList(const std::vector<int>& list) { | ||
| if (list.empty()) { | ||
| return 0; | ||
| } | ||
| uint64 hash_code = list[0]; | ||
| for (int i = 1; i < list.size(); i++) { | ||
| hash_code = Hash64Combine(hash_code, list[i]); | ||
| } | ||
| return hash_code; | ||
| } | ||
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| // A helper class that collects the shapes to describe a RNN model. | ||
| struct CudnnRnnModelShapes { | ||
| int num_layers; | ||
| int input_size; | ||
| int num_units; | ||
| int dir_count; | ||
| int max_seq_length; | ||
| int batch_size; | ||
| int cell_num_units = 0; | ||
| // If you add new field to this structure, please take care of | ||
| // updating IsCompatibleWith() below as well as the hash function in | ||
| // CudnnRnnConfigHasher. | ||
| TensorShape input_shape; | ||
| TensorShape output_shape; | ||
| TensorShape hidden_state_shape; | ||
| TensorShape cell_state_shape; | ||
| // At present only fields related to cached RnnDescriptor are concerned. | ||
| bool IsCompatibleWith(const CudnnRnnModelShapes& rhs) const { | ||
| return num_layers == rhs.num_layers && input_size == rhs.input_size && | ||
| num_units == rhs.num_units && dir_count == rhs.dir_count && | ||
| cell_num_units == rhs.cell_num_units && max_seq_length == rhs.max_seq_length; | ||
| } | ||
| string DebugString() const { | ||
| return strings::Printf( | ||
| "[num_layers, input_size, num_units, dir_count, max_seq_length, " | ||
| "batch_size, cell_num_units]: [%d, %d, %d, %d, %d, %d, %d] ", | ||
| num_layers, input_size, num_units, dir_count, max_seq_length, | ||
| batch_size, cell_num_units); | ||
| } | ||
| }; | ||
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| // Utility class for using CudnnRnnConfig and AlgorithmDesc pair a hash table | ||
| // key. | ||
| struct CudnnRnnConfigHasher { | ||
| uint64 operator()( | ||
| const std::pair<CudnnRnnModelShapes, absl::optional<AlgorithmDesc>>& | ||
| to_hash) const { | ||
| auto& shapes = to_hash.first; | ||
| auto& algo_desc = to_hash.second; | ||
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| uint64 hash = | ||
| HashList({shapes.num_layers, shapes.input_size, shapes.num_units, | ||
| shapes.dir_count, shapes.max_seq_length, shapes.batch_size}); | ||
| if (algo_desc.has_value()) { | ||
| hash = Hash64Combine(hash, algo_desc->hash()); | ||
| } | ||
| return hash; | ||
| } | ||
| }; | ||
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| } | ||
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| } | ||
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| #endif // TENSORFLOW_CORE_KERNELS_CUDNN_RNN_OPS_H |
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| Original file line number | Diff line number | Diff line change |
|---|---|---|
| @@ -0,0 +1,129 @@ | ||
| /* Copyright 2015 The TensorFlow Authors. All Rights Reserved. | ||
| 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 | ||
| http://www.apache.org/licenses/LICENSE-2.0 | ||
| 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/core/common_runtime/kernel_benchmark_testlib.h" | ||
| #include "tensorflow/core/framework/fake_input.h" | ||
| #include "tensorflow/core/framework/node_def_builder.h" | ||
| #include "tensorflow/core/framework/tensor.h" | ||
| #include "tensorflow/core/kernels/cudnn_rnn_ops.h" | ||
| #include "tensorflow/core/kernels/ops_testutil.h" | ||
| #include "tensorflow/core/platform/test.h" | ||
| #include "tensorflow/core/platform/test_benchmark.h" | ||
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| namespace tensorflow { | ||
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| class CudnnRnnModelShapesTest : public OpsTestBase {}; | ||
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| TEST_F(CudnnRnnModelShapesTest, NonVariable_SeqLength) { | ||
| CudnnRnnModelShapes model_shape_a; | ||
| model_shape_a.num_layers = 1; | ||
| model_shape_a.input_size = 2; | ||
| model_shape_a.num_units = 1; | ||
| model_shape_a.dir_count = 0; | ||
| model_shape_a.max_seq_length = 1; | ||
| model_shape_a.cell_num_units = 2; | ||
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| CudnnRnnModelShapes model_shape_b; | ||
| model_shape_b.num_layers = 1; | ||
| model_shape_b.input_size = 2; | ||
| model_shape_b.num_units = 1; | ||
| model_shape_b.dir_count = 0; | ||
| model_shape_b.max_seq_length = 1; | ||
| model_shape_b.cell_num_units = 2; | ||
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| EXPECT_TRUE(model_shape_a.IsCompatibleWith(model_shape_b)); | ||
| } | ||
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| TEST_F(CudnnRnnModelShapesTest, Variable_SeqLength) { | ||
| CudnnRnnModelShapes model_shape_a; | ||
| model_shape_a.num_layers = 1; | ||
| model_shape_a.input_size = 2; | ||
| model_shape_a.num_units = 1; | ||
| model_shape_a.dir_count = 0; | ||
| model_shape_a.max_seq_length = 1; | ||
| model_shape_a.cell_num_units = 2; | ||
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| CudnnRnnModelShapes model_shape_b; | ||
| model_shape_b.num_layers = 1; | ||
| model_shape_b.input_size = 2; | ||
| model_shape_b.num_units = 1; | ||
| model_shape_b.dir_count = 0; | ||
| model_shape_b.max_seq_length = 2; | ||
| model_shape_b.cell_num_units = 2; | ||
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| EXPECT_FALSE(model_shape_a.IsCompatibleWith(model_shape_b)); | ||
| } | ||
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| class CudnnRnnConfigHasherTest : public OpsTestBase {}; | ||
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| TEST_F(CudnnRnnConfigHasherTest, NonVariable_SeqLength) { | ||
| AlgorithmConfig algo_config; | ||
| AlgorithmDesc algo_desc(DebugCudnnRnnAlgo(), DebugCudnnRnnUseTensorOps()); | ||
| algo_config.set_algorithm(algo_desc); | ||
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| CudnnRnnModelShapes model_shape_a; | ||
| model_shape_a.num_layers = 1; | ||
| model_shape_a.input_size = 2; | ||
| model_shape_a.num_units = 1; | ||
| model_shape_a.dir_count = 0; | ||
| model_shape_a.max_seq_length = 1; | ||
| model_shape_a.batch_size = 1; | ||
| model_shape_a.cell_num_units = 2; | ||
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| CudnnRnnModelShapes model_shape_b; | ||
| model_shape_b.num_layers = 1; | ||
| model_shape_b.input_size = 2; | ||
| model_shape_b.num_units = 1; | ||
| model_shape_b.dir_count = 0; | ||
| model_shape_b.max_seq_length = 1; | ||
| model_shape_b.batch_size = 1; | ||
| model_shape_b.cell_num_units = 2; | ||
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| uint64 hash_a = CudnnRnnConfigHasher()(std::make_pair(model_shape_a, algo_config.algorithm())); | ||
| uint64 hash_b = CudnnRnnConfigHasher()(std::make_pair(model_shape_b, algo_config.algorithm())); | ||
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| EXPECT_TRUE(hash_a == hash_b); | ||
| } | ||
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| TEST_F(CudnnRnnConfigHasherTest, Variable_SeqLength) { | ||
| AlgorithmConfig algo_config; | ||
| AlgorithmDesc algo_desc(DebugCudnnRnnAlgo(), DebugCudnnRnnUseTensorOps()); | ||
| algo_config.set_algorithm(algo_desc); | ||
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| CudnnRnnModelShapes model_shape_a; | ||
| model_shape_a.num_layers = 1; | ||
| model_shape_a.input_size = 2; | ||
| model_shape_a.num_units = 1; | ||
| model_shape_a.dir_count = 0; | ||
| model_shape_a.max_seq_length = 1; | ||
| model_shape_a.batch_size = 1; | ||
| model_shape_a.cell_num_units = 2; | ||
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| CudnnRnnModelShapes model_shape_b; | ||
| model_shape_b.num_layers = 1; | ||
| model_shape_b.input_size = 2; | ||
| model_shape_b.num_units = 1; | ||
| model_shape_b.dir_count = 0; | ||
| model_shape_b.max_seq_length = 2; | ||
| model_shape_b.batch_size = 1; | ||
| model_shape_b.cell_num_units = 2; | ||
|
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| uint64 hash_a = CudnnRnnConfigHasher()(std::make_pair(model_shape_a, algo_config.algorithm())); | ||
| uint64 hash_b = CudnnRnnConfigHasher()(std::make_pair(model_shape_b, algo_config.algorithm())); | ||
|
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| EXPECT_TRUE(hash_a != hash_b); | ||
| } | ||
|
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| } // end namespace tensorflow |