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							2.1 KiB
						
					
					
				
			
		
		
	
	
							63 lines
						
					
					
						
							2.1 KiB
						
					
					
				/* Copyright (c) 2016 PaddlePaddle Authors. All Rights Reserve.
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Licensed under the Apache License, Version 2.0 (the "License");
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you may not use this file except in compliance with the License.
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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
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distributed under the License is distributed on an "AS IS" BASIS,
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WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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See the License for the specific language governing permissions and
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limitations under the License. */
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#include <gtest/gtest.h>
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#include "FunctionTest.h"
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namespace paddle {
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void testRowConvFw(size_t batchSize, size_t dim, size_t contextLength) {
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  CpuGpuFuncCompare test("RowConv", FuncConfig());
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  test.addSequence(SequenceIdArg(TensorShape{batchSize}));
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  test.addInputs(SequenceArg(VALUE_TYPE_FLOAT, TensorShape{batchSize, dim}));
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  test.addInputs(BufferArg(VALUE_TYPE_FLOAT, TensorShape{contextLength, dim}));
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  test.addOutputs(SequenceArg(VALUE_TYPE_FLOAT, TensorShape{batchSize, dim}),
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                  ADD_TO);
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  test.run();
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}
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void testRowConvBw(size_t batchSize, size_t dim, size_t contextLength) {
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  CpuGpuFuncCompare test("RowConvGrad", FuncConfig());
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  test.addSequence(SequenceIdArg(TensorShape{batchSize}));
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  test.addInputs(SequenceArg(VALUE_TYPE_FLOAT, TensorShape{batchSize, dim}));
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  test.addInputs(SequenceArg(VALUE_TYPE_FLOAT, TensorShape{batchSize, dim}));
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  test.addInputs(BufferArg(VALUE_TYPE_FLOAT, TensorShape{contextLength, dim}));
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  test.addOutputs(SequenceArg(VALUE_TYPE_FLOAT, TensorShape{batchSize, dim}),
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                  ADD_TO);
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  test.addOutputs(BufferArg(VALUE_TYPE_FLOAT, TensorShape{contextLength, dim}),
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                  ADD_TO);
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  test.run();
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}
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TEST(RowConv, real) {
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  for (size_t numSamples : {17, 129, 2020}) {
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    for (size_t dim : {16, 512, 2560}) {
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      for (size_t context : {3, 19, 65}) {
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        VLOG(3) << " numSamples=" << numSamples << " dim=" << dim
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                << " context length=" << context;
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        testRowConvFw(numSamples, dim, context);
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        testRowConvBw(numSamples, dim, context);
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      }
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    }
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  }
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}
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}  // namespace paddle
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