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91 lines
3.0 KiB
91 lines
3.0 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 "BufferArg.h"
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#include <gtest/gtest.h>
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#include "Function.h"
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#include "paddle/math/MemoryHandle.h"
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namespace paddle {
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TEST(BufferTest, BufferArg) {
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TensorShape shape({8, 10});
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CpuMemoryHandle memory(shape.getElements() *
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sizeOfValuType(VALUE_TYPE_FLOAT));
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BufferArg buffer(memory.getBuf(), VALUE_TYPE_FLOAT, shape);
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EXPECT_EQ(buffer.data(), memory.getBuf());
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}
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TEST(BufferTest, SequenceIdArg) {
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TensorShape shape({10});
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CpuMemoryHandle memory(shape.getElements() *
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sizeOfValuType(VALUE_TYPE_INT32));
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SequenceIdArg buffer(memory.getBuf(), shape);
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EXPECT_EQ(buffer.data(), memory.getBuf());
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EXPECT_EQ(buffer.numSeqs(), 9);
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}
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TEST(BufferTest, asArgument) {
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MatrixPtr matrix = Matrix::create(100, 200);
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VectorPtr vector = Vector::create(100, false);
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CpuSparseMatrix sparse(200, 300, 50);
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// prepare arguments
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BufferArgs argments;
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argments.addArg(*matrix);
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argments.addArg(*vector);
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argments.addArg(sparse);
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// function
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auto function = [=](const BufferArgs& inputs) {
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EXPECT_EQ(inputs.size(), 3);
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// check inputs[0]
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EXPECT_EQ(inputs[0].shape().ndims(), 2);
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EXPECT_EQ(inputs[0].shape()[0], 100);
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EXPECT_EQ(inputs[0].shape()[1], 200);
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EXPECT_EQ(inputs[0].data(), matrix->getData());
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EXPECT_EQ(inputs[0].matrix<DEVICE_TYPE_CPU>().getHeight(),
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matrix->getHeight());
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EXPECT_EQ(inputs[0].matrix<DEVICE_TYPE_CPU>().getWidth(),
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matrix->getWidth());
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EXPECT_EQ(inputs[0].matrix<DEVICE_TYPE_CPU>().getData(), matrix->getData());
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// check inputs[1]
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EXPECT_EQ(inputs[1].shape().ndims(), 1);
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EXPECT_EQ(inputs[1].shape()[0], 100);
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EXPECT_EQ(inputs[1].data(), vector->getData());
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CpuVector inVector = inputs[1].vector<real, DEVICE_TYPE_CPU>();
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EXPECT_EQ(inVector.getSize(), vector->getSize());
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EXPECT_EQ(inVector.getData(), vector->getData());
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// check inputs[2]
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EXPECT_EQ(inputs[2].shape().ndims(), 2);
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EXPECT_EQ(inputs[2].shape()[0], 200);
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EXPECT_EQ(inputs[2].shape()[1], 300);
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EXPECT_EQ(inputs[2].data(), sparse.getData());
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// CHECK_EQ(inputs[2].sparse().nnz(), 50);
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// CHECK_EQ(inputs[2].sparse().dataFormat(), SPARSE_CSR_FORMAT);
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// CHECK_EQ(inputs[2].sparse().dataType(), SPARSE_FLOAT_VALUE);
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EXPECT_EQ(inputs[2].sparse().getRowBuf(), sparse.getRows());
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EXPECT_EQ(inputs[2].sparse().getColBuf(), sparse.getCols());
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};
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// call function
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function(argments);
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}
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} // namespace paddle
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