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https://github.com/PaddlePaddle/FastDeploy.git
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de98163efa
* Add +-*/ functions * Add same dims test case for operations * add broadcast 0 * Add broadcast dim2 testcase * Add broadcast dim3 and dim4 testcase * Add +-*/ operators * Add mixed operation * refresh code style * Add reshape op * update code style
104 lines
3.1 KiB
C++
104 lines
3.1 KiB
C++
// Copyright (c) 2022 PaddlePaddle Authors. All Rights Reserved.
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//
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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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//
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// http://www.apache.org/licenses/LICENSE-2.0
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//
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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 "fastdeploy/core/fd_tensor.h"
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#include "gtest_utils.h"
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#include "gtest/gtest.h"
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#include <array>
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#include <cstring>
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#include <vector>
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namespace fastdeploy {
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TEST(fastdeploy, fd_tensor_constructor) {
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CheckShape check_shape;
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CheckData check_data;
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FDTensor tensor1;
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check_shape(tensor1.shape, {0});
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ASSERT_EQ(tensor1.name, "");
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ASSERT_EQ(tensor1.dtype, FDDataType::INT8);
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ASSERT_EQ(tensor1.device, Device::CPU);
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std::vector<int> inputs = {2, 4, 3, 7, 1, 5};
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tensor1.SetExternalData({2, 3}, FDDataType::INT32, inputs.data());
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ASSERT_EQ(tensor1.dtype, FDDataType::INT32);
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FDTensor tensor2(tensor1);
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check_shape(tensor1.shape, {2, 3});
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ASSERT_EQ(tensor2.name, "");
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ASSERT_EQ(tensor2.dtype, FDDataType::INT32);
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ASSERT_EQ(tensor2.device, Device::CPU);
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FDTensor tensor3;
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tensor3.Resize({2, 3}, FDDataType::INT32, "tensor3");
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check_shape(tensor3.shape, {2, 3});
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ASSERT_EQ(tensor3.Nbytes(), 24);
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// Copy constructor
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FDTensor tensor4(tensor3);
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check_shape(tensor4.shape, {2, 3});
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ASSERT_EQ(tensor3.Nbytes(), tensor4.Nbytes());
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check_data(reinterpret_cast<int*>(tensor3.Data()),
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reinterpret_cast<int*>(tensor4.Data()), tensor4.Numel());
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// Move constructor
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ASSERT_NE(tensor1.external_data_ptr, nullptr);
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FDTensor tensor5(std::move(tensor1));
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ASSERT_EQ(tensor1.external_data_ptr, nullptr);
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ASSERT_EQ(tensor5.external_data_ptr, inputs.data());
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check_shape(tensor5.shape, {2, 3});
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}
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TEST(fastdeploy, fd_tensor_assignment) {
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CheckShape check_shape;
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CheckData check_data;
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FDTensor tensor1("T1");
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std::vector<int> inputs = {2, 4, 3, 7, 1, 5};
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tensor1.SetExternalData({2, 3}, FDDataType::INT32, inputs.data());
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FDTensor tensor2;
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tensor2 = tensor1;
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ASSERT_EQ(tensor2.name, "T1");
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ASSERT_EQ(tensor2.dtype, FDDataType::INT32);
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ASSERT_EQ(tensor2.device, Device::CPU);
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ASSERT_EQ(tensor2.Data(), inputs.data());
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check_shape(tensor2.shape, {2, 3});
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FDTensor tensor3;
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tensor3 = std::move(tensor1);
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ASSERT_EQ(tensor3.name, "T1");
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ASSERT_EQ(tensor3.dtype, FDDataType::INT32);
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ASSERT_EQ(tensor3.device, Device::CPU);
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ASSERT_EQ(tensor3.Data(), inputs.data());
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ASSERT_EQ(tensor1.Data(), nullptr);
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}
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TEST(fastdeploy, fd_tensor_reshape) {
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CheckShape check_shape;
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FDTensor x;
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x.Allocate({2, 3, 4, 5}, FDDataType::FP32);
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x.Reshape({-1, 3, 2, 2, 5});
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check_shape(x.Shape(), {2, 3, 2, 2, 5});
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x.Reshape({0, -1, 5, 2});
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check_shape(x.Shape(), {2, 6, 5, 2});
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x.Reshape({2, 3, 0, 0, 2});
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check_shape(x.Shape(), {2, 3, 5, 2, 2});
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}
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} // namespace fastdeploy
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