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https://github.com/PaddlePaddle/FastDeploy.git
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e93bf6e35c
* Add InferShape func for all the vision processors * fix infer shape of limit short * Fix infer shape bug of stride_pad * revert modify of processor * add function pad
93 lines
3.4 KiB
C++
93 lines
3.4 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 <numeric>
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#include <vector>
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#include "fastdeploy/core/fd_tensor.h"
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#include "fastdeploy/function/pad.h"
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#include "glog/logging.h"
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#include "gtest/gtest.h"
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#include "gtest_utils.h"
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namespace fastdeploy {
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TEST(fastdeploy, pad_2d) {
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FDTensor input, output;
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CheckShape check_shape;
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CheckData check_data;
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CheckType check_type;
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std::vector<float> inputs = {2, 4, 3,
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7, 1, 5};
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std::vector<float> expected_result = {2.2, 2.2, 2.2, 2.2, 2.2,
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2.2, 2, 4, 3, 2.2,
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2.2, 7, 1, 5, 2.2,
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2.2, 2.2, 2.2, 2.2, 2.2};
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input.SetExternalData({2, 3}, FDDataType::FP32, inputs.data());
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Pad(input, &output, {1, 1, 1, 1}, 2.2);
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check_shape(output.shape, {4, 5});
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check_data(reinterpret_cast<const float*>(output.Data()),
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expected_result.data(), expected_result.size());
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check_type(input.dtype, output.dtype);
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}
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TEST(fastdeploy, pad_2d_int32_t) {
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FDTensor input, output;
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CheckShape check_shape;
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CheckData check_data;
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CheckType check_type;
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std::vector<int32_t> inputs = {2, 4, 3,
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7, 1, 5};
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std::vector<int32_t> expected_result = {2, 2, 2, 2, 2,
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2, 2, 4, 3, 2,
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2, 7, 1, 5, 2,
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2, 2, 2, 2, 2};
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input.SetExternalData({2, 3}, FDDataType::INT32, inputs.data());
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Pad(input, &output, {1, 1, 1, 1}, 2.2);
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check_shape(output.shape, {4, 5});
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check_data(reinterpret_cast<const int32_t*>(output.Data()),
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expected_result.data(), expected_result.size());
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check_type(input.dtype, output.dtype);
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}
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//TEST(fastdeploy, transpose_5d) {
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// FDTensor input, output;
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// CheckShape check_shape;
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// CheckData check_data;
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//
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// std::vector<int64_t> input_shape = {2, 1, 3, 1, 2};
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// auto total_size = std::accumulate(input_shape.begin(), input_shape.end(), 1,
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// std::multiplies<int64_t>());
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// std::vector<int> inputs(total_size, 1);
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// std::iota(inputs.begin(), inputs.end(), 1);
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// std::vector<int> expected_result = {1, 3, 5, 2, 4, 6, 7, 9, 11, 8, 10, 12};
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// input.SetExternalData(input_shape, FDDataType::INT32, inputs.data());
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//
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// Transpose(input, &output, {0, 1, 4, 3, 2});
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// check_shape(output.shape, {2, 1, 2, 1, 3});
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// check_data(reinterpret_cast<const int*>(output.Data()),
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// expected_result.data(), expected_result.size());
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//
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// Transpose(input, &input, {0, 1, 4, 3, 2});
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// check_shape(input.shape, {2, 1, 2, 1, 3});
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// check_data(reinterpret_cast<const int*>(input.Data()), expected_result.data(),
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// expected_result.size());
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//}
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} // namespace fastdeploy
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