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https://github.com/PaddlePaddle/FastDeploy.git
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129dda7809
* Add sort function * Add isfinite function * upgrade isinf isnan * Add Scalar to FDTensor * Add floor, ceil function * add cast functions * Update out_tmp * Update quantile * add gather scatter along axis * finish quantile function * Add quantile unittest * refresh code style for test source code * Add comments * Add full function * Add scalar to fd tensor * Add full unittest * Add functions headers * move fdtensor operators to fastdeploy namespace
62 lines
2.3 KiB
C++
62 lines
2.3 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 "fastdeploy/function/softmax.h"
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#include "glog/logging.h"
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#include "gtest_utils.h"
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#include "gtest/gtest.h"
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#include <vector>
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namespace fastdeploy {
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namespace function {
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TEST(fastdeploy, softmax) {
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FDTensor input, input1, output;
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CheckShape check_shape;
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CheckData check_data;
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std::vector<float> inputs = {1, 2, 3, 4, 5, 6};
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auto inputs1 = inputs;
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std::vector<float> expected_result_axis0 = {
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0.04742587, 0.04742587, 0.04742587, 0.95257413, 0.95257413, 0.95257413};
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std::vector<float> expected_result_axis1 = {
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0.09003057, 0.24472846, 0.66524088, 0.09003057, 0.24472846, 0.66524088};
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input.SetExternalData({2, 3}, FDDataType::FP32, inputs.data());
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input1.SetExternalData({2, 3}, FDDataType::FP32, inputs1.data());
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// axis = 0
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Softmax(input, &output, 0);
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check_shape(output.shape, {2, 3});
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check_data(reinterpret_cast<const float*>(output.Data()),
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expected_result_axis0.data(), expected_result_axis0.size());
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// Test the case when output eqauls to input
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Softmax(input, &input, 0);
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check_shape(output.shape, {2, 3});
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check_data(reinterpret_cast<const float*>(input.Data()),
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expected_result_axis0.data(), expected_result_axis0.size());
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// axis = 1
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Softmax(input1, &output, 1);
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check_shape(output.shape, {2, 3});
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check_data(reinterpret_cast<const float*>(output.Data()),
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expected_result_axis1.data(), expected_result_axis1.size());
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// Test the case when output eqauls to input
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Softmax(input1, &input1, 1);
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check_shape(output.shape, {2, 3});
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check_data(reinterpret_cast<const float*>(input1.Data()),
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expected_result_axis1.data(), expected_result_axis1.size());
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}
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} // namespace function
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} // namespace fastdeploy
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