mirror of
https://github.com/PaddlePaddle/FastDeploy.git
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52 lines
1.7 KiB
C++
52 lines
1.7 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/function/linspace.h"
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namespace fastdeploy {
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namespace function {
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template <typename T>
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void LinspaceKernel(double start, double end, int num, FDTensor* out) {
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FDASSERT(
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num > 0,
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"The num of linspace op should be larger than 0, but received num is %d",
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num);
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out->Allocate({num}, TypeToDataType<T>::dtype);
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T* out_data = reinterpret_cast<T*>(out->Data());
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if (num > 1) {
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// step should be of double type for all types
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double step = (static_cast<double>(end - start)) / (num - 1);
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int half_num = num / 2;
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for (int i = 0; i < num; ++i) {
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if (i < half_num) {
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out_data[i] = static_cast<T>(start + step * i);
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} else {
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out_data[i] = static_cast<T>(end - step * (num - i - 1));
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}
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}
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} else {
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out_data[0] = static_cast<T>(start);
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}
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}
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void Linspace(double start, double end, int num, FDTensor* out,
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FDDataType dtype) {
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FD_VISIT_INT_FLOAT_TYPES(dtype, "LinspaceKernel", ([&] {
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LinspaceKernel<data_t>(start, end, num, out);
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}));
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}
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} // namespace function
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} // namespace fastdeploy
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