mirror of
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
90 lines
2.8 KiB
C++
90 lines
2.8 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/elementwise.h"
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#include "fastdeploy/function/eigen.h"
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#include "fastdeploy/function/elementwise_base.h"
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#include "fastdeploy/function/elementwise_functor.h"
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#include "fastdeploy/utils/utils.h"
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#include <algorithm>
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namespace fastdeploy {
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namespace function {
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DEFINE_ELEMENTWISE_OP(Add);
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DEFINE_ELEMENTWISE_OP(Multiply);
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DEFINE_ELEMENTWISE_OP(Subtract);
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DEFINE_ELEMENTWISE_OP(Divide);
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void Add(const FDTensor& x, const FDTensor& y, FDTensor* out) {
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FD_VISIT_ALL_TYPES(x.dtype, "AddRawKernel",
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([&] { AddRawKernel<data_t>()(x, y, -1, out); }));
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}
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void Subtract(const FDTensor& x, const FDTensor& y, FDTensor* out) {
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FD_VISIT_ALL_TYPES(x.dtype, "SubtractRawKernel",
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([&] { SubtractRawKernel<data_t>()(x, y, -1, out); }));
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}
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void Multiply(const FDTensor& x, const FDTensor& y, FDTensor* out) {
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FD_VISIT_ALL_TYPES(x.dtype, "MultiplyRawKernel",
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([&] { MultiplyRawKernel<data_t>()(x, y, -1, out); }));
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}
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void Divide(const FDTensor& x, const FDTensor& y, FDTensor* out) {
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FD_VISIT_ALL_TYPES(x.dtype, "DivideRawKernel",
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([&] { DivideRawKernel<data_t>()(x, y, -1, out); }));
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}
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template <typename T> struct MaximumRawKernel {
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void operator()(const FDTensor& x, const FDTensor& y, int axis,
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FDTensor* out) {
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ElementwiseCompute<MaximumFunctor<T>, T>(x, y, axis, MaximumFunctor<T>(),
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out);
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}
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};
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void Maximum(const FDTensor& x, const FDTensor& y, FDTensor* out) {
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FD_VISIT_ALL_TYPES(x.dtype, "MaximumRawKernel",
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([&] { MaximumRawKernel<data_t>()(x, y, -1, out); }));
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}
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} // namespace function
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FDTensor operator+(const FDTensor& x, const FDTensor& y) {
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FDTensor out;
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function::Add(x, y, &out);
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return out;
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}
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FDTensor operator-(const FDTensor& x, const FDTensor& y) {
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FDTensor out;
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function::Subtract(x, y, &out);
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return out;
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}
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FDTensor operator*(const FDTensor& x, const FDTensor& y) {
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FDTensor out;
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function::Multiply(x, y, &out);
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return out;
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}
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FDTensor operator/(const FDTensor& x, const FDTensor& y) {
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FDTensor out;
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function::Divide(x, y, &out);
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return out;
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}
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} // namespace fastdeploy
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