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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
42 lines
1.5 KiB
C++
42 lines
1.5 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/full.h"
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#include "fastdeploy/function/eigen.h"
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#include <algorithm>
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namespace fastdeploy {
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namespace function {
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template <typename T> void FullValue(FDTensor* tensor, const Scalar& val) {
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auto t = EigenVector<T>::Flatten(*tensor);
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auto& place = *EigenDeviceWrapper::GetInstance()->GetDevice();
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t.device(place) = t.constant(val.to<T>());
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}
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void Full(const Scalar& value, const std::vector<int64_t>& shape, FDTensor* out,
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FDDataType dtype) {
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FD_VISIT_ALL_TYPES(dtype, "Full", ([&] {
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out->Allocate(shape, dtype);
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FullValue<data_t>(out, value);
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}));
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}
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void FullLike(const FDTensor& x, const Scalar& value, FDTensor* out,
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FDDataType dtype) {
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Full(value, x.Shape(), out, dtype);
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}
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} // namespace function
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} // namespace fastdeploy
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