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79 lines
2.5 KiB
C++
79 lines
2.5 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/cumprod.h"
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namespace fastdeploy {
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namespace function {
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void GetCumprodDimInfo(const std::vector<int64_t>& dim, int cumprod_dim,
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size_t* outer_dim, size_t* mid_dim, size_t* inner_dim) {
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int dim_size = dim.size();
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FDASSERT(cumprod_dim >= -dim_size,
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"The input dim of CumprodOp should be larger than the opposite "
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"rank of input x which is %d. But received dim = %d",
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-dim_size, cumprod_dim);
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FDASSERT(cumprod_dim < dim_size,
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"The input dim of CumprodOp should be smaller than the "
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"rank of input x which is %d. But received dim = %d",
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dim_size, cumprod_dim);
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if (cumprod_dim < 0)
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cumprod_dim += dim_size;
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*outer_dim = 1;
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for (int i = 0; i < cumprod_dim; ++i) {
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*outer_dim *= dim[i];
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}
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*mid_dim = dim[cumprod_dim];
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*inner_dim = 1;
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for (int i = cumprod_dim + 1; i < dim_size; ++i) {
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*inner_dim *= dim[i];
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}
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}
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template <typename T>
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void CumprodKernel(const FDTensor& x, FDTensor* out, int axis) {
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auto* x_data = reinterpret_cast<const T*>(x.Data());
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auto shape = x.Shape();
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size_t outer_dim = 1;
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size_t mid_dim = 1;
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size_t inner_dim = 1;
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GetCumprodDimInfo(shape, axis, &outer_dim, &mid_dim, &inner_dim);
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out->Allocate(x.Shape(), x.Dtype());
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auto* out_data = reinterpret_cast<T*>(out->Data());
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for (size_t i = 0; i < outer_dim; i++) {
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for (size_t j = 0; j < mid_dim; j++) {
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for (size_t k = 0; k < inner_dim; k++) {
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size_t pos = i * mid_dim * inner_dim + j * inner_dim + k;
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if (j == 0) {
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out_data[pos] = x_data[pos];
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} else {
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out_data[pos] = out_data[pos - inner_dim] * x_data[pos];
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}
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}
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}
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}
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}
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void Cumprod(const FDTensor& x, FDTensor* out, int axis) {
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FD_VISIT_INT_FLOAT_TYPES(x.dtype, "CumprodKernel",
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([&] { CumprodKernel<data_t>(x, out, axis); }));
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}
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} // namespace function
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} // namespace fastdeploy
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