wehub-resource-sync
87 lines
2.5 KiB
C++
87 lines
2.5 KiB
C++
/* Copyright (c) 2022 PaddlePaddle Authors. All Rights Reserved.
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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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http://www.apache.org/licenses/LICENSE-2.0
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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 "paddle/phi/kernels/stack_kernel.h"
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#include "paddle/phi/backends/cpu/cpu_context.h"
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#include "paddle/phi/core/kernel_registry.h"
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namespace phi {
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template <typename T, typename Context>
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void StackKernel(const Context& dev_ctx,
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const std::vector<const DenseTensor*>& x,
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int axis,
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DenseTensor* out) {
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if (axis < 0) axis += (x[0]->dims().size() + 1);
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auto x_dims = x[0]->dims();
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for (int i = 0; i < x_dims.size(); i++) {
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PADDLE_ENFORCE_GE(
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x_dims[i],
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0,
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common::errors::InvalidArgument(
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"The dims of Input(X) should be greater than or equal to 0"));
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}
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// zero sized tensor case
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if (x[0]->numel() == 0) {
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dev_ctx.template Alloc<T>(out);
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auto out_dims = out->dims();
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out->Resize(out_dims);
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return;
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}
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int n = static_cast<int>(x.size());
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T* y_data = dev_ctx.template Alloc<T>(out);
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std::vector<const T*> x_datas(n);
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for (int i = 0; i < n; i++) x_datas[i] = x[i]->data<T>();
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int pre = 1, post = 1;
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auto& dim = x[0]->dims();
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for (auto i = 0; i < axis; ++i) pre *= static_cast<int>(dim[i]);
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for (auto i = axis; i < dim.size(); ++i) post *= static_cast<int>(dim[i]);
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auto x_data_arr = x_datas.data();
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size_t x_offset = 0;
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size_t y_offset = 0;
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for (int i = 0; i < pre; i++) {
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for (int j = 0; j < n; j++) {
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std::memcpy(
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y_data + y_offset, x_data_arr[j] + x_offset, post * sizeof(T));
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y_offset += post;
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}
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x_offset += post;
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}
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}
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} // namespace phi
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PD_REGISTER_KERNEL(stack,
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CPU,
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ALL_LAYOUT,
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phi::StackKernel,
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bool,
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float,
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double,
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int,
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int8_t,
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int64_t,
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int16_t,
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uint8_t,
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phi::float16,
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phi::bfloat16,
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phi::complex64,
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phi::complex128) {}
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