wehub-resource-sync
134 lines
4.2 KiB
C++
134 lines
4.2 KiB
C++
// Copyright (c) 2023 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 "paddle/phi/kernels/take_along_axis_kernel.h"
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#include "glog/logging.h"
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#include "paddle/common/layout.h"
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#include "paddle/phi/backends/xpu/enforce_xpu.h"
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#include "paddle/phi/core/kernel_registry.h"
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#include "paddle/phi/kernels/full_kernel.h"
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namespace phi {
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template <typename T, typename Context>
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void TakeAlongAxisKernel(const Context& dev_ctx,
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const DenseTensor& x,
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const DenseTensor& index,
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int axis,
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DenseTensor* out) {
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if (index.numel() == 0) {
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dev_ctx.template Alloc<T>(out);
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return;
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}
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if (x.numel() == 0) {
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phi::Full<T, Context>(
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dev_ctx, vectorize(out->dims()), static_cast<T>(0), out);
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return;
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}
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out->Resize(index.dims());
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dev_ctx.template Alloc<T>(out);
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if (out->numel() == 0) {
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return;
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}
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if (x.numel() == 0 || index.numel() == 0) return;
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const auto& index_dtype = index.dtype();
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bool index_dtype_match =
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index_dtype == DataType::INT32 || index_dtype == DataType::INT64;
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PADDLE_ENFORCE_EQ(index_dtype_match,
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true,
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errors::InvalidArgument(
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"Input(Index) holds the wrong type, it holds %s, but "
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"desires to be %s or %s",
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DataTypeToString(index_dtype),
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DataTypeToString(DataType::INT32),
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DataTypeToString(DataType::INT64)));
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std::vector<int64_t> x_shape(x.dims().size());
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for (int i = 0; i < x.dims().size(); ++i) {
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x_shape[i] = x.dims()[i];
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}
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std::vector<int64_t> index_shape(index.dims().size());
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for (int i = 0; i < index.dims().size(); ++i) {
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index_shape[i] = index.dims()[i];
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}
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if (x_shape.size() <= 1 && index_shape.size() <= 1) {
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for (int i = x_shape.size(); i < 2; ++i) {
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x_shape.push_back(1);
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index_shape.push_back(1);
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}
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}
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using XPUType = typename XPUTypeTrait<T>::Type;
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int r = 0;
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#ifndef PADDLE_WITH_XPU_PLUGIN
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if (index_dtype == DataType::INT32) {
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r = xpu::gather<XPUType, int>(dev_ctx.x_context(),
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reinterpret_cast<const XPUType*>(x.data<T>()),
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index.data<int>(),
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reinterpret_cast<XPUType*>(out->data<T>()),
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x_shape,
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index_shape,
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axis);
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} else {
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r = xpu::gather<XPUType, int64_t>(
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dev_ctx.x_context(),
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reinterpret_cast<const XPUType*>(x.data<T>()),
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index.data<int64_t>(),
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reinterpret_cast<XPUType*>(out->data<T>()),
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x_shape,
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index_shape,
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axis);
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}
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PADDLE_ENFORCE_XDNN_SUCCESS(r, "gather");
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#else
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if (index_dtype == DataType::INT32) {
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r = xpu::plugin::take_along_axis<XPUType, int>(
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dev_ctx.x_context(),
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reinterpret_cast<const XPUType*>(x.data<T>()),
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index.data<int>(),
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reinterpret_cast<XPUType*>(out->data<T>()),
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x_shape,
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index_shape,
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axis);
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} else {
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r = xpu::plugin::take_along_axis<XPUType, int64_t>(
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dev_ctx.x_context(),
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reinterpret_cast<const XPUType*>(x.data<T>()),
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index.data<int64_t>(),
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reinterpret_cast<XPUType*>(out->data<T>()),
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x_shape,
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index_shape,
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axis);
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}
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PADDLE_ENFORCE_XDNN_SUCCESS(r, "take_along_axis");
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#endif
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}
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} // namespace phi
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PD_REGISTER_KERNEL(take_along_axis,
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XPU,
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ALL_LAYOUT,
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phi::TakeAlongAxisKernel,
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phi::float16,
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phi::bfloat16,
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float) {}
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