wehub-resource-sync
96 lines
3.6 KiB
C++
96 lines
3.6 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/index_sample_kernel.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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namespace phi {
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template <typename T, typename Context>
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void IndexSampleKernel(const Context& dev_ctx,
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const DenseTensor& x,
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const DenseTensor& index,
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DenseTensor* out) {
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if (out && out->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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auto index_type = index.dtype();
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bool index_type_match =
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index_type == DataType::INT32 || index_type == DataType::INT64;
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PADDLE_ENFORCE_EQ(index_type_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_type),
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DataTypeToString(DataType::INT32),
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DataTypeToString(DataType::INT64)));
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using XPUType = typename XPUTypeTrait<T>::Type;
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auto input_dim = x.dims();
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auto index_dim = index.dims();
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int64_t batch_size = input_dim[0];
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int64_t input_length = input_dim[1];
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int64_t index_length = index_dim[1];
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const T* in_data = x.data<T>();
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T* out_data = dev_ctx.template Alloc<T>(out);
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// template<typename T, typename TID> DLL_EXPORT int gather_element(Context*
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// xpu_ctx, const T* x, const TID* index, T* y, const std::vector<int64_t>&
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// xshape, const std::vector<int64_t>& idxshape, int64_t axis);
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if (index_type == DataType::INT64) {
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const int64_t* index_data = index.data<int64_t>();
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int r =
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xpu::gather<XPUType, int64_t>(dev_ctx.x_context(),
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reinterpret_cast<const XPUType*>(in_data),
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index_data,
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reinterpret_cast<XPUType*>(out_data),
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{batch_size, input_length},
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{batch_size, index_length},
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1);
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PADDLE_ENFORCE_XDNN_SUCCESS(r, "gather");
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} else if (index_type == DataType::INT32) {
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const int* index_data = index.data<int>();
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int r =
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xpu::gather<XPUType, int32_t>(dev_ctx.x_context(),
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reinterpret_cast<const XPUType*>(in_data),
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index_data,
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reinterpret_cast<XPUType*>(out_data),
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{batch_size, input_length},
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{batch_size, index_length},
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1);
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PADDLE_ENFORCE_XDNN_SUCCESS(r, "gather");
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}
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}
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} // namespace phi
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PD_REGISTER_KERNEL(index_sample,
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XPU,
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ALL_LAYOUT,
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phi::IndexSampleKernel,
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phi::bfloat16,
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phi::float16,
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float,
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int8_t,
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int16_t,
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int32_t,
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bool) {}
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