// Copyright (c) 2022 PaddlePaddle Authors. All Rights Reserved. // // Licensed under the Apache License, Version 2.0 (the "License"); // you may not use this file except in compliance with the License. // You may obtain a copy of the License at // // http://www.apache.org/licenses/LICENSE-2.0 // // Unless required by applicable law or agreed to in writing, software // distributed under the License is distributed on an "AS IS" BASIS, // WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. // See the License for the specific language governing permissions and // limitations under the License. #include "paddle/phi/kernels/index_select_kernel.h" #include "paddle/phi/backends/xpu/enforce_xpu.h" #include "paddle/phi/common/memory_utils.h" #include "paddle/phi/core/kernel_registry.h" #include "paddle/phi/core/utils/data_type.h" namespace phi { template void IndexSelectKernel(const Context& dev_ctx, const DenseTensor& x, const DenseTensor& index, int dim, DenseTensor* output) { if (output && output->numel() == 0) { dev_ctx.template Alloc(output); return; } auto input_dim = x.dims(); dim = dim >= 0 ? dim : dim + input_dim.size(); const auto& index_type = index.dtype(); bool index_type_match = index_type == DataType::INT32 || index_type == DataType::INT64; PADDLE_ENFORCE_EQ(index_type_match, true, common::errors::InvalidArgument( "Input(Index) holds the wrong type, it holds %s, but " "desires to be %s or %s", index_type, DataType::INT32, DataType::INT64)); using XPUType = typename XPUTypeTrait::Type; auto* in_data = x.data(); std::vector in_shape = vectorize(input_dim); int64_t index_len = output->dims()[dim]; dev_ctx.template Alloc(output); int r = 0; xpu::ctx_guard RAII_GUARD(dev_ctx.x_context()); int8_t* index_ptr = nullptr; // temp xpu buffer int byte_times = SizeOf(index_type); if (index.place() == CPUPlace()) { index_ptr = RAII_GUARD.alloc_l3_or_gm(byte_times * index.numel()); PADDLE_ENFORCE_XDNN_NOT_NULL(index_ptr); const void* cpu_idx_data = nullptr; if (index_type == DataType::INT64) { cpu_idx_data = reinterpret_cast(index.data()); } else if (index_type == DataType::INT32) { cpu_idx_data = reinterpret_cast(index.data()); } memory_utils::Copy(dev_ctx.GetPlace(), reinterpret_cast(index_ptr), CPUPlace(), cpu_idx_data, byte_times * index.numel()); } if (index_type == DataType::INT64) { const int64_t* index_data = index_ptr ? reinterpret_cast(index_ptr) : index.template data(); r = xpu::index_select( dev_ctx.x_context(), reinterpret_cast(in_data), reinterpret_cast(index_data), reinterpret_cast(output->data()), in_shape, index_len, dim); } else { const int* index_data = index_ptr ? reinterpret_cast(index_ptr) : index.template data(); r = xpu::index_select( dev_ctx.x_context(), reinterpret_cast(in_data), reinterpret_cast(index_data), reinterpret_cast(output->data()), in_shape, index_len, dim); } PADDLE_ENFORCE_XDNN_SUCCESS(r, "index_select"); } } // namespace phi PD_REGISTER_KERNEL(index_select, XPU, ALL_LAYOUT, phi::IndexSelectKernel, float, phi::float16, phi::bfloat16, int, int64_t) {}