// 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/scatter_kernel.h" #include "paddle/phi/backends/xpu/enforce_xpu.h" #include "paddle/phi/backends/xpu/xpu_context.h" #include "paddle/phi/core/kernel_registry.h" namespace phi { template void ScatterKernel(const Context &ctx, const DenseTensor &x, const DenseTensor &index, const DenseTensor &updates, bool overwrite, DenseTensor *out) { phi::Copy(ctx, x, ctx.GetPlace(), false, out); // Apply ScatterUpdate: Out[index] = Updates[:] const auto &index_type = index.dtype(); bool index_type_match = index_type == phi::DataType::INT32 || index_type == phi::DataType::INT64; PADDLE_ENFORCE_EQ( index_type_match, true, phi::errors::InvalidArgument("Index holds the wrong type, it holds [%s]," "but desires to be [%s] or [%s].", index_type, phi::DataType::INT32, phi::DataType::INT64)); // check index of shape 1-D PADDLE_ENFORCE_EQ( index.dims().size() == 1 || index.dims().size() == 0 || (index.dims().size() == 2 && index.dims()[1] == 1), true, phi::errors::InvalidArgument( "index's shape is error, " "expect index'dims shape is 0, 1, 2 (index.dims[1] should " "be 1), 0 but got index'dims shape is %d", index.dims().size())); int index_size = static_cast(index.dims().size() == 0 ? 1 : index.dims()[0]); auto x_dims = x.dims(); auto update_dims = updates.dims(); if (index.dims().size() != 0) { // only check when the updates tensor is not a 0D tensor for (int i = 1; i < x_dims.size(); i++) PADDLE_ENFORCE_EQ( x_dims[i], update_dims[i], phi::errors::InvalidArgument( "The dimensions of the source tensor and target tensor should" " match, but received source tensor's %d-th dimension is %d," "target tensor's %d-th dimension is %d.", i, x_dims[i], i, update_dims[i])); } int dim0 = static_cast(x.dims()[0]); int dim1 = static_cast(phi::product(phi::slice_ddim(x_dims, 1, x_dims.size()))); T *out_data = out->data(); const T *updates_data = updates.data(); DenseTensor indices_cpu(index.type()); phi::Copy(ctx, index, phi::CPUPlace(), false, &indices_cpu); int r = 0; if (index_type == phi::DataType::INT32) { auto index_data = const_cast(index.data()); xpu::VectorParam indices{ indices_cpu.data(), index_size, index_data}; r = xpu::scatter(ctx.x_context(), updates_data, out_data, indices, dim0, dim1, overwrite); } else { auto index_data = const_cast(index.data()); xpu::VectorParam indices{ indices_cpu.data(), index_size, index_data}; r = xpu::scatter(ctx.x_context(), updates_data, out_data, indices, dim0, dim1, overwrite); } PADDLE_ENFORCE_XDNN_SUCCESS(r, "scatter"); } } // namespace phi PD_REGISTER_KERNEL( scatter, XPU, ALL_LAYOUT, phi::ScatterKernel, float, int64_t) {}