// Copyright (c) 2025 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/all_to_all_kernel.h" #include "paddle/phi/backends/all_context.h" #include "paddle/phi/core/kernel_registry.h" #if defined(PADDLE_WITH_XPU_BKCL) #include "paddle/phi/core/distributed/bkcl_comm_context.h" #endif namespace phi { template void AllToAllKernel(const Context& dev_ctx, const DenseTensor& x, DenseTensor* out) { #if defined(PADDLE_WITH_XPU_BKCL) auto x_dims = x.dims(); out->Resize(x_dims); dev_ctx.template Alloc(out); auto comm_ctx = static_cast(dev_ctx.GetCommContext()); PADDLE_ENFORCE_NE(comm_ctx, nullptr, common::errors::Unavailable( "BKCLCommContext is nullptr, collective op should " "has ring_id attr.")); XPUStream stream = dev_ctx.stream(); int nranks = comm_ctx->GetSize(); PADDLE_ENFORCE_EQ( x_dims[0] % nranks, 0, errors::InvalidArgument( "The first dimension size (%d) of the input tensor must be " "divisible by the number of ranks (%d).", x_dims[0], nranks)); comm_ctx->AllToAll(out, x, stream); #else PADDLE_THROW(common::errors::PreconditionNotMet( "PaddlePaddle should be compiled with XPU.")); #endif } } // namespace phi PD_REGISTER_KERNEL(all_to_all, XPU, ALL_LAYOUT, phi::AllToAllKernel, int, int64_t, bool, uint8_t, float, phi::float16, phi::bfloat16) {}