chore: import upstream snapshot with attribution

2026-07-13 12:40:42 +08:00
commit e25996e7db
15472 changed files with 3536181 additions and 0 deletions
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+// Copyright (c) 2023 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 "glog/logging.h"
+
+#include "paddle/phi/backends/all_context.h"
+#include "paddle/phi/core/kernel_registry.h"
+
+#if defined(PADDLE_WITH_NCCL) || defined(PADDLE_WITH_RCCL)
+#include "paddle/phi/core/distributed/nccl_comm_context.h"
+#include "paddle/phi/core/distributed/utils.h"
+#endif
+
+namespace phi {
+
+template <typename T, typename Context>
+void AllToAllKernel(const Context& dev_ctx,
+                    const DenseTensor& x,
+                    DenseTensor* out) {
+#if defined(PADDLE_WITH_NCCL) || defined(PADDLE_WITH_RCCL)
+  auto x_dims = x.dims();
+  out->Resize(x_dims);
+  dev_ctx.template Alloc<T>(out);
+
+  auto comm_ctx =
+      static_cast<distributed::NCCLCommContext*>(dev_ctx.GetCommContext());
+  PADDLE_ENFORCE_NE(
+      comm_ctx,
+      nullptr,
+      errors::Unavailable("NCCLCommContext is nullptr, collective op should "
+                          "has ring_id attr."));
+  gpuStream_t stream = dev_ctx.stream();
+  PADDLE_ENFORCE_NOT_NULL(stream,
+                          errors::NotFound("Should initialize NCCL firstly."));
+
+  int nranks = comm_ctx->GetSize();
+  int64_t send_numel = x.numel() / nranks;
+  size_t offset = 0;
+
+  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->GroupStart();
+
+  const auto* send_buf = x.data<T>();
+  auto* recv_buf = out->data<T>();
+  for (auto i = 0; i < nranks; ++i) {
+    auto send_buf = distributed::GetPartialTensor(x, offset, send_numel);
+    comm_ctx->Send(send_buf, send_numel, i, stream);
+    auto recv_buf = distributed::GetPartialTensor(*out, offset, send_numel);
+    comm_ctx->Recv(&recv_buf, send_numel, i, stream);
+    offset += send_numel;
+  }
+  comm_ctx->GroupEnd();
+#else
+  PADDLE_THROW(
+      errors::PreconditionNotMet("PaddlePaddle should compile with GPU."));
+#endif
+}
+
+}  // namespace phi
+
+PD_REGISTER_KERNEL(all_to_all,
+                   GPU,
+                   ALL_LAYOUT,
+                   phi::AllToAllKernel,
+                   float,
+                   double,
+                   int,
+                   int8_t,
+                   uint8_t,
+                   int16_t,
+                   int64_t,
+                   bool,
+                   phi::bfloat16,
+                   phi::float16) {}