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/c_split_kernel.h"
+
+#include "paddle/phi/backends/xpu/enforce_xpu.h"
+#include "paddle/phi/core/kernel_registry.h"
+
+namespace phi {
+
+template <typename T, typename Context>
+void CSplitKernel(const Context& dev_ctx,
+                  const DenseTensor& x,
+                  int rank,
+                  int nranks,
+                  bool use_model_parallel,
+                  DenseTensor* out) {
+#if defined(PADDLE_WITH_XPU_BKCL)
+  using XPUType = typename XPUTypeTrait<T>::Type;
+
+  PADDLE_ENFORCE_GE(rank,
+                    0,
+                    common::errors::PreconditionNotMet(
+                        "The value of rank (%d) for c_split must be "
+                        "greater than or equal to 0.",
+                        rank));
+  PADDLE_ENFORCE_GE(nranks,
+                    2,
+                    common::errors::PreconditionNotMet(
+                        "The value of nranks (%d) for c_split must be "
+                        "greater than or equal to 2.",
+                        nranks));
+  PADDLE_ENFORCE_LT(rank,
+                    nranks,
+                    common::errors::PreconditionNotMet(
+                        "The value of rank (%d) for c_split must be "
+                        "less than that of nranks (%d).",
+                        rank,
+                        nranks));
+
+  auto dims = x.dims();
+  auto dims_size = dims.size();
+  // final dim
+  int64_t end_size = dims[dims_size - 1];
+
+  // remain dim
+  auto remain_ddim = slice_ddim(dims, 0, dims_size - 1);
+  int64_t remain_numel = common::product(remain_ddim);
+
+  dims[dims_size - 1] /= nranks;
+  out->Resize(dims);
+  dev_ctx.Alloc(out, x.dtype());
+
+  std::vector<XPUType*> output_list(nranks, nullptr);
+  output_list.at(rank) = reinterpret_cast<XPUType*>(out->data<T>());
+  std::vector<int64_t> split_list(nranks, dims[dims_size - 1]);
+  int axis = 1;
+
+  auto ret = xpu::split(dev_ctx.x_context(),
+                        reinterpret_cast<const XPUType*>(x.data<T>()),
+                        output_list,
+                        {remain_numel, end_size},
+                        split_list,
+                        axis);
+  PADDLE_ENFORCE_XDNN_SUCCESS(ret, "split");
+#else
+  PADDLE_THROW(common::errors::PreconditionNotMet(
+      "PaddlePaddle is not compiled with DWITH_XPU_BKCL, please recompile with "
+      "DWITH_XPU_BKCL for using c_split_kernel."));
+#endif
+}
+}  // namespace phi
+
+PD_REGISTER_KERNEL(c_split,
+                   XPU,
+                   ALL_LAYOUT,
+                   phi::CSplitKernel,
+                   float,
+                   int,
+                   phi::float16,
+                   phi::bfloat16) {}