chore: import upstream snapshot with attribution

paddle/phi/kernels/gpu/shuffle_batch_grad_kernel.cu

@@ -0,0 +1,67 @@
+// 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.
+
+#if defined(PADDLE_WITH_CUDA) || defined(PADDLE_WITH_HIP)
+
+#ifndef _MSC_VER
+#include <thrust/device_ptr.h>
+#include <thrust/iterator/counting_iterator.h>
+#include <thrust/random.h>
+#include <thrust/shuffle.h>
+#endif
+
+#include "paddle/common/errors.h"
+#include "paddle/phi/common/memory_utils.h"
+#include "paddle/phi/core/dense_tensor.h"
+#include "paddle/phi/core/kernel_registry.h"
+#include "paddle/phi/core/tensor_utils.h"
+#include "paddle/phi/kernels/funcs/for_range.h"
+#include "paddle/phi/kernels/gpu/shuffle_batch_utils.h"
+#include "paddle/phi/kernels/shuffle_batch_grad_kernel.h"
+
+namespace phi {
+
+template <typename T, typename Context>
+void ShuffleBatchGradKernel(const Context& dev_ctx,
+                            const DenseTensor& shuffleidx,
+                            const DenseTensor& out_grad,
+                            int startup_seed,
+                            DenseTensor* x_grad) {
+#ifdef _MSC_VER
+  PADDLE_THROW(common::errors::Unimplemented(
+      "GPU shuffle_batch_grad is not supported on Windows yet"));
+#else
+  const auto* out_grad_data = out_grad.data<T>();
+  const auto* shuffleidx_data = shuffleidx.data<int64_t>();
+  auto* x_grad_data = dev_ctx.template Alloc<T>(x_grad);
+  auto x_embed_size = x_grad->dims()[x_grad->dims().size() - 1];
+  ReorderFunctor<T, false> functor(
+      out_grad_data, shuffleidx_data, x_grad_data, x_embed_size);
+  // TODO(zengjinle): for small data, direct cudaMemcpy may be better
+  funcs::ForRange<GPUContext> for_range(dev_ctx, x_grad->numel());
+  for_range(functor);
+#endif
+}
+
+}  // namespace phi
+
+PD_REGISTER_KERNEL(shuffle_batch_grad,
+                   GPU,
+                   ALL_LAYOUT,
+                   phi::ShuffleBatchGradKernel,
+                   float,
+                   double,
+                   int32_t,
+                   int64_t) {}
+#endif