chore: import upstream snapshot with attribution

paddle/phi/kernels/gpu/expand_kernel.cu

@@ -0,0 +1,117 @@
+// 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/expand_kernel.h"
+
+#include "paddle/phi/backends/gpu/gpu_context.h"
+#include "paddle/phi/common/scalar.h"
+#include "paddle/phi/core/dense_tensor.h"
+#include "paddle/phi/core/kernel_registry.h"
+#include "paddle/phi/kernels/funcs/broadcast_function.h"
+
+namespace phi {
+
+template <typename T, typename Context>
+void ExpandKernel(const Context& dev_ctx,
+                  const DenseTensor& x,
+                  const IntArray& shape,
+                  DenseTensor* out) {
+  auto in_dims = x.dims();
+  auto expand_shape = shape.GetData();
+  if (expand_shape.empty()) {
+    *out = x;
+    return;
+  }
+  auto vec_in_dims = vectorize<int64_t>(in_dims);
+  auto diff = expand_shape.size() - vec_in_dims.size();
+  PADDLE_ENFORCE_GE(
+      diff,
+      0,
+      common::errors::InvalidArgument(
+          "The rank of the target shape (%d) must be greater than or equal to "
+          "the rank of the input tensor (%d).",
+          expand_shape.size(),
+          vec_in_dims.size()));
+  vec_in_dims.insert(vec_in_dims.begin(), diff, 1);
+  auto out_shape = vec_in_dims;
+  bool has_zero_dim = false;
+  for (size_t i = 0; i < out_shape.size(); ++i) {
+    if (i < diff) {
+      PADDLE_ENFORCE_GE(
+          expand_shape[i],
+          0,
+          common::errors::InvalidArgument(
+              "The expanded size (%d) for non-existing dimensions must be "
+              "positive for expand_v2 op.",
+              expand_shape[i]));
+      if (expand_shape[i] == 0) has_zero_dim = true;
+      out_shape[i] = expand_shape[i];
+    } else if (expand_shape[i] == -1) {
+      out_shape[i] = vec_in_dims[i];
+    } else if (expand_shape[i] == 0) {
+      PADDLE_ENFORCE_EQ(
+          vec_in_dims[i] == 1 || vec_in_dims[i] == expand_shape[i],
+          true,
+          common::errors::InvalidArgument(
+              "The %d-th dimension of input tensor (%d) must match or be "
+              "broadcastable to the corresponding dimension (%d) in shape.",
+              i,
+              vec_in_dims[i],
+              expand_shape[i]));
+      out_shape[i] = 0;
+      has_zero_dim = true;
+    } else if (expand_shape[i] > 0) {
+      PADDLE_ENFORCE_EQ(
+          vec_in_dims[i] == 1 || vec_in_dims[i] == expand_shape[i],
+          true,
+          common::errors::InvalidArgument(
+              "The %d-th dimension of input tensor (%d) must match or be "
+              "broadcastable to the corresponding dimension (%d) in shape.",
+              i,
+              vec_in_dims[i],
+              expand_shape[i]));
+      out_shape[i] = expand_shape[i];
+    }
+  }
+
+  out->Resize(out_shape);
+  dev_ctx.template Alloc<T>(out);
+  if (has_zero_dim) {
+    return;
+  }
+  std::vector<const DenseTensor*> ins = {&x};
+  std::vector<DenseTensor*> outs = {out};
+  funcs::BroadcastKernel<T>(dev_ctx, ins, &outs, kps::IdentityFunctor<T>());
+}
+
+}  // namespace phi
+
+PD_REGISTER_KERNEL(expand,
+                   GPU,
+                   ALL_LAYOUT,
+                   phi::ExpandKernel,
+                   float,
+                   double,
+                   int,
+                   int64_t,
+                   bool,
+                   int16_t,
+                   uint8_t,
+                   int8_t,
+                   phi::float16,
+                   phi::bfloat16,
+                   phi::float8_e4m3fn,
+                   phi::float8_e5m2,
+                   phi::complex64,
+                   phi::complex128) {}