chore: import upstream snapshot with attribution

paddle/phi/kernels/impl/softmax_kernel_impl.h

@@ -0,0 +1,53 @@
+/* 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. */
+
+#pragma once
+
+#include "paddle/phi/kernels/funcs/axis_utils.h"
+#include "paddle/phi/kernels/funcs/math_function.h"
+#include "paddle/phi/kernels/funcs/softmax.h"
+#include "paddle/phi/kernels/softmax_kernel.h"
+
+namespace phi {
+
+template <typename T, typename Context>
+void SoftmaxKernel(const Context& dev_ctx,
+                   const DenseTensor& x,
+                   int axis,
+                   DenseTensor* out) {
+  const int rank = x.dims().size();
+  const int calc_axis = funcs::CanonicalAxis(axis, rank);
+  int64_t axis_dim = x.dims()[calc_axis];
+
+  // allocate memory on device.
+  dev_ctx.template Alloc<T>(out);
+  // For 0-Sized Tensor
+  if (out->numel() == 0) {
+    return;
+  }
+  // For 0D Tensor
+  if (rank == 0) {
+    funcs::set_constant(dev_ctx, out, static_cast<T>(1.0));
+    return;
+  }
+
+  const int64_t n = funcs::SizeToAxis(calc_axis, x.dims());
+  const int64_t d = funcs::SizeFromAxis(calc_axis, x.dims());
+  DenseTensor X_2d, Out_2d;
+  X_2d.ShareDataWith(x).Resize({n, d});
+  Out_2d.ShareDataWith(*out).Resize({n, d});
+  funcs::SoftmaxFunctor<Context, T>()(dev_ctx, axis_dim, &X_2d, &Out_2d);
+}
+
+}  // namespace phi