chore: import upstream snapshot with attribution

paddle/phi/kernels/cpu/elementwise_grad_kernel.cc

@@ -0,0 +1,232 @@
+//   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/elementwise_grad_kernel.h"
+
+#include "paddle/phi/backends/cpu/cpu_context.h"
+#include "paddle/phi/core/kernel_registry.h"
+#include "paddle/phi/core/tensor_utils.h"
+#include "paddle/phi/kernels/cpu/elementwise_grad.h"
+#include "paddle/phi/kernels/full_kernel.h"
+#include "paddle/phi/kernels/funcs/elementwise_functor.h"
+#include "paddle/phi/kernels/impl/elementwise_grad_kernel_impl.h"
+
+namespace phi {
+
+template <typename T, typename Context>
+void MaximumGradKernel(const Context& dev_ctx,
+                       const DenseTensor& x,
+                       const DenseTensor& y,
+                       const DenseTensor& dout,
+                       DenseTensor* dx,
+                       DenseTensor* dy) {
+  if (dout.numel() == 0) {
+    if (dx) {
+      if (dx->numel() == 0) {
+        dev_ctx.template Alloc<T>(dx);
+      } else {
+        Full<T, Context>(dev_ctx, dx->dims(), 0, dx);
+      }
+    }
+    if (dy) {
+      if (dy->numel() == 0) {
+        dev_ctx.template Alloc<T>(dy);
+      } else {
+        Full<T, Context>(dev_ctx, dy->dims(), 0, dy);
+      }
+    }
+    return;
+  }
+  funcs::ElementwiseGradPreProcess(dout, dx);
+  int axis = -1;
+  funcs::ElemwiseGradCompute<Context, T, MaxGradDx<T>, MaxGradDy<T>>(
+      dev_ctx, x, y, dout, dout, axis, dx, dy, MaxGradDx<T>(), MaxGradDy<T>());
+}
+
+template <typename T, typename Context>
+void MinimumGradKernel(const Context& dev_ctx,
+                       const DenseTensor& x,
+                       const DenseTensor& y,
+                       const DenseTensor& dout,
+                       DenseTensor* dx,
+                       DenseTensor* dy) {
+  if (dout.numel() == 0) {
+    if (dx) {
+      if (dx->numel() == 0) {
+        dev_ctx.template Alloc<T>(dx);
+      } else {
+        Full<T, Context>(dev_ctx, dx->dims(), 0, dx);
+      }
+    }
+    if (dy) {
+      if (dy->numel() == 0) {
+        dev_ctx.template Alloc<T>(dy);
+      } else {
+        Full<T, Context>(dev_ctx, dy->dims(), 0, dy);
+      }
+    }
+    return;
+  }
+  funcs::ElementwiseGradPreProcess(dout, dx);
+  int axis = -1;
+  funcs::ElemwiseGradCompute<Context, T, MinGradDx<T>, MinGradDy<T>>(
+      dev_ctx, x, y, dout, dout, axis, dx, dy, MinGradDx<T>(), MinGradDy<T>());
+}
+
+template <typename T, typename Context>
+void RemainderGradKernel(const Context& dev_ctx,
+                         const DenseTensor& x,
+                         const DenseTensor& y,
+                         const DenseTensor& dout,
+                         DenseTensor* dx,
+                         DenseTensor* dy) {
+  if (dout.numel() == 0) {
+    if (dx) {
+      if (dx->numel() == 0) {
+        dev_ctx.template Alloc<T>(dx);
+      } else {
+        Full<T, Context>(dev_ctx, dx->dims(), 0, dx);
+      }
+    }
+    if (dy) {
+      if (dy->numel() == 0) {
+        dev_ctx.template Alloc<T>(dy);
+      } else {
+        Full<T, Context>(dev_ctx, dy->dims(), 0, dy);
+      }
+    }
+    return;
+  }
+  funcs::ElementwiseGradPreProcess(dout, dx);
+  int axis = -1;
+  funcs::
+      ElemwiseGradCompute<Context, T, RemainderGradDx<T>, RemainderGradDy<T>>(
+          dev_ctx,
+          x,
+          y,
+          dout,
+          dout,
+          axis,
+          dx,
+          dy,
+          RemainderGradDx<T>(),
+          RemainderGradDy<T>());
+}
+
+template <typename T, typename Context>
+void CopySignGradKernel(const Context& dev_ctx,
+                        const DenseTensor& x,
+                        const DenseTensor& y,
+                        const DenseTensor& out_grad,
+                        DenseTensor* x_grad,
+                        DenseTensor* y_grad) {
+  funcs::ElementwiseGradPreProcess(out_grad, x_grad);
+  int axis = -1;
+  funcs::ElemwiseGradCompute<Context, T, CopySignGradDX<T>, CopySignGradDY<T>>(
+      dev_ctx,
+      x,
+      y,
+      out_grad,
+      out_grad,
+      axis,
+      x_grad,
+      y_grad,
+      CopySignGradDX<T>(),
+      CopySignGradDY<T>());
+}
+}  // namespace phi
+
+PD_REGISTER_KERNEL(fmax_grad,
+                   CPU,
+                   ALL_LAYOUT,
+                   phi::ElementwiseFMaxGradKernel,
+                   float,
+                   double,
+                   int,
+                   int64_t) {}
+
+PD_REGISTER_KERNEL(fmin_grad,
+                   CPU,
+                   ALL_LAYOUT,
+                   phi::ElementwiseFMinGradKernel,
+                   float,
+                   double,
+                   int,
+                   int64_t) {}
+
+PD_REGISTER_KERNEL(maximum_grad,
+                   CPU,
+                   ALL_LAYOUT,
+                   phi::MaximumGradKernel,
+                   float,
+                   double,
+                   int,
+                   int64_t,
+                   phi::bfloat16) {}
+
+PD_REGISTER_KERNEL(minimum_grad,
+                   CPU,
+                   ALL_LAYOUT,
+                   phi::MinimumGradKernel,
+                   float,
+                   double,
+                   int,
+                   int64_t,
+                   phi::bfloat16) {}
+
+PD_REGISTER_KERNEL(remainder_grad,
+                   CPU,
+                   ALL_LAYOUT,
+                   phi::RemainderGradKernel,
+                   float,
+                   double,
+                   int,
+                   int64_t,
+                   phi::bfloat16) {}
+
+PD_REGISTER_KERNEL(heaviside_grad,
+                   CPU,
+                   ALL_LAYOUT,
+                   phi::HeavisideGradKernel,
+                   float,
+                   double,
+                   int,
+                   int64_t) {}
+
+PD_REGISTER_KERNEL(elementwise_pow_grad,
+                   CPU,
+                   ALL_LAYOUT,
+                   phi::ElementwisePowGradKernel,
+                   float,
+                   double,
+                   int,
+                   int64_t,
+                   phi::bfloat16,
+                   phi::complex64,
+                   phi::complex128) {}
+
+PD_REGISTER_KERNEL(copysign_grad,
+                   CPU,
+                   ALL_LAYOUT,
+                   phi::CopySignGradKernel,
+                   bool,
+                   uint8_t,
+                   int8_t,
+                   int16_t,
+                   int,
+                   int64_t,
+                   float,
+                   double,
+                   phi::float16,
+                   phi::bfloat16) {}