chore: import upstream snapshot with attribution

paddle/phi/kernels/impl/inverse_grad_kernel_impl.h

@@ -0,0 +1,73 @@
+// 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/inverse_grad_kernel.h"
+
+#include "paddle/phi/backends/cpu/cpu_context.h"
+#include "paddle/phi/backends/gpu/gpu_context.h"
+#include "paddle/phi/kernels/complex_kernel.h"
+#include "paddle/phi/kernels/funcs/blas/blas.h"
+#include "paddle/phi/kernels/funcs/matrix_inverse.h"
+
+namespace phi {
+
+template <typename T, typename Context>
+void InverseGradKernel(const Context& dev_ctx,
+                       const DenseTensor& out,
+                       const DenseTensor& out_grad,
+                       DenseTensor* in_grad) {
+  if (in_grad) {
+    dev_ctx.template Alloc<T>(in_grad);
+    if (out_grad.numel() == 0) {
+      return;
+    }
+    auto blas = funcs::GetBlas<Context, T>(dev_ctx);
+
+    DenseTensor tmp_out;
+    tmp_out.Resize(out.dims());
+    dev_ctx.template Alloc<T>(&tmp_out);
+
+    if (IsComplexType(out.dtype())) {
+      DenseTensor out_conj;
+      out_conj.Resize(out.dims());
+      dev_ctx.template Alloc<T>(&out_conj);
+
+      ConjKernel<T, Context>(dev_ctx, out, &out_conj);
+
+      auto mat_dim_a0 =
+          funcs::CreateMatrixDescriptor(out_grad.dims(), 0, false);
+      auto mat_dim_b0 = funcs::CreateMatrixDescriptor(out.dims(), 0, true);
+      blas.MatMul(
+          out_grad, mat_dim_a0, out_conj, mat_dim_b0, T(1), &tmp_out, T(0));
+
+      auto mat_dim_a1 = funcs::CreateMatrixDescriptor(out.dims(), 0, true);
+      auto mat_dim_b1 = funcs::CreateMatrixDescriptor(tmp_out.dims(), 0, false);
+      blas.MatMul(
+          out_conj, mat_dim_a1, tmp_out, mat_dim_b1, T(-1), in_grad, T(0));
+    } else {
+      auto mat_dim_a0 =
+          funcs::CreateMatrixDescriptor(out_grad.dims(), 0, false);
+      auto mat_dim_b0 = funcs::CreateMatrixDescriptor(out.dims(), 0, true);
+      blas.MatMul(out_grad, mat_dim_a0, out, mat_dim_b0, T(1), &tmp_out, T(0));
+
+      auto mat_dim_a1 = funcs::CreateMatrixDescriptor(out.dims(), 0, true);
+      auto mat_dim_b1 = funcs::CreateMatrixDescriptor(tmp_out.dims(), 0, false);
+      blas.MatMul(out, mat_dim_a1, tmp_out, mat_dim_b1, T(-1), in_grad, T(0));
+    }
+  }
+}
+
+}  // namespace phi