[PHI] Migrate squeeze and squeeze_grad kernels

paddle/fluid/operators/mkldnn/reshape_mkldnn_op.cc

@@ -21,7 +21,6 @@ enum class ReshapeKernelOpName {
   reshape,
   reshape2,
   squeeze,
-  squeeze2,
   flatten,
   flatten2,
 };
@@ -106,9 +105,6 @@ class ReshapeMKLDNNKernel : public framework::OpKernel<T> {
       case ReshapeKernelOpName::squeeze:
         InferShapeSqueezeOp(ctx, x_dims, out_dims);
         break;
-      case ReshapeKernelOpName::squeeze2:
-        InferShapeSqueeze2Op(ctx, x_dims, out_dims);
-        break;
       case ReshapeKernelOpName::flatten:
         InferShapeFlattenOp(ctx, x_dims, out_dims);
         break;
@@ -172,16 +168,6 @@ class ReshapeMKLDNNKernel : public framework::OpKernel<T> {
     out_dims = GetOutputShape(axes, x_dims, true);
   }
 
-  void InferShapeSqueeze2Op(const framework::ExecutionContext& ctx,
-                            framework::DDim& x_dims,            // NOLINT
-                            framework::DDim& out_dims) const {  // NOLINT
-    auto* out = ctx.Output<phi::DenseTensor>("Out");
-    auto* xshape = ctx.Output<phi::DenseTensor>("XShape");
-    auto xshape_dims = xshape->dims();
-    x_dims = phi::slice_ddim(xshape_dims, 1, xshape_dims.size());
-    out_dims = out->dims();
-  }
-
   void InferShapeFlattenOp(const framework::ExecutionContext& ctx,
                            framework::DDim& x_dims,            // NOLINT
                            framework::DDim& out_dims) const {  // NOLINT
@@ -342,19 +328,16 @@ class ReshapeGradMKLDNNKernel : public ReshapeMKLDNNKernel<T, op_name> {
         InferShapeReshapeSqueezeGradOp(ctx, x_dims);
         break;
       case ReshapeKernelOpName::reshape2:
-        InferShapeReshape2Squeeze2Flatten2GradOp(ctx, x_dims);
+        InferShapeReshape2Flatten2GradOp(ctx, x_dims);
         break;
       case ReshapeKernelOpName::squeeze:
         InferShapeReshapeSqueezeGradOp(ctx, x_dims);
         break;
-      case ReshapeKernelOpName::squeeze2:
-        InferShapeReshape2Squeeze2Flatten2GradOp(ctx, x_dims);
-        break;
       case ReshapeKernelOpName::flatten:
         InferShapeFlattenGradOp(ctx, x_dims);
         break;
       case ReshapeKernelOpName::flatten2:
-        InferShapeReshape2Squeeze2Flatten2GradOp(ctx, x_dims);
+        InferShapeReshape2Flatten2GradOp(ctx, x_dims);
         break;
       default:
         PADDLE_THROW(paddle::platform::errors::OutOfRange(
@@ -369,7 +352,7 @@ class ReshapeGradMKLDNNKernel : public ReshapeMKLDNNKernel<T, op_name> {
     dx_dims = dx->dims();
   }
 
-  void InferShapeReshape2Squeeze2Flatten2GradOp(
+  void InferShapeReshape2Flatten2GradOp(
       const framework::ExecutionContext& ctx,
       framework::DDim& dx_dims) const {  // NOLINT
     auto xshape_dims = ctx.Input<phi::DenseTensor>("XShape")->dims();
@@ -401,22 +384,6 @@ REGISTER_OP_KERNEL(
     ops::ReshapeGradMKLDNNKernel<paddle::platform::bfloat16,
                                  ReshapeKernelOpName::squeeze>);
 
-REGISTER_OP_KERNEL(
-    squeeze2,
-    MKLDNN,
-    paddle::platform::CPUPlace,
-    ops::ReshapeMKLDNNKernel<float, ReshapeKernelOpName::squeeze2>,
-    ops::ReshapeMKLDNNKernel<paddle::platform::bfloat16,
-                             ReshapeKernelOpName::squeeze2>);
-
-REGISTER_OP_KERNEL(
-    squeeze2_grad,
-    MKLDNN,
-    paddle::platform::CPUPlace,
-    ops::ReshapeGradMKLDNNKernel<float, ReshapeKernelOpName::squeeze2>,
-    ops::ReshapeGradMKLDNNKernel<paddle::platform::bfloat16,
-                                 ReshapeKernelOpName::squeeze2>);
-
 REGISTER_OP_KERNEL(
     reshape,
     MKLDNN,

paddle/phi/kernels/onednn/squeeze_grad_kernel.cc

@@ -0,0 +1,59 @@
+// 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/squeeze_grad_kernel.h"
+
+#include "paddle/phi/backends/onednn/onednn_reuse.h"
+#include "paddle/phi/core/kernel_registry.h"
+
+namespace phi {
+
+template <typename T, typename Context>
+void SqueezeGradKernel(const Context& dev_ctx,
+                       const DenseTensor& xshape,
+                       const DenseTensor& dout,
+                       const IntArray& axes,
+                       DenseTensor* dx) {
+  auto dout_vec_dims = vectorize(dout.dims());
+  auto dout_type = funcs::ToOneDNNDataType(dout.dtype());
+
+  funcs::ReorderOneDNNHandler reorder_handler(
+      dout_vec_dims, dout.dtype(), dout_type, dev_ctx.GetEngine());
+
+  auto reorder_src_memory_p = reorder_handler.AcquireSrcMemory(
+      dout.mem_desc(), funcs::to_void_cast(dout.data<T>()));
+  auto reorder_dst_memory_p = reorder_handler.AcquireDstMemory(
+      dx,
+      funcs::GetPlainOneDNNFormat(dout_vec_dims.size()),
+      dev_ctx.GetPlace());
+  auto reorder_p = reorder_handler.AcquireReorder(reorder_dst_memory_p,
+                                                  reorder_src_memory_p);
+
+  auto& astream = OneDNNContext::tls().get_stream();
+  reorder_p->execute(astream, *reorder_src_memory_p, *reorder_dst_memory_p);
+  astream.wait();
+
+  auto dx_dims = slice_ddim(xshape.dims(), 1, xshape.dims().size());
+  dx->Resize(dx_dims);
+  reorder_dst_memory_p->get_desc().reshape(vectorize(dx_dims));
+}
+
+}  // namespace phi
+
+PD_REGISTER_KERNEL(squeeze_grad,
+                   OneDNN,
+                   ONEDNN,
+                   phi::SqueezeGradKernel,
+                   float,
+                   phi::dtype::bfloat16) {}

paddle/phi/kernels/onednn/squeeze_kernel.cc

@@ -0,0 +1,85 @@
+// 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/squeeze_kernel.h"
+
+#include "paddle/phi/backends/onednn/onednn_reuse.h"
+#include "paddle/phi/core/kernel_registry.h"
+#include "paddle/phi/kernels/funcs/unsqueeze.h"
+
+namespace phi {
+
+template <typename T, typename Context>
+void ExecuteSqueeze(const Context& dev_ctx,
+                    const DenseTensor& x,
+                    const DDim& x_dims,
+                    const DDim& out_dims,
+                    DenseTensor* out) {
+  auto x_vec_dims = vectorize(x_dims);
+
+  funcs::ReorderOneDNNHandler reorder_handler(
+      x_vec_dims,
+      x.dtype(),
+      funcs::ToOneDNNDataType(x.dtype()),
+      dev_ctx.GetEngine());
+
+  auto reorder_src_memory_p = reorder_handler.AcquireSrcMemory(
+      x.mem_desc(), funcs::to_void_cast(x.data<T>()));
+  out->Resize(x_dims);  // to match x numel, format is changed later
+  // reorder is done into a plain tag to allow usage with blocked formats
+  auto reorder_dst_memory_p = reorder_handler.AcquireDstMemory(
+      out, funcs::GetPlainOneDNNFormat(x_dims.size()), dev_ctx.GetPlace());
+  auto reorder_p = reorder_handler.AcquireReorder(reorder_dst_memory_p,
+                                                  reorder_src_memory_p);
+  auto& astream = OneDNNContext::tls().get_stream();
+  reorder_p->execute(astream, *reorder_src_memory_p, *reorder_dst_memory_p);
+  astream.wait();
+
+  out->Resize(out_dims);
+  out->set_mem_desc(
+      reorder_dst_memory_p->get_desc().reshape(vectorize(out_dims)));
+}
+
+template <typename T, typename Context>
+void SqueezeKernel(const Context& dev_ctx,
+                   const DenseTensor& x,
+                   const IntArray& axes,
+                   DenseTensor* out) {
+  auto x_dims = x.dims();
+  std::vector<int32_t> tmp(axes.GetData().begin(), axes.GetData().end());
+  auto out_dims = funcs::GetOutputSqueezeShape(tmp, x_dims, true);
+  ExecuteSqueeze<T, Context>(dev_ctx, x, x_dims, out_dims, out);
+}
+
+template <typename T, typename Context>
+void SqueezeWithXShapeKernel(const Context& dev_ctx,
+                             const DenseTensor& x,
+                             const IntArray& axes,
+                             DenseTensor* out,
+                             DenseTensor* xshape) {
+  auto x_dims = slice_ddim(xshape->dims(), 1, xshape->dims().size());
+  auto out_dims = out->dims();
+  ExecuteSqueeze<T, Context>(dev_ctx, x, x_dims, out_dims, out);
+}
+}  // namespace phi
+
+PD_REGISTER_KERNEL(
+    squeeze, OneDNN, ONEDNN, phi::SqueezeKernel, float, phi::dtype::bfloat16) {}
+
+PD_REGISTER_KERNEL(squeeze_with_xshape,
+                   OneDNN,
+                   ONEDNN,
+                   phi::SqueezeWithXShapeKernel,
+                   float,
+                   phi::dtype::bfloat16) {}