Merge branch 'develop' of https://github.com/PaddlePaddle/Paddle into hsigmoid_op

paddle/fluid/operators/mul_mkldnn_op.cc

-/* Copyright (c) 2018 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 "mkldnn.hpp"
-#include "paddle/fluid/framework/tensor.h"
-#include "paddle/fluid/operators/mul_op.h"
-#include "paddle/fluid/platform/device_context.h"
-#include "paddle/fluid/platform/mkldnn_helper.h"
-
-namespace paddle {
-namespace operators {
-
-using paddle::framework::Tensor;
-using paddle::platform::MKLDNNDeviceContext;
-
-template <typename Format = mkldnn::memory::format>
-mkldnn::memory::desc type(const std::vector<int>& dims, Format&& f) {
-  return platform::MKLDNNMemDesc(dims, mkldnn::memory::data_type::f32, f);
-}
-
-template <typename T>
-class MulMKLDNNOpKernel : public paddle::framework::OpKernel<T> {
-  void Compute(const paddle::framework::ExecutionContext& ctx) const override {
-    PADDLE_ENFORCE(paddle::platform::is_cpu_place(ctx.GetPlace()),
-                   "It must use CPUPlace.");
-
-    auto& dev_ctx = ctx.template device_context<MKLDNNDeviceContext>();
-    auto mkldnn_engine = dev_ctx.GetEngine();
-
-    auto input = ctx.Input<Tensor>("X");
-    auto weight = ctx.Input<Tensor>("Y");
-
-    PADDLE_ENFORCE(input->dims().size() & (2 | 4),
-                   "Input must be with 2 or 4 dimensions, i.e. NC or NCHW");
-    PADDLE_ENFORCE(weight->dims().size() & (2 | 4),
-                   "Weights must be with 2 or 4 dimensions, i.e. OI or OIHW");
-
-    std::vector<int> w_tz = paddle::framework::vectorize2int(weight->dims());
-    std::vector<int> src_tz = paddle::framework::vectorize2int(input->dims());
-
-    auto src_md =
-        src_tz.size() != 2
-            ? type(src_tz, mkldnn::memory::format::nchw)
-            : type({src_tz[0], src_tz[1]}, mkldnn::memory::format::nc);
-
-    auto dst_md = type({src_tz[0], w_tz[1]}, mkldnn::memory::format::nc);
-
-    auto weights_md =
-        src_tz.size() != 2
-            ? type({w_tz[1], src_tz[1], src_tz[2], src_tz[3]},
-                   mkldnn::memory::format::oihw)
-            : type({w_tz[1], src_tz[1]}, mkldnn::memory::format::oi);
-
-    auto output = ctx.Output<Tensor>("Out");
-    T* output_data = output->mutable_data<T>(ctx.GetPlace());
-
-    const std::string key = ctx.op().Output("Out");
-    const std::string key_fc_pd = key + "@mul_pd";
-
-    const T* input_data = input->data<T>();
-    const T* w_data = weight->data<T>();
-
-    auto dst_memory = mkldnn::memory({dst_md, mkldnn_engine}, output_data);
-
-    auto src_memory = mkldnn::memory({src_md, mkldnn_engine},
-                                     platform::to_void_cast(input_data));
-
-    auto weights_memory = mkldnn::memory({weights_md, mkldnn_engine},
-                                         platform::to_void_cast(w_data));
-
-    auto pd = platform::MKLDNNFwdPrimitiveDesc<mkldnn::inner_product_forward>(
-        mkldnn_engine, src_md, weights_md, dst_md);
-
-    dev_ctx.SetBlob(key_fc_pd, pd);
-
-    auto forward = mkldnn::inner_product_forward(*pd, src_memory,
-                                                 weights_memory, dst_memory);
-
-    std::vector<mkldnn::primitive> pipeline = {forward};
-    mkldnn::stream(mkldnn::stream::kind::eager).submit(pipeline).wait();
-  }
-};
-
-template <typename T>
-class MulMKLDNNGradOpKernel : public paddle::framework::OpKernel<T> {
- public:
-  void Compute(const paddle::framework::ExecutionContext& ctx) const override {
-    PADDLE_ENFORCE(paddle::platform::is_cpu_place(ctx.GetPlace()),
-                   "It must use CPUPlace.");
-
-    auto& dev_ctx = ctx.template device_context<MKLDNNDeviceContext>();
-    auto mkldnn_engine = dev_ctx.GetEngine();
-
-    const Tensor* input = ctx.Input<Tensor>("X");
-    const Tensor* w = ctx.Input<Tensor>("Y");
-
-    const Tensor* out_grad = ctx.Input<Tensor>(framework::GradVarName("Out"));
-    Tensor* input_grad = ctx.Output<Tensor>(framework::GradVarName("X"));
-    Tensor* w_grad = ctx.Output<Tensor>(framework::GradVarName("Y"));
-
-    const std::string key = ctx.op().Input("Out");
-    const std::string key_fc_pd = key + "@mul_pd";
-
-    const T* input_data = input->data<T>();
-    const T* w_data = w->data<T>();
-    const T* out_grad_data = out_grad->data<T>();
-    T* input_grad_data = nullptr;
-    T* w_grad_data = nullptr;
-
-    if (input_grad) {
-      input_grad_data = input_grad->mutable_data<T>(ctx.GetPlace());
-    }
-    if (w_grad) {
-      w_grad_data = w_grad->mutable_data<T>(ctx.GetPlace());
-    }
-
-    std::vector<int> src_tz = paddle::framework::vectorize2int(input->dims());
-    std::vector<int> w_tz = paddle::framework::vectorize2int(w->dims());
-
-    auto src_md =
-        src_tz.size() != 2
-            ? type(src_tz, mkldnn::memory::format::nchw)
-            : type({src_tz[0], src_tz[1]}, mkldnn::memory::format::nc);
-
-    auto dst_md = type({src_tz[0], w_tz[1]}, mkldnn::memory::format::nc);
-
-    auto weights_md =
-        src_tz.size() != 2
-            ? type({w_tz[1], src_tz[1], src_tz[2], src_tz[3]},
-                   mkldnn::memory::format::oihw)
-            : type({w_tz[1], src_tz[1]}, mkldnn::memory::format::oi);
-
-    auto src_memory = mkldnn::memory({src_md, mkldnn_engine},
-                                     platform::to_void_cast(input_data));
-
-    auto dst_memory = mkldnn::memory({dst_md, mkldnn_engine},
-                                     platform::to_void_cast(out_grad_data));
-
-    auto weight_memory = mkldnn::memory({weights_md, mkldnn_engine},
-                                        platform::to_void_cast(w_data));
-
-    auto pd =
-        std::static_pointer_cast<mkldnn::inner_product_forward::primitive_desc>(
-            dev_ctx.GetBlob(key_fc_pd));
-
-    PADDLE_ENFORCE(pd != nullptr, "Fail to find pd in device context");
-
-    if (w_grad) {
-      auto weights_grad_memory = mkldnn::memory(
-          {weights_md, mkldnn_engine}, platform::to_void_cast(w_grad_data));
-
-      auto bwd_weight_pd = platform::MKLDNNBwdPrimitiveDesc<
-          mkldnn::inner_product_backward_weights>(mkldnn_engine, *pd, src_md,
-                                                  weights_md, dst_md);
-
-      auto bwd_weights_prim = mkldnn::inner_product_backward_weights(
-          bwd_weight_pd, src_memory, dst_memory, weights_grad_memory);
-
-      std::vector<mkldnn::primitive> pipeline{bwd_weights_prim};
-      mkldnn::stream(mkldnn::stream::kind::eager).submit(pipeline).wait();
-    }
-
-    if (input_grad) {
-      auto src_grad_memory = mkldnn::memory(
-          {src_md, mkldnn_engine}, platform::to_void_cast(input_grad_data));
-
-      auto bwd_data_pd =
-          platform::MKLDNNBwdPrimitiveDesc<mkldnn::inner_product_backward_data>(
-              mkldnn_engine, *pd, src_md, weights_md, dst_md);
-
-      auto bwd_data_prim = mkldnn::inner_product_backward_data(
-          bwd_data_pd, dst_memory, weight_memory, src_grad_memory);
-
-      std::vector<mkldnn::primitive> pipeline{bwd_data_prim};
-      mkldnn::stream(mkldnn::stream::kind::eager).submit(pipeline).wait();
-    }
-  }
-};
-}  // namespace operators
-}  // namespace paddle
-
-REGISTER_OP_KERNEL(mul, MKLDNN, ::paddle::platform::CPUPlace,
-                   paddle::operators::MulMKLDNNOpKernel<float>);
-
-REGISTER_OP_KERNEL(mul_grad, MKLDNN, ::paddle::platform::CPUPlace,
-                   paddle::operators::MulMKLDNNGradOpKernel<float>);

paddle/fluid/operators/mul_op.cc

@@ -16,10 +16,6 @@ limitations under the License. */
 #include <string>
 #include <vector>
 
-#ifdef PADDLE_WITH_MKLDNN
-#include "paddle/fluid/platform/mkldnn_helper.h"
-#endif
-
 namespace paddle {
 namespace operators {
 
@@ -76,22 +72,6 @@ class MulOp : public framework::OperatorWithKernel {
     ctx->SetOutputDim("Out", framework::make_ddim(output_dims));
     ctx->ShareLoD("X", /*->*/ "Out");
   }
-
- private:
-  framework::OpKernelType GetExpectedKernelType(
-      const framework::ExecutionContext& ctx) const override {
-    framework::LibraryType library{framework::LibraryType::kPlain};
-#ifdef PADDLE_WITH_MKLDNN
-    if (library == framework::LibraryType::kPlain &&
-        platform::CanMKLDNNBeUsed(ctx)) {
-      library = framework::LibraryType::kMKLDNN;
-    }
-#endif
-    framework::DataLayout layout{framework::DataLayout::kAnyLayout};
-    return framework::OpKernelType(
-        framework::ToDataType(ctx.Input<Tensor>("X")->type()), ctx.GetPlace(),
-        layout, library);
-  }
 };
 
 class MulOpMaker : public framework::OpProtoAndCheckerMaker {
@@ -120,9 +100,6 @@ class MulOpMaker : public framework::OpProtoAndCheckerMaker {
         )DOC")
         .SetDefault(1)
         .EqualGreaterThan(1);
-    AddAttr<bool>("use_mkldnn",
-                  "(bool, default false) Only used in mkldnn kernel")
-        .SetDefault(false);
     AddAttr<int>(
         "y_num_col_dims",
         R"DOC((int, default 1), The mul_op can take tensors with more than two,
@@ -177,22 +154,6 @@ class MulGradOp : public framework::OperatorWithKernel {
       ctx->SetOutputDim(y_grad_name, y_dims);
     }
   }
-
- private:
-  framework::OpKernelType GetExpectedKernelType(
-      const framework::ExecutionContext& ctx) const override {
-    framework::LibraryType library{framework::LibraryType::kPlain};
-#ifdef PADDLE_WITH_MKLDNN
-    if (library == framework::LibraryType::kPlain &&
-        platform::CanMKLDNNBeUsed(ctx)) {
-      library = framework::LibraryType::kMKLDNN;
-    }
-#endif
-    framework::DataLayout layout{framework::DataLayout::kAnyLayout};
-    return framework::OpKernelType(
-        framework::ToDataType(ctx.Input<Tensor>("X")->type()), ctx.GetPlace(),
-        layout, library);
-  }
 };
 
 }  // namespace operators

python/paddle/fluid/layers/nn.py

@@ -180,11 +180,8 @@ def fc(input,
             inputs={"X": input_var,
                     "Y": w},
             outputs={"Out": tmp},
-            attrs={
-                "x_num_col_dims": num_flatten_dims,
-                "y_num_col_dims": 1,
-                "use_mkldnn": use_mkldnn
-            })
+            attrs={"x_num_col_dims": num_flatten_dims,
+                   "y_num_col_dims": 1})
         mul_results.append(tmp)
 
     if len(mul_results) == 1:

python/paddle/fluid/tests/unittests/test_mul_mkldnn_op.py

-#   Copyright (c) 2018 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.
-
-import unittest
-from test_mul_op import TestMulOp, TestMulOp2, TestFP16MulOp1, TestFP16MulOp2
-
-
-class TestMKLDNNMulOp(TestMulOp):
-    def init_op_test(self):
-        super(TestMKLDNNMulOp, self).setUp()
-        self.attrs = {"use_mkldnn": True}
-
-
-class TestMKLDNNMulOp2(TestMulOp2):
-    def init_op_test(self):
-        super(TestMKLDNNMulOp2, self).setUp()
-        self.attrs = {"use_mkldnn": True}
-
-
-class TestMKLDNNFP16MulOp1(TestFP16MulOp1):
-    def init_op_test(self):
-        super(TestMKLDNNFP16MulOp1, self).setUp()
-        self.attrs = {"use_mkldnn": True}
-
-
-class TestMKLDNNFP16MulOp2(TestFP16MulOp2):
-    def init_op_test(self):
-        super(TestMKLDNNFP16MulOp2, self).setUp()
-        self.attrs = {"use_mkldnn": True}
-
-
-if __name__ == "__main__":
-    unittest.main()

python/paddle/fluid/tests/unittests/test_mul_op.py

@@ -21,12 +21,10 @@ from op_test import OpTest
 class TestMulOp(OpTest):
     def setUp(self):
         self.op_type = "mul"
-        self.use_mkldnn = False
         self.inputs = {
             'X': np.random.random((32, 84)).astype("float32"),
             'Y': np.random.random((84, 100)).astype("float32")
         }
-        self.attrs = {'use_mkldnn': self.use_mkldnn}
         self.outputs = {'Out': np.dot(self.inputs['X'], self.inputs['Y'])}
 
     def test_check_output(self):
@@ -47,16 +45,11 @@ class TestMulOp(OpTest):
 class TestMulOp2(OpTest):
     def setUp(self):
         self.op_type = "mul"
-        self.use_mkldnn = False
         self.inputs = {
             'X': np.random.random((15, 4, 12, 10)).astype("float32"),
             'Y': np.random.random((4, 30, 8, 2, 9)).astype("float32")
         }
-        self.attrs = {
-            'x_num_col_dims': 2,
-            'y_num_col_dims': 2,
-            'use_mkldnn': self.use_mkldnn
-        }
+        self.attrs = {'x_num_col_dims': 2, 'y_num_col_dims': 2}
         result = np.dot(self.inputs['X'].reshape(15 * 4, 12 * 10),
                         self.inputs['Y'].reshape(4 * 30, 8 * 2 * 9))
         result = result.reshape(15, 4, 8, 2, 9)
@@ -80,11 +73,9 @@ class TestMulOp2(OpTest):
 class TestFP16MulOp1(OpTest):
     def setUp(self):
         self.op_type = "mul"
-        self.use_mkldnn = False
         x = np.random.random((32, 84)).astype("float16")
         y = np.random.random((84, 100)).astype("float16")
         self.inputs = {'X': x.view(np.uint16), 'Y': y.view(np.uint16)}
-        self.attrs = {'use_mkldnn': self.use_mkldnn}
         self.outputs = {'Out': np.dot(x, y)}
 
     def test_check_output(self):
@@ -97,15 +88,10 @@ class TestFP16MulOp1(OpTest):
 class TestFP16MulOp2(OpTest):
     def setUp(self):
         self.op_type = "mul"
-        self.use_mkldnn = False
         x = np.random.random((15, 4, 12, 10)).astype("float16")
         y = np.random.random((4, 30, 8, 2, 9)).astype("float16")
         self.inputs = {'X': x.view(np.uint16), 'Y': y.view(np.uint16)}
-        self.attrs = {
-            'x_num_col_dims': 2,
-            'y_num_col_dims': 2,
-            'use_mkldnn': self.use_mkldnn
-        }
+        self.attrs = {'x_num_col_dims': 2, 'y_num_col_dims': 2}
         result = np.dot(
             x.reshape(15 * 4, 12 * 10), y.reshape(4 * 30, 8 * 2 * 9))
         result = result.reshape(15, 4, 8, 2, 9)

python/paddle/fluid/tests/unittests/test_operator_desc.py

@@ -63,10 +63,7 @@ class TestOperator(unittest.TestCase):
         self.assertEqual(mul_op.output("Out"), ["mul.out"])
         self.assertEqual(
             set(mul_op.attr_names),
-            set([
-                "x_num_col_dims", "y_num_col_dims", "use_mkldnn", "op_role",
-                "op_role_var"
-            ]))
+            set(["x_num_col_dims", "y_num_col_dims", "op_role", "op_role_var"]))
         self.assertEqual(mul_op.has_attr("x_num_col_dims"), True)
         self.assertEqual(mul_op.attr_type("x_num_col_dims"), core.AttrType.INT)
         self.assertEqual(mul_op.attr("x_num_col_dims"), 1)