diff --git a/paddle/fluid/operators/mul_mkldnn_op.cc b/paddle/fluid/operators/mul_mkldnn_op.cc deleted file mode 100644 index a5f3a98f678a870d30eebfc4cf329de7c93266ee..0000000000000000000000000000000000000000 --- a/paddle/fluid/operators/mul_mkldnn_op.cc +++ /dev/null @@ -1,197 +0,0 @@ -/* 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 -mkldnn::memory::desc type(const std::vector& dims, Format&& f) { - return platform::MKLDNNMemDesc(dims, mkldnn::memory::data_type::f32, f); -} - -template -class MulMKLDNNOpKernel : public paddle::framework::OpKernel { - 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(); - auto mkldnn_engine = dev_ctx.GetEngine(); - - auto input = ctx.Input("X"); - auto weight = ctx.Input("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 w_tz = paddle::framework::vectorize2int(weight->dims()); - std::vector 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("Out"); - T* output_data = output->mutable_data(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(); - const T* w_data = weight->data(); - - 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_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 pipeline = {forward}; - mkldnn::stream(mkldnn::stream::kind::eager).submit(pipeline).wait(); - } -}; - -template -class MulMKLDNNGradOpKernel : public paddle::framework::OpKernel { - 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(); - auto mkldnn_engine = dev_ctx.GetEngine(); - - const Tensor* input = ctx.Input("X"); - const Tensor* w = ctx.Input("Y"); - - const Tensor* out_grad = ctx.Input(framework::GradVarName("Out")); - Tensor* input_grad = ctx.Output(framework::GradVarName("X")); - Tensor* w_grad = ctx.Output(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(); - const T* w_data = w->data(); - const T* out_grad_data = out_grad->data(); - T* input_grad_data = nullptr; - T* w_grad_data = nullptr; - - if (input_grad) { - input_grad_data = input_grad->mutable_data(ctx.GetPlace()); - } - if (w_grad) { - w_grad_data = w_grad->mutable_data(ctx.GetPlace()); - } - - std::vector src_tz = paddle::framework::vectorize2int(input->dims()); - std::vector 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( - 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 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_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 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); - -REGISTER_OP_KERNEL(mul_grad, MKLDNN, ::paddle::platform::CPUPlace, - paddle::operators::MulMKLDNNGradOpKernel); diff --git a/paddle/fluid/operators/mul_op.cc b/paddle/fluid/operators/mul_op.cc index a43739463c85b38e1dba04c6ec1bfcf4b6cbfa63..51993398bd3427e1f0da155918395bc50fa65e45 100644 --- a/paddle/fluid/operators/mul_op.cc +++ b/paddle/fluid/operators/mul_op.cc @@ -16,10 +16,6 @@ limitations under the License. */ #include #include -#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("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("use_mkldnn", - "(bool, default false) Only used in mkldnn kernel") - .SetDefault(false); AddAttr( "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("X")->type()), ctx.GetPlace(), - layout, library); - } }; } // namespace operators diff --git a/python/paddle/fluid/layers/nn.py b/python/paddle/fluid/layers/nn.py index 3bb9fd04038b2a0ee98cbfb17b5c0ea0b8b06789..63ec83151477770ea64070cae4f5e4fcc497f7af 100644 --- a/python/paddle/fluid/layers/nn.py +++ b/python/paddle/fluid/layers/nn.py @@ -179,11 +179,8 @@ 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: diff --git a/python/paddle/fluid/tests/unittests/test_mul_mkldnn_op.py b/python/paddle/fluid/tests/unittests/test_mul_mkldnn_op.py deleted file mode 100644 index 42d68ef376dc4a664a96ff5a24545c1997ee924a..0000000000000000000000000000000000000000 --- a/python/paddle/fluid/tests/unittests/test_mul_mkldnn_op.py +++ /dev/null @@ -1,44 +0,0 @@ -# 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() diff --git a/python/paddle/fluid/tests/unittests/test_mul_op.py b/python/paddle/fluid/tests/unittests/test_mul_op.py index d984393c89f44f5b9679a22bf7bb6182599233e3..862b7f8cb93620da4dd4673028776cfe565eeb0b 100644 --- a/python/paddle/fluid/tests/unittests/test_mul_op.py +++ b/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) diff --git a/python/paddle/fluid/tests/unittests/test_operator_desc.py b/python/paddle/fluid/tests/unittests/test_operator_desc.py index 8b15aa6822aee7bb4d53dcf1d87565fae5504821..c098a5a0cb0364f9ec93c95c1ef50912e574b3d9 100644 --- a/python/paddle/fluid/tests/unittests/test_operator_desc.py +++ b/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)