提交 50870a62 编写于 作者: T Tao Luo 提交者: GitHub

Merge pull request #3881 from luotao1/op_refine

Op refine for making build system more automatic
...@@ -3,7 +3,7 @@ ...@@ -3,7 +3,7 @@
#include "paddle/framework/op_registry.h" #include "paddle/framework/op_registry.h"
#include "paddle/framework/operator.h" #include "paddle/framework/operator.h"
USE_OP(add_two); USE_OP(add);
namespace paddle { namespace paddle {
namespace framework { namespace framework {
...@@ -41,7 +41,7 @@ namespace f = paddle::framework; ...@@ -41,7 +41,7 @@ namespace f = paddle::framework;
TEST(GradOpBuilder, AddTwo) { TEST(GradOpBuilder, AddTwo) {
std::shared_ptr<f::OperatorBase> add_op(f::OpRegistry::CreateOp( std::shared_ptr<f::OperatorBase> add_op(f::OpRegistry::CreateOp(
"add_two", {{"X", {"x"}}, {"Y", {"y"}}}, {{"Out", {"out"}}}, {})); "add", {{"X", {"x"}}, {"Y", {"y"}}}, {{"Out", {"out"}}}, {}));
std::shared_ptr<f::OperatorBase> grad_add_op = std::shared_ptr<f::OperatorBase> grad_add_op =
f::OpRegistry::CreateGradOp(*add_op); f::OpRegistry::CreateGradOp(*add_op);
EXPECT_EQ(grad_add_op->Inputs().size(), 4UL); EXPECT_EQ(grad_add_op->Inputs().size(), 4UL);
......
...@@ -14,6 +14,15 @@ function(op_library TARGET) ...@@ -14,6 +14,15 @@ function(op_library TARGET)
cmake_parse_arguments(op_library "${options}" "${oneValueArgs}" cmake_parse_arguments(op_library "${options}" "${oneValueArgs}"
"${multiValueArgs}" ${ARGN}) "${multiValueArgs}" ${ARGN})
list(LENGTH op_library_SRCS op_library_SRCS_len)
if (${op_library_SRCS_len} EQUAL 0)
if (EXISTS ${CMAKE_CURRENT_SOURCE_DIR}/${TARGET}.cc)
list(APPEND cc_srcs ${TARGET}.cc)
endif()
if (EXISTS ${CMAKE_CURRENT_SOURCE_DIR}/${TARGET}.cu)
list(APPEND cu_srcs ${TARGET}.cu)
endif()
else()
foreach(src ${op_library_SRCS}) foreach(src ${op_library_SRCS})
if (${src} MATCHES ".*\\.cu$") if (${src} MATCHES ".*\\.cu$")
list(APPEND cu_srcs ${src}) list(APPEND cu_srcs ${src})
...@@ -23,18 +32,13 @@ function(op_library TARGET) ...@@ -23,18 +32,13 @@ function(op_library TARGET)
message(FATAL_ERROR "${TARGET} Source file ${src} should only be .cc or .cu") message(FATAL_ERROR "${TARGET} Source file ${src} should only be .cc or .cu")
endif() endif()
endforeach() endforeach()
endif()
list(LENGTH cc_srcs cc_srcs_len) list(LENGTH cc_srcs cc_srcs_len)
if (${cc_srcs_len} EQUAL 0) if (${cc_srcs_len} EQUAL 0)
message(FATAL_ERROR "The op library ${TARGET} should contains at least one .cc file") message(FATAL_ERROR "The op library ${TARGET} should contains at least one .cc file")
endif() endif()
list(LENGTH cu_srcs cu_srcs_len)
list(LENGTH op_library_DEPS dep_len)
if (${cu_srcs_len} EQUAL 0 AND ${dep_len} EQUAL 0)
message(WARNING "The op library ${TARGET} not support GPU!")
endif()
if (WITH_GPU) if (WITH_GPU)
nv_library(${TARGET} SRCS ${cc_srcs} ${cu_srcs} DEPS ${op_library_DEPS} nv_library(${TARGET} SRCS ${cc_srcs} ${cu_srcs} DEPS ${op_library_DEPS}
${op_common_deps}) ${op_common_deps})
...@@ -46,22 +50,22 @@ endfunction() ...@@ -46,22 +50,22 @@ endfunction()
add_subdirectory(math) add_subdirectory(math)
list(REMOVE_ITEM GENERAL_OPS set(DEPS_OPS
net_op identity_op
minus_op minus_op
mul_op mul_op
recurrent_op recurrent_op
scale_op) scale_op)
op_library(identity_op DEPS scale_op)
op_library(net_op SRCS net_op.cc) op_library(minus_op DEPS scale_op)
op_library(minus_op SRCS minus_op.cc minus_op.cu DEPS scale_op) op_library(mul_op DEPS math_function)
op_library(mul_op SRCS mul_op.cc mul_op.cu DEPS math_function)
op_library(recurrent_op SRCS recurrent_op.cc rnn/recurrent_op_utils.cc op_library(recurrent_op SRCS recurrent_op.cc rnn/recurrent_op_utils.cc
DEPS framework_proto tensor operator net_op) DEPS framework_proto tensor operator net_op)
op_library(scale_op SRCS scale_op.cc scale_op.cu DEPS net_op) op_library(scale_op DEPS net_op)
list(REMOVE_ITEM GENERAL_OPS ${DEPS_OPS})
foreach(src ${GENERAL_OPS}) foreach(src ${GENERAL_OPS})
op_library(${src} SRCS ${src}.cc ${src}.cu) op_library(${src})
endforeach() endforeach()
set(GLOB_OP_LIB ${OP_LIBRARY} CACHE INTERNAL "Global OP library") set(GLOB_OP_LIB ${OP_LIBRARY} CACHE INTERNAL "Global OP library")
......
...@@ -57,7 +57,6 @@ class AddOpGrad : public framework::OperatorWithKernel { ...@@ -57,7 +57,6 @@ class AddOpGrad : public framework::OperatorWithKernel {
} // namespace paddle } // namespace paddle
namespace ops = paddle::operators; namespace ops = paddle::operators;
REGISTER_OP(add_two, ops::AddOp, ops::AddOpMaker, add_two_grad, ops::AddOpGrad); REGISTER_OP(add, ops::AddOp, ops::AddOpMaker, add_grad, ops::AddOpGrad);
REGISTER_OP_CPU_KERNEL(add_two, REGISTER_OP_CPU_KERNEL(add, ops::AddKernel<paddle::platform::CPUPlace, float>);
ops::AddKernel<paddle::platform::CPUPlace, float>);
...@@ -12,10 +12,7 @@ ...@@ -12,10 +12,7 @@
See the License for the specific language governing permissions and See the License for the specific language governing permissions and
limitations under the License. */ limitations under the License. */
#define EIGEN_USE_GPU
#include "paddle/framework/op_registry.h"
#include "paddle/operators/add_op.h" #include "paddle/operators/add_op.h"
namespace ops = paddle::operators; namespace ops = paddle::operators;
REGISTER_OP_GPU_KERNEL(add_two, REGISTER_OP_GPU_KERNEL(add, ops::AddKernel<paddle::platform::GPUPlace, float>);
ops::AddKernel<paddle::platform::GPUPlace, float>);
...@@ -12,9 +12,43 @@ ...@@ -12,9 +12,43 @@
See the License for the specific language governing permissions and See the License for the specific language governing permissions and
limitations under the License. */ limitations under the License. */
#define EIGEN_USE_GPU #include "paddle/operators/net_op.h"
#include "paddle/operators/gather_op.h" #include "paddle/operators/scale_op.h"
namespace paddle {
namespace operators {
// identity is a alias of scale op. This is also a example for creating a alias
// operator.
template <typename AttrType>
class IdentityOpMaker : public framework::OpProtoAndCheckerMaker {
public:
IdentityOpMaker(framework::OpProto *proto,
framework::OpAttrChecker *op_checker)
: OpProtoAndCheckerMaker(proto, op_checker) {
AddInput("X", "input tensor of identity op");
AddOutput("Out", "output tensor of identity op");
AddComment("identity operator. Just a alias of scale op which scale = 1.0");
}
};
template <typename AttrType>
class IdentityOp : public NetOp {
public:
IdentityOp(const std::string &type, const framework::VariableNameMap &inputs,
const framework::VariableNameMap &outputs,
const framework::AttributeMap &attrs)
: NetOp(type, inputs, outputs, attrs) {
AppendOp(framework::OpRegistry::CreateOp(
"scale", {{"X", {Input("X")}}}, {{"Out", {Output("Out")}}},
{{"scale", static_cast<AttrType>(1)}}));
}
};
} // namespace operators
} // namespace paddle
namespace ops = paddle::operators; namespace ops = paddle::operators;
REGISTER_OP_GPU_KERNEL(gather,
ops::GatherOpKernel<paddle::platform::GPUPlace, float>); REGISTER_OP_WITHOUT_GRADIENT(identity, ops::IdentityOp<float>,
ops::IdentityOpMaker<float>);
...@@ -48,7 +48,7 @@ The equation is: Out = scale*X ...@@ -48,7 +48,7 @@ The equation is: Out = scale*X
} }
}; };
// Identity Op's gradient is identity op, too. // Scale Op's gradient is scale op, too.
// Grad(Out=scale(X)) => Grad(X) = scale(Grad(Out)) // Grad(Out=scale(X)) => Grad(X) = scale(Grad(Out))
template <typename AttrType> template <typename AttrType>
class ScaleGradOp : public NetOp { class ScaleGradOp : public NetOp {
...@@ -65,33 +65,6 @@ class ScaleGradOp : public NetOp { ...@@ -65,33 +65,6 @@ class ScaleGradOp : public NetOp {
} }
}; };
// identity is a alias of scale op. This is also a example for creating a alias
// operator.
template <typename AttrType>
class IdentityOpMaker : public framework::OpProtoAndCheckerMaker {
public:
IdentityOpMaker(framework::OpProto *proto,
framework::OpAttrChecker *op_checker)
: OpProtoAndCheckerMaker(proto, op_checker) {
AddInput("X", "input tensor of identity op");
AddOutput("Out", "output tensor of identity op");
AddComment("identity operator. Just a alias of scale op which scale = 1.0");
}
};
template <typename AttrType>
class IdentityOp : public NetOp {
public:
IdentityOp(const std::string &type, const framework::VariableNameMap &inputs,
const framework::VariableNameMap &outputs,
const framework::AttributeMap &attrs)
: NetOp(type, inputs, outputs, attrs) {
AppendOp(framework::OpRegistry::CreateOp(
"scale", {{"X", {Input("X")}}}, {{"Out", {Output("Out")}}},
{{"scale", static_cast<AttrType>(1)}}));
}
};
} // namespace operators } // namespace operators
} // namespace paddle } // namespace paddle
...@@ -101,5 +74,3 @@ REGISTER_OP(scale, ops::ScaleOp, ops::ScaleOpMaker<float>, scale_grad, ...@@ -101,5 +74,3 @@ REGISTER_OP(scale, ops::ScaleOp, ops::ScaleOpMaker<float>, scale_grad,
ops::ScaleGradOp<float>); ops::ScaleGradOp<float>);
REGISTER_OP_CPU_KERNEL(scale, REGISTER_OP_CPU_KERNEL(scale,
ops::ScaleKernel<paddle::platform::CPUPlace, float>); ops::ScaleKernel<paddle::platform::CPUPlace, float>);
REGISTER_OP_WITHOUT_GRADIENT(identity, ops::IdentityOp<float>,
ops::IdentityOpMaker<float>);
/* Copyright (c) 2016 PaddlePaddle Authors. All Rights Reserve.
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. */
#define EIGEN_USE_GPU
#include "paddle/operators/scatter_op.h"
namespace ops = paddle::operators;
REGISTER_OP_GPU_KERNEL(scatter,
ops::ScatterOpKernel<paddle::platform::GPUPlace, float>);
...@@ -30,7 +30,7 @@ limitations under the License. */ ...@@ -30,7 +30,7 @@ limitations under the License. */
namespace py = pybind11; namespace py = pybind11;
USE_OP(add_two); USE_OP(add);
USE_OP(onehot_cross_entropy); USE_OP(onehot_cross_entropy);
USE_OP(sgd); USE_OP(sgd);
USE_OP(mul); USE_OP(mul);
......
...@@ -11,7 +11,7 @@ class TestAddOp(unittest.TestCase): ...@@ -11,7 +11,7 @@ class TestAddOp(unittest.TestCase):
__metaclass__ = OpTestMeta __metaclass__ = OpTestMeta
def setUp(self): def setUp(self):
self.type = "add_two" self.type = "add"
self.inputs = { self.inputs = {
'X': numpy.random.random((102, 105)).astype("float32"), 'X': numpy.random.random((102, 105)).astype("float32"),
'Y': numpy.random.random((102, 105)).astype("float32") 'Y': numpy.random.random((102, 105)).astype("float32")
......
...@@ -7,7 +7,7 @@ from gradient_checker import get_numeric_gradient ...@@ -7,7 +7,7 @@ from gradient_checker import get_numeric_gradient
class GetNumericGradientTest(unittest.TestCase): class GetNumericGradientTest(unittest.TestCase):
def test_add_op(self): def test_add_op(self):
add_op = Operator('add_two', X="X", Y="Y", Out="Z") add_op = Operator('add', X="X", Y="Y", Out="Z")
x = numpy.random.random((10, 1)).astype("float32") x = numpy.random.random((10, 1)).astype("float32")
y = numpy.random.random((10, 1)).astype("float32") y = numpy.random.random((10, 1)).astype("float32")
......
...@@ -15,7 +15,7 @@ def fc(X, W, Y): ...@@ -15,7 +15,7 @@ def fc(X, W, Y):
class TestNet(unittest.TestCase): class TestNet(unittest.TestCase):
def test_net_all(self): def test_net_all(self):
net = core.Net.create() net = core.Net.create()
op1 = Operator("add_two", X="X", Y="Y", Out="Out") op1 = Operator("add", X="X", Y="Y", Out="Out")
net.append_op(op1) net.append_op(op1)
net2 = core.Net.create() net2 = core.Net.create()
...@@ -26,7 +26,7 @@ class TestNet(unittest.TestCase): ...@@ -26,7 +26,7 @@ class TestNet(unittest.TestCase):
expected = ''' expected = '''
Op(plain_net), inputs:{all[W, X, Y]}, outputs:{all[Out, fc.out, pre_activation]}. Op(plain_net), inputs:{all[W, X, Y]}, outputs:{all[Out, fc.out, pre_activation]}.
Op(add_two), inputs:{X[X], Y[Y]}, outputs:{Out[Out]}. Op(add), inputs:{X[X], Y[Y]}, outputs:{Out[Out]}.
Op(plain_net), inputs:{all[W, X]}, outputs:{all[fc.out, pre_activation]}. Op(plain_net), inputs:{all[W, X]}, outputs:{all[fc.out, pre_activation]}.
Op(plain_net), inputs:{all[W, X]}, outputs:{all[fc.out, pre_activation]}. Op(plain_net), inputs:{all[W, X]}, outputs:{all[fc.out, pre_activation]}.
Op(mul), inputs:{X[X], Y[W]}, outputs:{Out[pre_activation]}. Op(mul), inputs:{X[X], Y[W]}, outputs:{Out[pre_activation]}.
......
...@@ -193,10 +193,10 @@ class TestOpDescCreationMethod(unittest.TestCase): ...@@ -193,10 +193,10 @@ class TestOpDescCreationMethod(unittest.TestCase):
class TestOpCreations(unittest.TestCase): class TestOpCreations(unittest.TestCase):
def test_all(self): def test_all(self):
add_op = op.Operator("add_two", X="a", Y="b", Out="z") add_op = op.Operator("add", X="a", Y="b", Out="z")
self.assertIsNotNone(add_op) self.assertIsNotNone(add_op)
# Invoke C++ DebugString() # Invoke C++ DebugString()
self.assertEqual('Op(add_two), inputs:{X[a], Y[b]}, outputs:{Out[z]}.', self.assertEqual('Op(add), inputs:{X[a], Y[b]}, outputs:{Out[z]}.',
str(add_op)) str(add_op))
......
...@@ -146,7 +146,7 @@ class TestRecurrentOp(unittest.TestCase): ...@@ -146,7 +146,7 @@ class TestRecurrentOp(unittest.TestCase):
stepnet = core.Net.create() stepnet = core.Net.create()
x_fc_op = Operator("mul", X="x@alias", Y="W", Out="Wx") x_fc_op = Operator("mul", X="x@alias", Y="W", Out="Wx")
h_fc_op = Operator("mul", X="h@pre", Y="U", Out="Uh") h_fc_op = Operator("mul", X="h@pre", Y="U", Out="Uh")
sum_op = Operator("add_two", X="Wx", Y="Uh", Out="sum") sum_op = Operator("add", X="Wx", Y="Uh", Out="sum")
sig_op = Operator("sigmoid", X="sum", Y="h@alias") sig_op = Operator("sigmoid", X="sum", Y="h@alias")
for op in [x_fc_op, h_fc_op, sum_op, sig_op]: for op in [x_fc_op, h_fc_op, sum_op, sig_op]:
......
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