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Adding logical operators for beam search and control flow (#5708)

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release/0.11.0
Abhinav Arora 8 years ago committed by GitHub
parent bce1c03a90
commit 6cfcf6245a
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GPG Key ID: 4AEE18F83AFDEB23
6 changed files with 315 additions and 0 deletions
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5
paddle/framework/data_type.h
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@ -46,6 +46,8 @@ inline std::type_index ToTypeIndex(DataType type) {
return typeid(int);
case DataType::INT64:
return typeid(int64_t);
case DataType::BOOL:
return typeid(bool);
default:
PADDLE_THROW("Not support type %d", type);
}
@ -66,6 +68,9 @@ inline void VisitDataType(DataType type, Visitor visitor) {
case DataType::INT64:
visitor.template operator()<int64_t>();
break;
case DataType::BOOL:
visitor.template operator()<bool>();
break;
default:
PADDLE_THROW("Not supported");
}

5
paddle/operators/CMakeLists.txt
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@ -87,6 +87,11 @@ function(op_library TARGET)
file(APPEND ${pybind_file} "USE_OP(pool2d_cudnn);\n")
endif()
if ("${TARGET}" STREQUAL "logical_op")
set(pybind_flag 1)
file(APPEND ${pybind_file} "USE_OP(logical_and);\n")
endif()
# pool_with_index_op contains several operators
if ("${TARGET}" STREQUAL "pool_with_index_op")
set(pybind_flag 1)

153
paddle/operators/logical_op.cc
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@ -0,0 +1,153 @@
/* Copyright (c) 2016 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/operators/logical_op.h"
#include "paddle/framework/op_registry.h"
namespace paddle {
namespace operators {
template <typename OpComment>
class BinaryLogicalOpProtoMaker : public framework::OpProtoAndCheckerMaker {
public:
BinaryLogicalOpProtoMaker(framework::OpProto *proto,
framework::OpAttrChecker *op_checker)
: OpProtoAndCheckerMaker(proto, op_checker) {
OpComment comment;
AddInput("X",
string::Sprintf("(LoDTensor) Left hand operand of %s operator",
comment.type));
AddInput("Y",
string::Sprintf("(LoDTensor) Right hand operand of %s operator",
comment.type));
AddOutput("Out", string::Sprintf(
"(LoDTensor) n-dim bool tensor. Each element is %s",
comment.equation));
AddComment(string::Sprintf(R"DOC(%s Operator
It operates element-wise on X and Y, and returns the Out. X, Y and Out are N-dim boolean tensors.
Each element of Out is calculated by %s
)DOC",
comment.type, comment.equation));
}
};
template <typename OpComment>
class UnaryLogicalOpProtoMaker : public framework::OpProtoAndCheckerMaker {
public:
UnaryLogicalOpProtoMaker(framework::OpProto *proto,
framework::OpAttrChecker *op_checker)
: OpProtoAndCheckerMaker(proto, op_checker) {
OpComment comment;
AddInput("X", string::Sprintf("(LoDTensor) Operand of %s operator",
comment.type));
AddOutput("Out", string::Sprintf(
"(LoDTensor) n-dim bool tensor. Each element is %s",
comment.equation));
AddComment(string::Sprintf(R"DOC(%s Operator
It operates element-wise on X, and returns the Out. X and Out are N-dim boolean tensors.
Each element of Out is calculated by %s
)DOC",
comment.type, comment.equation));
}
};
template <typename OpComment>
class BinaryLogicalOpInferShape : public framework::InferShapeBase {
public:
void operator()(framework::InferShapeContext *context) const override {
OpComment comment;
PADDLE_ENFORCE(context->HasInput("X"),
"Input(X) of %s operator must not be null", comment.type);
PADDLE_ENFORCE(context->HasInput("Y"),
"Input(Y) of %s operator must not be null", comment.type);
auto dim_x = context->GetInputDim("X");
auto dim_y = context->GetInputDim("Y");
PADDLE_ENFORCE_EQ(framework::product(dim_x), framework::product(dim_y),
"The number of elements in X and Y should be same");
context->SetOutputDim("Out", context->GetInputDim("X"));
context->ShareLoD("X", "Out");
}
};
template <typename OpComment>
class UnaryLogicalOpInferShape : public framework::InferShapeBase {
public:
void operator()(framework::InferShapeContext *context) const override {
OpComment comment;
PADDLE_ENFORCE(context->HasInput("X"),
"Input(X) of %s operator must not be null", comment.type);
auto dim_x = context->GetInputDim("X");
context->SetOutputDim("Out", context->GetInputDim("X"));
context->ShareLoD("X", "Out");
}
};
class LogicalOp : public framework::OperatorWithKernel {
public:
using framework::OperatorWithKernel::OperatorWithKernel;
protected:
framework::OpKernelType GetKernelType(
const framework::ExecutionContext &ctx) const override {
framework::OpKernelType kt = OperatorWithKernel::GetKernelType(ctx);
// LogicalOp kernel's device type is decided by input tensor place
kt.place_ = ctx.Input<framework::LoDTensor>("X")->place();
return kt;
}
};
} // namespace operators
} // namespace paddle
#define REGISTER_BINARY_LOGICAL_OP(op_type, _equation) \
struct _##op_type##Comment { \
static char type[]; \
static char equation[]; \
}; \
char _##op_type##Comment::type[]{#op_type}; \
char _##op_type##Comment::equation[]{_equation}; \
REGISTER_OPERATOR( \
op_type, ::paddle::operators::LogicalOp, \
::paddle::operators::BinaryLogicalOpProtoMaker<_##op_type##Comment>, \
::paddle::operators::BinaryLogicalOpInferShape<_##op_type##Comment>, \
::paddle::framework::EmptyGradOpMaker);
#define REGISTER_UNARY_LOGICAL_OP(op_type, _equation) \
struct _##op_type##Comment { \
static char type[]; \
static char equation[]; \
}; \
char _##op_type##Comment::type[]{#op_type}; \
char _##op_type##Comment::equation[]{_equation}; \
REGISTER_OPERATOR( \
op_type, ::paddle::operators::LogicalOp, \
::paddle::operators::UnaryLogicalOpProtoMaker<_##op_type##Comment>, \
::paddle::operators::UnaryLogicalOpInferShape<_##op_type##Comment>, \
::paddle::framework::EmptyGradOpMaker);
REGISTER_BINARY_LOGICAL_OP(logical_and, "Out = X && Y");
REGISTER_BINARY_LOGICAL_KERNEL(logical_and, CPU,
paddle::operators::LogicalAndFunctor);
REGISTER_BINARY_LOGICAL_OP(logical_or, "Out = X && Y");
REGISTER_BINARY_LOGICAL_KERNEL(logical_or, CPU,
paddle::operators::LogicalOrFunctor);
REGISTER_UNARY_LOGICAL_OP(logical_not, "Out = !X");
REGISTER_UNARY_LOGICAL_KERNEL(logical_not, CPU,
paddle::operators::LogicalNotFunctor);
REGISTER_BINARY_LOGICAL_OP(logical_xor, "Out = (X || Y) && !(X && Y)");
REGISTER_BINARY_LOGICAL_KERNEL(logical_xor, CPU,
paddle::operators::LogicalXorFunctor);

24
paddle/operators/logical_op.cu
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@ -0,0 +1,24 @@
/* Copyright (c) 2016 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/operators/logical_op.h"
REGISTER_BINARY_LOGICAL_KERNEL(logical_and, GPU,
paddle::operators::LogicalAndFunctor);
REGISTER_BINARY_LOGICAL_KERNEL(logical_or, GPU,
paddle::operators::LogicalOrFunctor);
REGISTER_UNARY_LOGICAL_KERNEL(logical_not, GPU,
paddle::operators::LogicalNotFunctor);
REGISTER_BINARY_LOGICAL_KERNEL(logical_xor, GPU,
paddle::operators::LogicalXorFunctor);

93
paddle/operators/logical_op.h
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@ -0,0 +1,93 @@
/* Copyright (c) 2016 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 <math.h>
#include <type_traits>
#include "paddle/framework/op_registry.h"
#include "paddle/platform/transform.h"
namespace paddle {
namespace operators {
template <typename T>
struct LogicalAndFunctor {
using ELEM_TYPE = T;
HOSTDEVICE bool operator()(const T& a, const T& b) const { return a && b; }
};
template <typename T>
struct LogicalOrFunctor {
using ELEM_TYPE = T;
HOSTDEVICE bool operator()(const T& a, const T& b) const { return a || b; }
};
template <typename T>
struct LogicalNotFunctor {
using ELEM_TYPE = T;
HOSTDEVICE bool operator()(const T& a) const { return !a; }
};
template <typename T>
struct LogicalXorFunctor {
using ELEM_TYPE = T;
HOSTDEVICE bool operator()(const T& a, const T& b) const {
return (a || b) && !(a && b);
}
};
template <typename Place, typename Functor>
class BinaryLogicalOpKernel
: public framework::OpKernel<typename Functor::ELEM_TYPE> {
public:
void Compute(const framework::ExecutionContext& context) const override {
using T = typename Functor::ELEM_TYPE;
auto* x = context.Input<framework::Tensor>("X");
auto* y = context.Input<framework::Tensor>("Y");
auto* out = context.Output<framework::Tensor>("Out");
Functor binary_func;
platform::Transform<Place> trans;
trans(context.device_context(), x->data<T>(), x->data<T>() + x->numel(),
y->data<T>(), out->mutable_data<bool>(context.GetPlace()),
binary_func);
}
};
template <typename Place, typename Functor>
class UnaryLogicalOpKernel
: public framework::OpKernel<typename Functor::ELEM_TYPE> {
public:
void Compute(const framework::ExecutionContext& context) const override {
using T = typename Functor::ELEM_TYPE;
auto* x = context.Input<framework::Tensor>("X");
auto* out = context.Output<framework::Tensor>("Out");
Functor unary_func;
platform::Transform<Place> trans;
trans(context.device_context(), x->data<T>(), x->data<T>() + x->numel(),
out->mutable_data<bool>(context.GetPlace()), unary_func);
}
};
} // namespace operators
} // namespace paddle
#define REGISTER_BINARY_LOGICAL_KERNEL(op_type, dev, functor) \
REGISTER_OP_##dev##_KERNEL( \
op_type, ::paddle::operators::BinaryLogicalOpKernel< \
::paddle::platform::dev##Place, functor<bool>>);
#define REGISTER_UNARY_LOGICAL_KERNEL(op_type, dev, functor) \
REGISTER_OP_##dev##_KERNEL( \
op_type, ::paddle::operators::UnaryLogicalOpKernel< \
::paddle::platform::dev##Place, functor<bool>>);

35
python/paddle/v2/fluid/tests/test_logical_op.py
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@ -0,0 +1,35 @@
import op_test
import unittest
import numpy as np
def create_test_class(op_type, callback, binary_op=True):
class Cls(op_test.OpTest):
def setUp(self):
a = np.random.choice(a=[True, False], size=(10, 7)).astype(bool)
if binary_op:
b = np.random.choice(a=[True, False], size=(10, 7)).astype(bool)
c = callback(a, b)
else:
c = callback(a)
self.outputs = {'Out': c}
self.op_type = op_type
if binary_op:
self.inputs = {'X': a, 'Y': b}
else:
self.inputs = {'X': a}
def test_output(self):
self.check_output()
Cls.__name__ = op_type
globals()[op_type] = Cls
create_test_class('logical_and', lambda _a, _b: np.logical_and(_a, _b))
create_test_class('logical_or', lambda _a, _b: np.logical_or(_a, _b))
create_test_class('logical_not', lambda _a: np.logical_not(_a), False)
create_test_class('logical_xor', lambda _a, _b: np.logical_xor(_a, _b))
if __name__ == '__main__':
unittest.main()
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