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提交 9949681a 编写于 作者: H hjchen2
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Aggregate activation operations, add log and lod_reset op

上级 6e6d5dde
隐藏空白更改
内联 并排
Showing with 489 addition and 180 deletion
src/common/types.cpp
浏览文件 @ 9949681a
...@@ -73,6 +73,8 @@ const char *G_OP_TYPE_SHAPE = "shape"; ...@@ -73,6 +73,8 @@ const char *G_OP_TYPE_SHAPE = "shape";
const char *G_OP_TYPE_SUM = "sum"; const char *G_OP_TYPE_SUM = "sum";
const char *G_OP_TYPE_TOP_K = "top_k"; const char *G_OP_TYPE_TOP_K = "top_k";
const char *G_OP_TYPE_CAST = "cast"; const char *G_OP_TYPE_CAST = "cast";
const char *G_OP_TYPE_LOG = "log";
const char *G_OP_TYPE_LOD_RESET = "lod_reset";
const char *G_OP_TYPE_QUANTIZE = "quantize"; const char *G_OP_TYPE_QUANTIZE = "quantize";
const char *G_OP_TYPE_DEQUANTIZE = "dequantize"; const char *G_OP_TYPE_DEQUANTIZE = "dequantize";
...@@ -171,5 +173,7 @@ std::unordered_map< ...@@ -171,5 +173,7 @@ std::unordered_map<
{G_OP_TYPE_SEQUENCE_EXPAND, {{"X", "Y"}, {"Out"}}}, {G_OP_TYPE_SEQUENCE_EXPAND, {{"X", "Y"}, {"Out"}}},
{G_OP_TYPE_SEQUENCE_POOL, {{"X"}, {"Out"}}}, {G_OP_TYPE_SEQUENCE_POOL, {{"X"}, {"Out"}}},
{G_OP_TYPE_SEQUENCE_SOFTMAX, {{"X"}, {"Out"}}}, {G_OP_TYPE_SEQUENCE_SOFTMAX, {{"X"}, {"Out"}}},
{G_OP_TYPE_NORM, {{"X"}, {"Out", "Norm"}}}}; {G_OP_TYPE_NORM, {{"X"}, {"Out", "Norm"}}},
{G_OP_TYPE_LOG, {{"X"}, {"Out"}}},
{G_OP_TYPE_LOD_RESET, {{"X", "Y"}, {"Out"}}}};
} // namespace paddle_mobile } // namespace paddle_mobile
src/common/types.h
浏览文件 @ 9949681a
...@@ -100,6 +100,7 @@ enum ActivationType { ...@@ -100,6 +100,7 @@ enum ActivationType {
LEAKY_RELU = 4, LEAKY_RELU = 4,
TANH = 5, TANH = 5,
SIGMOID = 6, SIGMOID = 6,
LOG = 7,
}; };
enum PoolingType { enum PoolingType {
...@@ -155,6 +156,8 @@ extern const char *G_OP_TYPE_PRELU; ...@@ -155,6 +156,8 @@ extern const char *G_OP_TYPE_PRELU;
extern const char *G_OP_TYPE_SUM; extern const char *G_OP_TYPE_SUM;
extern const char *G_OP_TYPE_TOP_K; extern const char *G_OP_TYPE_TOP_K;
extern const char *G_OP_TYPE_CAST; extern const char *G_OP_TYPE_CAST;
extern const char *G_OP_TYPE_LOG;
extern const char *G_OP_TYPE_LOD_RESET;
extern const char *G_OP_TYPE_QUANTIZE; extern const char *G_OP_TYPE_QUANTIZE;
extern const char *G_OP_TYPE_DEQUANTIZE; extern const char *G_OP_TYPE_DEQUANTIZE;
......
src/framework/load_ops.h
浏览文件 @ 9949681a
...@@ -270,3 +270,6 @@ LOAD_OP1(sequence_expand, CPU); ...@@ -270,3 +270,6 @@ LOAD_OP1(sequence_expand, CPU);
#ifdef SEQUENCE_POOL_OP #ifdef SEQUENCE_POOL_OP
LOAD_OP1(sequence_pool, CPU); LOAD_OP1(sequence_pool, CPU);
#endif #endif
#ifdef LOG_OP
LOAD_OP1(log, CPU);
#endif
src/framework/operator.h
浏览文件 @ 9949681a
...@@ -36,13 +36,12 @@ limitations under the License. */ ...@@ -36,13 +36,12 @@ limitations under the License. */
#include "framework/cl/cl_helper.h" #include "framework/cl/cl_helper.h"
#include "framework/cl/cl_scope.h" #include "framework/cl/cl_scope.h"
#endif #endif
namespace paddle_mobile { namespace paddle_mobile {
namespace framework { namespace framework {
using std::string;
using std::vector;
template <typename T> template <typename T>
static T *GetVarValue(const string &key, const VariableNameMap &var_map, static T *GetVarValue(const std::string &key, const VariableNameMap &var_map,
const Scope &scope) { const Scope &scope) {
auto var_vec = var_map.at(key); auto var_vec = var_map.at(key);
if (!var_vec.empty()) { if (!var_vec.empty()) {
...@@ -56,44 +55,29 @@ static T *GetVarValue(const string &key, const VariableNameMap &var_map, ...@@ -56,44 +55,29 @@ static T *GetVarValue(const string &key, const VariableNameMap &var_map,
template <typename Dtype> template <typename Dtype>
class OperatorBase { class OperatorBase {
public: public:
/*
* @b op 基类的实例化方法, op 获取到了 输入、参数以及提前分配好的输出 tensor
* */
OperatorBase(const std::string &type, const VariableNameMap &inputs, OperatorBase(const std::string &type, const VariableNameMap &inputs,
const VariableNameMap &outputs, const AttributeMap &attrs, const VariableNameMap &outputs, const AttributeMap &attrs,
std::shared_ptr<Scope> scope); std::shared_ptr<Scope> scope);
virtual ~OperatorBase() {} virtual ~OperatorBase() {}
void Run();
std::vector<string> GetOutKeys() const;
std::vector<string> GetInputKeys() const;
virtual void RunImpl() = 0;
virtual void Init() = 0; virtual void Init() = 0;
/* virtual void InferShape() const = 0;
* @b op 运算所需的输入, 如上一层的输出结果、卷积核 virtual void Run();
* */ virtual void RunImpl() = 0;
std::vector<std::string> GetOutKeys() const;
std::vector<std::string> GetInputKeys() const;
const VariableNameMap &Inputs() const { return inputs_; } const VariableNameMap &Inputs() const { return inputs_; }
/*
* @b op 的输出, 内存会提前被分配好, 运算结果会被存到分配好的内存内
* */
const VariableNameMap &Outputs() const { return outputs_; } const VariableNameMap &Outputs() const { return outputs_; }
/*
* @b op 类型
* */
const std::string &Type() const { return type_; } const std::string &Type() const { return type_; }
/*
* @b op 运算所需要用到的参数: 如 conv 运算所需要用到的 stride
* */
const AttributeMap &Attrs() const { return attrs_; } const AttributeMap &Attrs() const { return attrs_; }
void ClearVariables(const std::vector<std::string> &var_names) const { void ClearVariables(const std::vector<std::string> &var_names) const {
if (this->scope_) { if (this->scope_) {
this->scope_->EraseVars(var_names); this->scope_->EraseVars(var_names);
} }
} }
/*
* @b 根据输入形状和参数计算出输出形状
* */
virtual void InferShape() const = 0;
protected: protected:
std::shared_ptr<Scope> scope_; std::shared_ptr<Scope> scope_;
...@@ -106,9 +90,6 @@ class OperatorBase { ...@@ -106,9 +90,6 @@ class OperatorBase {
void CheckAllInputOutputSet() const; void CheckAllInputOutputSet() const;
}; };
/*
* @b 这个类为所有带有运算的 op 的父类, 这个 op 继承与 OperatorBase
* */
template <typename Dtype, typename ParamType, typename KernelType> template <typename Dtype, typename ParamType, typename KernelType>
class OperatorWithKernel : public OperatorBase<Dtype> { class OperatorWithKernel : public OperatorBase<Dtype> {
public: public:
...@@ -136,9 +117,6 @@ class OperatorWithKernel : public OperatorBase<Dtype> { ...@@ -136,9 +117,6 @@ class OperatorWithKernel : public OperatorBase<Dtype> {
ParamType param_; ParamType param_;
}; };
/*
* @b 所有kernel的父类
* */
template <typename Dtype, typename P> template <typename Dtype, typename P>
class OpKernelBase { class OpKernelBase {
public: public:
...@@ -150,11 +128,6 @@ class OpKernelBase { ...@@ -150,11 +128,6 @@ class OpKernelBase {
} }
#endif #endif
/*
* @b 所有kernel 需实现 Compute 方法
* @p para 这个参数为 kernel 运算时所需要用到参数组成的一个结构体,
* 所有结构体存在与: paddle-mobile/src/operators/op_param.h
* */
#ifdef PADDLE_McOBILE_MALI_GPU #ifdef PADDLE_McOBILE_MALI_GPU
OpKernelBase() { acl_op_ = nullptr; } OpKernelBase() { acl_op_ = nullptr; }
void *GetAclOp() const { return acl_op_; } void *GetAclOp() const { return acl_op_; }
...@@ -177,6 +150,23 @@ class OpKernelBase { ...@@ -177,6 +150,23 @@ class OpKernelBase {
#endif #endif
}; };
#define DECLARE_OPERATOR(OpName, OpParam, OpKernel) \
template <typename DeviceType, typename T> \
class OpName##Op : public framework::OperatorWithKernel< \
DeviceType, OpParam<DeviceType>, \
operators::OpKernel<DeviceType, T>> { \
public: \
OpName##Op(const std::string &type, const VariableNameMap &inputs, \
const VariableNameMap &outputs, \
const framework::AttributeMap &attrs, \
std::shared_ptr<framework::Scope> scope) \
: framework::OperatorWithKernel<DeviceType, OpParam<DeviceType>, \
operators::OpKernel<DeviceType, T>>( \
type, inputs, outputs, attrs, scope) {} \
\
void InferShape() const override; \
};
#define DEFINE_OP_CONSTRUCTOR(cls, parent_cls) \ #define DEFINE_OP_CONSTRUCTOR(cls, parent_cls) \
cls(const std::string &type, const ::paddle_mobile::VariableNameMap &inputs, \ cls(const std::string &type, const ::paddle_mobile::VariableNameMap &inputs, \
const ::paddle_mobile::VariableNameMap &outputs, \ const ::paddle_mobile::VariableNameMap &outputs, \
...@@ -202,7 +192,6 @@ class FusionOpMatcher { ...@@ -202,7 +192,6 @@ class FusionOpMatcher {
virtual std::vector<std::pair<int, std::string>> NeedCheck() { return {}; } virtual std::vector<std::pair<int, std::string>> NeedCheck() { return {}; }
// virtual bool Fusion();
protected: protected:
Node node_; Node node_;
std::string type_; std::string type_;
......
src/operators/relu_op.cpp → src/operators/activation_op.cpp
浏览文件 @ 9949681a
...@@ -12,29 +12,40 @@ WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. ...@@ -12,29 +12,40 @@ WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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. */
#ifdef RELU_OP #include "operators/activation_op.h"
#include "operators/relu_op.h"
namespace paddle_mobile { namespace paddle_mobile {
namespace operators { namespace operators {
template <typename Dtype, typename T> #define DEFINE_INFERSHAPE(OpName) \
void ReluOp<Dtype, T>::InferShape() const { template <typename Dtype, typename T> \
auto input_dims = this->param_.InputX()->dims(); void OpName##Op<Dtype, T>::InferShape() const { \
this->param_.Out()->Resize(input_dims); const auto &input_dims = this->param_.InputX()->dims(); \
} this->param_.Out()->Resize(input_dims); \
}
#ifdef RELU_OP
DEFINE_INFERSHAPE(Relu);
DEFINE_INFERSHAPE(Relu6);
#endif // RELU_OP
template <typename Dtype, typename T> #ifdef SIGMOID_OP
void Relu6Op<Dtype, T>::InferShape() const { DEFINE_INFERSHAPE(Sigmoid);
auto input_dims = this->param_.InputX()->dims(); #endif // SIGMOID_OP
this->param_.Out()->Resize(input_dims);
} #ifdef TANH_OP
DEFINE_INFERSHAPE(Tanh);
#endif // TANH_OP
#ifdef LOG_OP
DEFINE_INFERSHAPE(Log);
#endif // LOG_OP
} // namespace operators } // namespace operators
} // namespace paddle_mobile } // namespace paddle_mobile
namespace ops = paddle_mobile::operators; namespace ops = paddle_mobile::operators;
#ifdef RELU_OP
#ifdef PADDLE_MOBILE_CPU #ifdef PADDLE_MOBILE_CPU
REGISTER_OPERATOR_CPU(relu, ops::ReluOp); REGISTER_OPERATOR_CPU(relu, ops::ReluOp);
REGISTER_OPERATOR_CPU(relu6, ops::Relu6Op); REGISTER_OPERATOR_CPU(relu6, ops::Relu6Op);
...@@ -47,5 +58,23 @@ REGISTER_OPERATOR_MALI_GPU(relu, ops::ReluOp); ...@@ -47,5 +58,23 @@ REGISTER_OPERATOR_MALI_GPU(relu, ops::ReluOp);
#ifdef PADDLE_MOBILE_CL #ifdef PADDLE_MOBILE_CL
REGISTER_OPERATOR_CL(relu, ops::ReluOp); REGISTER_OPERATOR_CL(relu, ops::ReluOp);
#endif #endif
#endif // RELU_OP #endif // RELU_OP
#ifdef SIGMOID_OP
#ifdef PADDLE_MOBILE_CPU
REGISTER_OPERATOR_CPU(sigmoid, ops::SigmoidOp);
#endif
#endif // SIGMOID_OP
#ifdef TANH_OP
#ifdef PADDLE_MOBILE_CPU
REGISTER_OPERATOR_CPU(tanh, ops::TanhOp);
#endif
#ifdef PADDLE_MOBILE_FPGA
REGISTER_OPERATOR_FPGA(tanh, ops::TanhOp);
#endif
#endif // TANH_OP
#ifdef LOG_OP
REGISTER_OPERATOR_CPU(log, ops::LogOp);
#endif // LOG_OP
src/operators/tanh_op.h → src/operators/activation_op.h
浏览文件 @ 9949681a
...@@ -12,8 +12,6 @@ WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. ...@@ -12,8 +12,6 @@ WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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. */
#ifdef TANH_OP
#pragma once #pragma once
#include <string> #include <string>
...@@ -24,21 +22,22 @@ limitations under the License. */ ...@@ -24,21 +22,22 @@ limitations under the License. */
namespace paddle_mobile { namespace paddle_mobile {
namespace operators { namespace operators {
template <typename DeviceType, typename T> #ifdef RELU_OP
class TanhOp : public framework::OperatorWithKernel< DECLARE_OPERATOR(Relu, ReluParam, ReluKernel);
DeviceType, TanhParam<DeviceType>, DECLARE_OPERATOR(Relu6, ReluParam, Relu6Kernel);
operators::TanhKernel<DeviceType, T>> { #endif
public:
TanhOp(const std::string &type, const VariableNameMap &inputs,
const VariableNameMap &outputs, const framework::AttributeMap &attrs,
std::shared_ptr<framework::Scope> scope)
: framework::OperatorWithKernel<DeviceType, TanhParam<DeviceType>,
operators::TanhKernel<DeviceType, T>>(
type, inputs, outputs, attrs, scope) {}
void InferShape() const override;
};
} // namespace operators #ifdef SIGMOID_OP
} // namespace paddle_mobile DECLARE_OPERATOR(Sigmoid, SigmoidParam, SigmoidKernel);
#endif
#ifdef TANH_OP
DECLARE_OPERATOR(Tanh, TanhParam, TanhKernel);
#endif
#ifdef LOG_OP
DECLARE_OPERATOR(Log, ReluParam, LogKernel);
#endif #endif
} // namespace operators
} // namespace paddle_mobile
src/operators/kernel/activation_kernel.h
浏览文件 @ 9949681a
...@@ -20,26 +20,30 @@ limitations under the License. */ ...@@ -20,26 +20,30 @@ limitations under the License. */
namespace paddle_mobile { namespace paddle_mobile {
namespace operators { namespace operators {
#define DECLARE_KERNEL(KernelClass, KernelParam) \ #define DECLARE_KERNEL(OpName, Param) \
template <typename DeviceType, typename T> \ template <typename DeviceType, typename T> \
class KernelClass \ class OpName##Kernel \
: public framework::OpKernelBase<DeviceType, KernelParam<DeviceType>> { \ : public framework::OpKernelBase<DeviceType, Param<DeviceType>> { \
public: \ public: \
bool Init(KernelParam<DeviceType> *param); \ bool Init(Param<DeviceType> *param); \
void Compute(const KernelParam<DeviceType> &param); \ void Compute(const Param<DeviceType> &param); \
}; };
#ifdef RELU_OP #ifdef RELU_OP
DECLARE_KERNEL(ReluKernel, ReluParam); DECLARE_KERNEL(Relu, ReluParam);
DECLARE_KERNEL(Relu6Kernel, ReluParam); DECLARE_KERNEL(Relu6, ReluParam);
#endif #endif
#ifdef SIGMOID_OP #ifdef SIGMOID_OP
DECLARE_KERNEL(SigmoidKernel, SigmoidParam); DECLARE_KERNEL(Sigmoid, SigmoidParam);
#endif #endif
#ifdef TANH_OP #ifdef TANH_OP
DECLARE_KERNEL(TanhKernel, TanhParam); DECLARE_KERNEL(Tanh, TanhParam);
#endif
#ifdef LOG_OP
DECLARE_KERNEL(Log, ReluParam);
#endif #endif
} // namespace operators } // namespace operators
......
src/operators/kernel/arm/activation_kernel.cpp
浏览文件 @ 9949681a
...@@ -105,7 +105,7 @@ void SigmoidKernel<CPU, float>::Compute(const SigmoidParam<CPU> &param) { ...@@ -105,7 +105,7 @@ void SigmoidKernel<CPU, float>::Compute(const SigmoidParam<CPU> &param) {
#ifdef TANH_OP #ifdef TANH_OP
template <> template <>
void TanhKernel<CPU, float>::Init(TanhParam<CPU> *param) { bool TanhKernel<CPU, float>::Init(TanhParam<CPU> *param) {
return true; return true;
} }
...@@ -117,5 +117,19 @@ void TanhKernel<CPU, float>::Compute(const TanhParam<CPU> &param) { ...@@ -117,5 +117,19 @@ void TanhKernel<CPU, float>::Compute(const TanhParam<CPU> &param) {
} }
#endif #endif
#ifdef LOG_OP
template <>
bool LogKernel<CPU, float>::Init(ReluParam<CPU> *param) {
return true;
}
template <>
void LogKernel<CPU, float>::Compute(const ReluParam<CPU> &param) {
const Tensor *input = param.InputX();
Tensor *output = param.Out();
ActivationCompute<float, LOG>()(input, output);
}
#endif
} // namespace operators } // namespace operators
} // namespace paddle_mobile } // namespace paddle_mobile
src/operators/sigmoid_op.h → src/operators/kernel/arm/lod_reset_kernel.cpp
浏览文件 @ 9949681a
...@@ -12,34 +12,51 @@ WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. ...@@ -12,34 +12,51 @@ WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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. */
#ifdef SIGMOID_OP #ifdef LOD_RESET_OP
#pragma once #include "operators/kernel/kernels.h"
#include <string>
#include "framework/operator.h"
#include "operators/kernel/activation_kernel.h"
#include "operators/op_param.h"
namespace paddle_mobile { namespace paddle_mobile {
namespace operators { namespace operators {
template <typename DeviceType, typename T> template <>
class SigmoidOp : public framework::OperatorWithKernel< bool LodResetKernel<CPU, float>::Init(LodResetParam<CPU> *param) {
DeviceType, SigmoidParam<DeviceType>, return true;
operators::SigmoidKernel<DeviceType, T>> { }
public:
SigmoidOp(const std::string &type, const VariableNameMap &inputs, template <>
const VariableNameMap &outputs, void LodResetKernel<CPU, float>::Compute(const LodResetParam<CPU> &param) {
const framework::AttributeMap &attrs, const auto *input = param.input_x_;
std::shared_ptr<framework::Scope> scope) const auto *lod_t = param.input_y_;
: framework::OperatorWithKernel<DeviceType, SigmoidParam<DeviceType>, auto *output = param.output_;
operators::SigmoidKernel<DeviceType, T>>(
type, inputs, outputs, attrs, scope) {} output->ShareDataWith(*input);
void InferShape() const override;
}; std::vector<int> level0;
if (lod_t) {
if (lod_t->lod().size() > 0) {
output->set_lod(lod_t->lod());
return; // early return, since lod already set
} else {
auto *lod = lod_t->data<int>();
level0 = std::vector<int>(lod, lod + lod_t->numel());
}
} else {
level0 = param.target_lod_;
}
// cast level0 to size_t
std::vector<size_t> ulevel0(level0.size(), 0);
for (int i = 0; i < level0.size(); ++i) {
ulevel0[i] = level0[i];
}
framework::LoD target_lod;
target_lod.push_back(std::move(ulevel0));
output->set_lod(target_lod);
}
} // namespace operators } // namespace operators
} // namespace paddle_mobile } // namespace paddle_mobile
#endif #endif // LOD_RESET_OP
src/operators/kernel/kernels.h
浏览文件 @ 9949681a
...@@ -22,7 +22,7 @@ namespace operators { ...@@ -22,7 +22,7 @@ namespace operators {
#define DECLARE_KERNEL(KernelClass, KernelParam) \ #define DECLARE_KERNEL(KernelClass, KernelParam) \
template <typename DeviceType, typename T> \ template <typename DeviceType, typename T> \
class KernelClass \ class KernelClass##Kernel \
: public framework::OpKernelBase<DeviceType, KernelParam<DeviceType>> { \ : public framework::OpKernelBase<DeviceType, KernelParam<DeviceType>> { \
public: \ public: \
bool Init(KernelParam<DeviceType> *param); \ bool Init(KernelParam<DeviceType> *param); \
...@@ -30,12 +30,16 @@ namespace operators { ...@@ -30,12 +30,16 @@ namespace operators {
}; };
#ifdef TOP_K_OP #ifdef TOP_K_OP
DECLARE_KERNEL(TopKKernel, TopKParam) DECLARE_KERNEL(TopK, TopKParam)
#endif // TOP_K_OP #endif // TOP_K_OP
#ifdef CAST_OP #ifdef CAST_OP
DECLARE_KERNEL(CastKernel, CastParam) DECLARE_KERNEL(Cast, CastParam)
#endif // CAST_OP #endif // CAST_OP
#ifdef LOD_RESET_OP
DECLARE_KERNEL(LodReset, LodResetParam)
#endif // LOD_RESET_OP
} // namespace operators } // namespace operators
} // namespace paddle_mobile } // namespace paddle_mobile
src/operators/sigmoid_op.cpp → src/operators/lod_reset_op.cpp
浏览文件 @ 9949681a
...@@ -12,16 +12,17 @@ WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. ...@@ -12,16 +12,17 @@ WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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. */
#ifdef SIGMOID_OP #ifdef LOD_RESET_OP
#include "operators/sigmoid_op.h" #include "operators/lod_reset_op.h"
namespace paddle_mobile { namespace paddle_mobile {
namespace operators { namespace operators {
template <typename DeviceType, typename T> template <typename Dtype, typename T>
void SigmoidOp<DeviceType, T>::InferShape() const { void LodResetOp<Dtype, T>::InferShape() const {
this->param_.Out()->Resize(this->param_.InputX()->dims()); const auto &input_dims = this->param_.input_->dims();
this->param_.output_->Resize(input_dims);
} }
} // namespace operators } // namespace operators
...@@ -29,7 +30,7 @@ void SigmoidOp<DeviceType, T>::InferShape() const { ...@@ -29,7 +30,7 @@ void SigmoidOp<DeviceType, T>::InferShape() const {
namespace ops = paddle_mobile::operators; namespace ops = paddle_mobile::operators;
#ifdef PADDLE_MOBILE_CPU #ifdef PADDLE_MOBILE_CPU
REGISTER_OPERATOR_CPU(sigmoid, ops::SigmoidOp); REGISTER_OPERATOR_CPU(lod_reset, ops::LodResetOp);
#endif #endif
#endif #endif // LOD_RESET_OP
src/operators/tanh_op.cpp → src/operators/lod_reset_op.h
浏览文件 @ 9949681a
...@@ -12,27 +12,21 @@ WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. ...@@ -12,27 +12,21 @@ WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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. */
#ifdef TANH_OP #ifdef LOD_RESET_OP
#include "operators/tanh_op.h" #pragma once
#include <string>
#include "framework/operator.h"
#include "operators/kernel/kernels.h"
#include "operators/op_param.h"
namespace paddle_mobile { namespace paddle_mobile {
namespace operators { namespace operators {
template <typename DeviceType, typename T> DECLARE_OPERATOR(LodReset, LodResetParam, LodResetKernel);
void TanhOp<DeviceType, T>::InferShape() const {
this->param_.Out()->Resize(this->param_.InputX()->dims());
}
} // namespace operators } // namespace operators
} // namespace paddle_mobile } // namespace paddle_mobile
namespace ops = paddle_mobile::operators; #endif // LOD_RESET_OP
#ifdef PADDLE_MOBILE_CPU
REGISTER_OPERATOR_CPU(tanh, ops::TanhOp);
#endif
#ifdef PADDLE_MOBILE_FPGA
REGISTER_OPERATOR_FPGA(tanh, ops::TanhOp);
#endif
#endif
src/operators/math/activation.h
浏览文件 @ 9949681a
...@@ -86,6 +86,11 @@ inline float32x4_t vActiveq_f32<TANH>(const float32x4_t &x) { ...@@ -86,6 +86,11 @@ inline float32x4_t vActiveq_f32<TANH>(const float32x4_t &x) {
__out = vmulq_n_f32(__out, 2.f); __out = vmulq_n_f32(__out, 2.f);
return vsubq_f32(__out, __one); return vsubq_f32(__out, __one);
} }
template <>
inline float32x4_t vActiveq_f32<LOG>(const float32x4_t &x) {
return log_ps(x);
}
#endif #endif
template <ActivationType Act = IDENTITY> template <ActivationType Act = IDENTITY>
...@@ -119,6 +124,11 @@ inline float Active<TANH>(const float &x) { ...@@ -119,6 +124,11 @@ inline float Active<TANH>(const float &x) {
return 2.f / (1.f + exp(-2.f * x)) - 1.f; return 2.f / (1.f + exp(-2.f * x)) - 1.f;
} }
template <>
inline float Active<LOG>(const float &x) {
return log(x);
}
} // namespace math } // namespace math
} // namespace operators } // namespace operators
} // namespace paddle_mobile } // namespace paddle_mobile
src/operators/op_param.h
浏览文件 @ 9949681a
...@@ -2829,5 +2829,32 @@ class SequencePoolParam : public OpParam { ...@@ -2829,5 +2829,32 @@ class SequencePoolParam : public OpParam {
}; };
#endif // SEQUENCE_EXPAND_OP #endif // SEQUENCE_EXPAND_OP
#ifdef LOD_RESET_OP
template <typename Dtype>
class LodResetParam : public OpParam {
typedef typename DtypeTensorTrait<Dtype>::gtype GType;
typedef typename DtypeTensorTrait<Dtype>::rtype RType;
public:
LodResetParam(const VariableNameMap &inputs, const VariableNameMap &outputs,
const AttributeMap &attrs, const Scope &scope) {
input_x_ = InputXFrom<GType>(inputs, scope);
output_ = OutFrom<GType>(outputs, scope);
input_y_ = nullptr;
if (inputs.count("Y")) {
input_y_ = InputYFrom<GType>(inputs, scope);
} else {
target_lod_ = OpParam::GetAttr<vector<int>>("target_lod", attrs);
}
}
public:
GType *input_x_;
GType *input_y_;
GType *output_;
std::vector<int> target_lod_;
};
#endif // LOD_RESET_OP
} // namespace operators } // namespace operators
} // namespace paddle_mobile } // namespace paddle_mobile
src/operators/relu_op.h 已删除 100644 → 0
浏览文件 @ 6e6d5dde
/* 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. */
#ifdef RELU_OP
#pragma once
#include <string>
#include "framework/operator.h"
#include "operators/kernel/activation_kernel.h"
#include "operators/op_param.h"
namespace paddle_mobile {
namespace operators {
template <typename DeviceType, typename T>
class ReluOp : public framework::OperatorWithKernel<
DeviceType, ReluParam<DeviceType>,
operators::ReluKernel<DeviceType, T>> {
public:
ReluOp(const std::string &type, const VariableNameMap &inputs,
const VariableNameMap &outputs, const framework::AttributeMap &attrs,
std::shared_ptr<framework::Scope> scope)
: framework::OperatorWithKernel<DeviceType, ReluParam<DeviceType>,
operators::ReluKernel<DeviceType, T>>(
type, inputs, outputs, attrs, scope) {}
void InferShape() const override;
};
template <typename DeviceType, typename T>
class Relu6Op : public framework::OperatorWithKernel<
DeviceType, ReluParam<DeviceType>,
operators::Relu6Kernel<DeviceType, T>> {
public:
Relu6Op(const std::string &type, const VariableNameMap &inputs,
const VariableNameMap &outputs, const framework::AttributeMap &attrs,
std::shared_ptr<framework::Scope> scope)
: framework::OperatorWithKernel<DeviceType, ReluParam<DeviceType>,
operators::Relu6Kernel<DeviceType, T>>(
type, inputs, outputs, attrs, scope) {}
void InferShape() const override;
};
} // namespace operators
} // namespace paddle_mobile
#endif
test/CMakeLists.txt
浏览文件 @ 9949681a
...@@ -238,6 +238,12 @@ if (NOT FOUND_MATCH) ...@@ -238,6 +238,12 @@ if (NOT FOUND_MATCH)
ADD_EXECUTABLE(test-relu6-op operators/test_relu6_op.cpp test_helper.h test_include.h) ADD_EXECUTABLE(test-relu6-op operators/test_relu6_op.cpp test_helper.h test_include.h)
target_link_libraries(test-relu6-op paddle-mobile) target_link_libraries(test-relu6-op paddle-mobile)
ADD_EXECUTABLE(test-tanh-op operators/test_tanh_op.cpp test_helper.h test_include.h)
target_link_libraries(test-tanh-op paddle-mobile)
ADD_EXECUTABLE(test-log-op operators/test_log_op.cpp test_helper.h test_include.h)
target_link_libraries(test-log-op paddle-mobile)
ADD_EXECUTABLE(test-topk-op operators/test_topk_op.cpp test_helper.h test_include.h) ADD_EXECUTABLE(test-topk-op operators/test_topk_op.cpp test_helper.h test_include.h)
target_link_libraries(test-topk-op paddle-mobile) target_link_libraries(test-topk-op paddle-mobile)
......
test/executor_for_test.h
浏览文件 @ 9949681a
...@@ -20,12 +20,11 @@ limitations under the License. */ ...@@ -20,12 +20,11 @@ limitations under the License. */
#include "common/log.h" #include "common/log.h"
#include "framework/executor.h" #include "framework/executor.h"
#include "framework/op_registry.h" #include "framework/op_registry.h"
#include "operators/activation_op.h"
#include "operators/conv_op.h" #include "operators/conv_op.h"
#include "operators/elementwise_add_op.h" #include "operators/elementwise_add_op.h"
#include "operators/pool_op.h" #include "operators/pool_op.h"
#include "operators/relu_op.h"
#include "operators/reshape_op.h" #include "operators/reshape_op.h"
#include "operators/sigmoid_op.h"
#include "operators/softmax_op.h" #include "operators/softmax_op.h"
#include "operators/transpose_op.h" #include "operators/transpose_op.h"
......
test/operators/test_log_op.cpp 0 → 100644
浏览文件 @ 9949681a
/* 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 <cmath>
#include <iostream>
#include "../test_include.h"
#include "operators/activation_op.h"
namespace paddle_mobile {
void Log(const framework::Tensor *X, framework::Tensor *Y) {
const float *x = X->data<float>();
float *y = Y->mutable_data<float>();
for (int i = 0; i < X->numel(); ++i) {
y[i] = log(x[i]);
}
}
int TestLogOp(const std::vector<int> input_shape) {
framework::DDim dims = framework::make_ddim(input_shape);
VariableNameMap inputs;
VariableNameMap outputs;
auto scope = std::make_shared<framework::Scope>();
inputs["X"] = std::vector<std::string>({"input"});
outputs["Out"] = std::vector<std::string>({"output"});
auto input_var = scope.get()->Var("input");
auto input = input_var->template GetMutable<framework::LoDTensor>();
SetupTensor<float>(input, dims, 0.0001, 100.0);
auto output_var = scope.get()->Var("output");
framework::AttributeMap attrs;
auto *op =
new operators::LogOp<CPU, float>("log", inputs, outputs, attrs, scope);
op->InferShape();
op->Init();
op->Run();
auto output = output_var->template Get<framework::LoDTensor>();
framework::Tensor output_cmp;
float *output_cmp_data = output_cmp.mutable_data<float>(output->dims());
Log(input, &output_cmp);
const float *output_data = output->data<float>();
for (int i = 0; i < output->numel(); ++i) {
float gap = output_data[i] - output_cmp_data[i];
if (std::abs(gap / (output_data[i] + 1e-5)) > 1e-3) {
LOG(kLOG_INFO) << "output_data[" << i << "] = " << output_data[i]
<< ", output_cmp_data[" << i
<< "] = " << output_cmp_data[i];
delete op;
exit(1);
}
}
delete op;
return 0;
}
} // namespace paddle_mobile
int main() {
paddle_mobile::TestLogOp({1, 1, 2, 3});
paddle_mobile::TestLogOp({1, 3, 11, 22});
paddle_mobile::TestLogOp({1, 32, 112, 112});
std::cout << "test log op pass." << std::endl;
return 0;
}
test/operators/test_relu6_op.cpp
浏览文件 @ 9949681a
...@@ -15,7 +15,7 @@ limitations under the License. */ ...@@ -15,7 +15,7 @@ limitations under the License. */
#include <cmath> #include <cmath>
#include <iostream> #include <iostream>
#include "../test_include.h" #include "../test_include.h"
#include "operators/relu_op.h" #include "operators/activation_op.h"
namespace paddle_mobile { namespace paddle_mobile {
......
test/operators/test_relu_op.cpp
浏览文件 @ 9949681a
...@@ -15,7 +15,7 @@ limitations under the License. */ ...@@ -15,7 +15,7 @@ limitations under the License. */
#include <cmath> #include <cmath>
#include <iostream> #include <iostream>
#include "../test_include.h" #include "../test_include.h"
#include "operators/relu_op.h" #include "operators/activation_op.h"
namespace paddle_mobile { namespace paddle_mobile {
......
test/operators/test_sigmoid_op.cpp
浏览文件 @ 9949681a
...@@ -12,15 +12,70 @@ WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. ...@@ -12,15 +12,70 @@ WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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. */
#include "../test_helper.h" #include <cmath>
#include <iostream>
#include "../test_include.h"
#include "operators/activation_op.h"
int main() { namespace paddle_mobile {
paddle_mobile::framework::Tensor input;
paddle_mobile::framework::Tensor output; void Sigmoid(const framework::Tensor *X, framework::Tensor *Y) {
SetupTensor<float>(&input, {1, 4, 60, 60}, static_cast<float>(0), const float *x = X->data<float>();
static_cast<float>(1)); float *y = Y->mutable_data<float>();
for (int i = 0; i < X->numel(); ++i) {
y[i] = 1.f / (1.f + exp(-x[i]));
}
}
int TestSigmoidOp(const std::vector<int> input_shape) {
framework::DDim dims = framework::make_ddim(input_shape);
VariableNameMap inputs;
VariableNameMap outputs;
auto scope = std::make_shared<framework::Scope>();
inputs["X"] = std::vector<std::string>({"input"});
outputs["Out"] = std::vector<std::string>({"output"});
auto input_var = scope.get()->Var("input");
auto input = input_var->template GetMutable<framework::LoDTensor>();
SetupTensor<float>(input, dims, -100.0, 100.0);
auto output_var = scope.get()->Var("output");
framework::AttributeMap attrs;
auto *op = new operators::SigmoidOp<CPU, float>("sigmoid", inputs, outputs,
attrs, scope);
op->InferShape();
op->Init();
op->Run();
auto out_ddim = paddle_mobile::framework::make_ddim({1, 4, 60, 60}); auto output = output_var->template Get<framework::LoDTensor>();
output.Resize(out_ddim);
framework::Tensor output_cmp;
float *output_cmp_data = output_cmp.mutable_data<float>(output->dims());
Sigmoid(input, &output_cmp);
const float *output_data = output->data<float>();
for (int i = 0; i < output->numel(); ++i) {
float gap = output_data[i] - output_cmp_data[i];
if (std::abs(gap / (output_data[i] + 1e-5)) > 1e-3) {
LOG(kLOG_INFO) << "output_data[" << i << "] = " << output_data[i]
<< ", output_cmp_data[" << i
<< "] = " << output_cmp_data[i];
delete op;
exit(1);
}
}
delete op;
return 0;
}
} // namespace paddle_mobile
int main() {
paddle_mobile::TestSigmoidOp({1, 1, 2, 3});
paddle_mobile::TestSigmoidOp({1, 3, 11, 22});
paddle_mobile::TestSigmoidOp({1, 32, 112, 112});
std::cout << "test sigmoid op pass." << std::endl;
return 0; return 0;
} }
test/operators/test_tanh_op.cpp 0 → 100644
浏览文件 @ 9949681a
/* 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 <cmath>
#include <iostream>
#include "../test_include.h"
#include "operators/activation_op.h"
namespace paddle_mobile {
void Tanh(const framework::Tensor *X, framework::Tensor *Y) {
const float *x = X->data<float>();
float *y = Y->mutable_data<float>();
for (int i = 0; i < X->numel(); ++i) {
y[i] = 2.f / (1.f + exp(-2.f * x[i])) - 1.f;
}
}
int TestTanhOp(const std::vector<int> input_shape) {
framework::DDim dims = framework::make_ddim(input_shape);
VariableNameMap inputs;
VariableNameMap outputs;
auto scope = std::make_shared<framework::Scope>();
inputs["X"] = std::vector<std::string>({"input"});
outputs["Out"] = std::vector<std::string>({"output"});
auto input_var = scope.get()->Var("input");
auto input = input_var->template GetMutable<framework::LoDTensor>();
SetupTensor<float>(input, dims, -100.0, 100.0);
auto output_var = scope.get()->Var("output");
framework::AttributeMap attrs;
auto *op =
new operators::TanhOp<CPU, float>("tanh", inputs, outputs, attrs, scope);
op->InferShape();
op->Init();
op->Run();
auto output = output_var->template Get<framework::LoDTensor>();
framework::Tensor output_cmp;
float *output_cmp_data = output_cmp.mutable_data<float>(output->dims());
Tanh(input, &output_cmp);
const float *output_data = output->data<float>();
for (int i = 0; i < output->numel(); ++i) {
float gap = output_data[i] - output_cmp_data[i];
if (std::abs(gap / (output_data[i] + 1e-5)) > 1e-3) {
LOG(kLOG_INFO) << "output_data[" << i << "] = " << output_data[i]
<< ", output_cmp_data[" << i
<< "] = " << output_cmp_data[i];
delete op;
exit(1);
}
}
delete op;
return 0;
}
} // namespace paddle_mobile
int main() {
paddle_mobile::TestTanhOp({1, 1, 2, 3});
paddle_mobile::TestTanhOp({1, 3, 11, 22});
paddle_mobile::TestTanhOp({1, 32, 112, 112});
std::cout << "test sigmoid op pass." << std::endl;
return 0;
}
tools/op.cmake
浏览文件 @ 9949681a
...@@ -276,6 +276,8 @@ if(NOT FOUND_MATCH) ...@@ -276,6 +276,8 @@ if(NOT FOUND_MATCH)
set(SEQUENCE_EXPAND_OP ON) set(SEQUENCE_EXPAND_OP ON)
set(SEQUENCE_POOL_OP ON) set(SEQUENCE_POOL_OP ON)
set(SEQUENCE_SOFTMAX_OP ON) set(SEQUENCE_SOFTMAX_OP ON)
set(LOG_OP ON)
set(TANH_OP ON)
endif() endif()
# option(BATCHNORM_OP "" ON) # option(BATCHNORM_OP "" ON)
...@@ -512,6 +514,9 @@ endif() ...@@ -512,6 +514,9 @@ endif()
if (SEQUENCE_SOFTMAX_OP) if (SEQUENCE_SOFTMAX_OP)
add_definitions(-DSEQUENCE_SOFTMAX_OP) add_definitions(-DSEQUENCE_SOFTMAX_OP)
endif() endif()
if (LOG_OP)
add_definitions(-DLOG_OP)
endif()
if (TANH_OP) if (TANH_OP)
add_definitions(-DTANH_OP) add_definitions(-DTANH_OP)
......
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