提交 c5b5e346 编写于 作者: qnqinan's avatar qnqinan 提交者: GitHub

Merge branch 'develop' into develop

...@@ -37,6 +37,7 @@ const char *G_OP_TYPE_FUSION_CONV_ADD = "fusion_conv_add"; ...@@ -37,6 +37,7 @@ const char *G_OP_TYPE_FUSION_CONV_ADD = "fusion_conv_add";
const char *G_OP_TYPE_LRN = "lrn"; const char *G_OP_TYPE_LRN = "lrn";
const char *G_OP_TYPE_MUL = "mul"; const char *G_OP_TYPE_MUL = "mul";
const char *G_OP_TYPE_MULTICLASS_NMS = "multiclass_nms"; const char *G_OP_TYPE_MULTICLASS_NMS = "multiclass_nms";
const char *G_OP_TYPE_NORM = "norm";
const char *G_OP_TYPE_POLYGON_BOX_TRANSFORM = "polygon_box_transform"; const char *G_OP_TYPE_POLYGON_BOX_TRANSFORM = "polygon_box_transform";
const char *G_OP_TYPE_POOL2D = "pool2d"; const char *G_OP_TYPE_POOL2D = "pool2d";
const char *G_OP_TYPE_PRIOR_BOX = "prior_box"; const char *G_OP_TYPE_PRIOR_BOX = "prior_box";
...@@ -169,5 +170,6 @@ std::unordered_map< ...@@ -169,5 +170,6 @@ std::unordered_map<
{G_OP_TYPE_FUSION_DECONV_ADD_RELU, {{"Input"}, {"Out"}}}, {G_OP_TYPE_FUSION_DECONV_ADD_RELU, {{"Input"}, {"Out"}}},
{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"}}}};
} // namespace paddle_mobile } // namespace paddle_mobile
/* 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 NORM_OP
#include "operators/kernel/norm_kernel.h"
#include "operators/kernel/central-arm-func/norm_arm_func.h"
namespace paddle_mobile {
namespace operators {
template <>
bool NormKernel<CPU, float>::Init(NormParam<CPU> *param) {
return true;
}
template <>
void NormKernel<CPU, float>::Compute(const NormParam<CPU> &param) {
NormCompute<float>(param);
}
} // namespace operators
} // namespace paddle_mobile
#endif
/* 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 NORM_OP
#pragma once
#include <cmath>
#include "operators/op_param.h"
namespace paddle_mobile {
namespace operators {
inline void GetDims(const framework::DDim &dim, int axis, int *pre, int *n,
int *post) {
*pre = 1;
*post = 1;
*n = dim[axis];
for (int i = 0; i < axis; ++i) {
(*pre) *= dim[i];
}
for (int i = axis + 1; i < dim.size(); ++i) {
(*post) *= dim[i];
}
}
template <typename P>
void NormCompute(const NormParam<CPU> &param) {
const float epsilon = param.Epsilon();
int axis = param.Axis();
const framework::Tensor *input = param.InputX();
framework::Tensor square;
framework::Tensor *norm = param.OutputNorm();
framework::Tensor *out = param.Out();
auto x_dims = input->dims();
if (axis < 0) {
axis += x_dims.size();
}
int pre, n, post;
GetDims(x_dims, axis, &pre, &n, &post);
square.Resize(input->dims());
const float *input_ptr = input->data<float>();
float *square_ptr = square.mutable_data<float>();
float *norm_ptr = norm->mutable_data<float>();
float *out_ptr = out->mutable_data<float>();
const float *in_tmp = input_ptr;
float *square_tmp = square_ptr;
for (int i = 0; i < input->numel(); ++i) {
float element = *in_tmp;
*square_tmp = element * element;
square_tmp++;
in_tmp++;
}
// const float *norm_tmp = norm_ptr;
// for (int i = 0; i < norm->numel(); ++i) {
// *norm_tmp = 0;
// norm_tmp++;
// }
square_tmp = square_ptr;
float *norm_tmp = norm_ptr;
for (int i = 0; i < pre; ++i) {
for (int j = 0; j < post; ++j) {
for (int k = 0; k < n; ++k) {
if (k == 0) {
*norm_tmp = *square_tmp;
} else {
*norm_tmp += *(square_tmp + k * post);
}
}
float sum = *norm_tmp + epsilon;
*norm_tmp = sqrtf(sum);
norm_tmp++;
square_tmp++;
}
}
in_tmp = input_ptr;
norm_tmp = norm_ptr;
float *out_tmp = out_ptr;
for (int i = 0; i < pre; ++i) {
for (int k = 0; k < n; ++k) {
for (int j = 0; j < post; ++j) {
*out_tmp = *in_tmp / *norm_tmp;
in_tmp++;
norm_tmp++;
out_tmp++;
}
norm_tmp = norm_ptr + i * post;
}
}
}
} // namespace operators
} // namespace paddle_mobile
#endif
/* 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 NORM_OP
#pragma once
#include "framework/operator.h"
#include "operators/op_param.h"
namespace paddle_mobile {
namespace operators {
template <typename DeviceType, typename T>
class NormKernel
: public framework::OpKernelBase<DeviceType, NormParam<DeviceType>> {
public:
void Compute(const NormParam<DeviceType> &param);
bool Init(NormParam<DeviceType> *param);
};
} // namespace operators
} // namespace paddle_mobile
#endif
/* 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 NORM_OP
#include "operators/norm_op.h"
#include "framework/op_proto_maker.h"
#include "framework/op_registry.h"
namespace paddle_mobile {
namespace operators {
template <typename Dtype, typename T>
void NormOp<Dtype, T>::InferShape() const {
auto x_dims = this->param_.InputX()->dims();
this->param_.Out()->Resize(x_dims);
int axis = this->param_.Axis();
if (axis < 0) {
axis += x_dims.size();
}
x_dims[axis] = 1;
this->param_.OutputNorm()->Resize(x_dims);
}
} // namespace operators
} // namespace paddle_mobile
namespace ops = paddle_mobile::operators;
#ifdef PADDLE_MOBILE_CPU
REGISTER_OPERATOR_CPU(norm, ops::NormOp);
#endif
#ifdef PADDLE_MOBILE_MALI_GPU
#endif
#ifdef PADDLE_MOBILE_FPGA
#endif
#ifdef PADDLE_MOBILE_CL
#endif
#endif
/* 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 NORM_OP
#pragma once
#include <string>
#include "framework/operator.h"
#include "operators/kernel/norm_kernel.h"
#include "operators/op_param.h"
namespace paddle_mobile {
namespace operators {
using std::string;
template <typename DeviceType, typename T>
class NormOp
: public framework::OperatorWithKernel<DeviceType, NormParam<DeviceType>,
NormKernel<DeviceType, T>> {
public:
NormOp(const string &type, const VariableNameMap &inputs,
const VariableNameMap &outputs, const framework::AttributeMap &attrs,
std::shared_ptr<framework::Scope> scope)
: framework::OperatorWithKernel<DeviceType, NormParam<DeviceType>,
NormKernel<DeviceType, T>>(
type, inputs, outputs, attrs, scope) {}
void InferShape() const override;
protected:
};
} // namespace operators
} // namespace paddle_mobile
#endif
...@@ -280,6 +280,11 @@ class OpParam { ...@@ -280,6 +280,11 @@ class OpParam {
return GetVarValue<T>("OutputBox", outputs, scope); return GetVarValue<T>("OutputBox", outputs, scope);
} }
template <typename T>
static T *OutputNormFrom(const VariableNameMap &outputs, const Scope &scope) {
return GetVarValue<T>("Norm", outputs, scope);
}
template <typename T> template <typename T>
static T *OutputVariancesFrom(const VariableNameMap &outputs, static T *OutputVariancesFrom(const VariableNameMap &outputs,
const Scope &scope) { const Scope &scope) {
...@@ -733,6 +738,41 @@ class LrnParam : public OpParam { ...@@ -733,6 +738,41 @@ class LrnParam : public OpParam {
}; };
#endif #endif
#ifdef NORM_OP
template <typename Dtype>
class NormParam : OpParam {
typedef typename DtypeTensorTrait<Dtype>::gtype GType;
typedef typename DtypeTensorTrait<Dtype>::rtype RType;
public:
NormParam(const VariableNameMap &inputs, const VariableNameMap &outputs,
const AttributeMap &attrs, const Scope &scope) {
input_x_ = InputXFrom<GType>(inputs, scope);
out_ = OutFrom<GType>(outputs, scope);
output_norm_ = OutputNormFrom<GType>(outputs, scope);
epsilon_ = GetAttr<float>("epsilon", attrs);
axis_ = GetAttr<int>("axis", attrs);
}
const RType *InputX() const { return input_x_; }
RType *Out() const { return out_; }
RType *OutputNorm() const { return output_norm_; }
const float &Epsilon() const { return epsilon_; }
const int &Axis() const { return axis_; }
private:
RType *input_x_;
RType *out_;
RType *output_norm_;
float epsilon_;
int axis_;
};
#endif
#ifdef BATCHNORM_OP #ifdef BATCHNORM_OP
template <typename Dtype> template <typename Dtype>
class BatchNormParam : OpParam { class BatchNormParam : OpParam {
......
...@@ -394,4 +394,9 @@ if (NOT FOUND_MATCH) ...@@ -394,4 +394,9 @@ if (NOT FOUND_MATCH)
ADD_EXECUTABLE(test-sequence-softmax operators/test_sequence_softmax_op.cpp test_helper.h test_include.h) ADD_EXECUTABLE(test-sequence-softmax operators/test_sequence_softmax_op.cpp test_helper.h test_include.h)
target_link_libraries(test-sequence-softmax paddle-mobile) target_link_libraries(test-sequence-softmax paddle-mobile)
# gen test
ADD_EXECUTABLE(test-vgg16ssd net/test_vgg16ssd.cpp test_helper.h test_include.h)
target_link_libraries(test-vgg16ssd paddle-mobile)
endif () endif ()
/* 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 <iostream>
#include "../test_helper.h"
#include "../test_include.h"
int main() {
paddle_mobile::PaddleMobile<paddle_mobile::CPU> paddle_mobile;
paddle_mobile.SetThreadNum(1);
auto time1 = paddle_mobile::time();
auto isok =
paddle_mobile.Load(std::string(g_vgg16_ssd_combined) + "/model",
std::string(g_vgg16_ssd_combined) + "/params", false);
if (isok) {
auto time2 = paddle_mobile::time();
std::cout << "load cost :" << paddle_mobile::time_diff(time1, time1) << "ms"
<< std::endl;
std::vector<int64_t> dims{1, 3, 300, 300};
Tensor input_tensor;
SetupTensor<float>(&input_tensor, {1, 3, 300, 300}, static_cast<float>(0),
static_cast<float>(1));
std::vector<float> input(input_tensor.data<float>(),
input_tensor.data<float>() + input_tensor.numel());
auto vec_result = paddle_mobile.Predict(input, dims);
DLOG << vec_result;
}
return 0;
}
...@@ -50,6 +50,7 @@ static const char *g_yolo = "../models/yolo"; ...@@ -50,6 +50,7 @@ static const char *g_yolo = "../models/yolo";
static const char *g_yolo_combined = "../models/yolo_combined"; static const char *g_yolo_combined = "../models/yolo_combined";
static const char *g_yolo_mul = "../models/d"; static const char *g_yolo_mul = "../models/d";
static const char *g_fluid_fssd_new = "../models/fluid_fssd_new"; static const char *g_fluid_fssd_new = "../models/fluid_fssd_new";
static const char *g_vgg16_ssd_combined = "../models/vgg16_ssd_combined";
static const char *g_test_image_1x3x224x224 = static const char *g_test_image_1x3x224x224 =
"../images/test_image_1x3x224x224_float"; "../images/test_image_1x3x224x224_float";
static const char *g_test_image_1x3x224x224_banana = static const char *g_test_image_1x3x224x224_banana =
......
...@@ -146,6 +146,7 @@ if (NOT DEFINED CMAKE_IOS_DEVELOPER_ROOT) ...@@ -146,6 +146,7 @@ if (NOT DEFINED CMAKE_IOS_DEVELOPER_ROOT)
endif (NOT DEFINED CMAKE_IOS_DEVELOPER_ROOT) endif (NOT DEFINED CMAKE_IOS_DEVELOPER_ROOT)
set (CMAKE_IOS_DEVELOPER_ROOT ${CMAKE_IOS_DEVELOPER_ROOT} CACHE PATH "Location of iOS Platform") set (CMAKE_IOS_DEVELOPER_ROOT ${CMAKE_IOS_DEVELOPER_ROOT} CACHE PATH "Location of iOS Platform")
set(CMAKE_IOS_SDK_ROOT "/Applications/Xcode.app/Contents/Developer/Platforms/iPhoneOS.platform/Developer/SDKs/iPhoneOS.sdk")
# Find and use the most recent iOS sdk unless specified manually with CMAKE_IOS_SDK_ROOT # Find and use the most recent iOS sdk unless specified manually with CMAKE_IOS_SDK_ROOT
if (NOT DEFINED CMAKE_IOS_SDK_ROOT) if (NOT DEFINED CMAKE_IOS_SDK_ROOT)
file (GLOB _CMAKE_IOS_SDKS "${CMAKE_IOS_DEVELOPER_ROOT}/SDKs/*") file (GLOB _CMAKE_IOS_SDKS "${CMAKE_IOS_DEVELOPER_ROOT}/SDKs/*")
......
...@@ -215,6 +215,7 @@ endif() ...@@ -215,6 +215,7 @@ endif()
if(NOT FOUND_MATCH) if(NOT FOUND_MATCH)
message("--default--") message("--default--")
set(NORM_OP ON)
set(BATCHNORM_OP ON) set(BATCHNORM_OP ON)
set(CONV_TRANSPOSE_OP ON) set(CONV_TRANSPOSE_OP ON)
set(BOXCODER_OP ON) set(BOXCODER_OP ON)
...@@ -302,6 +303,9 @@ endif() ...@@ -302,6 +303,9 @@ endif()
# option(TRANSPOSE2_OP "" ON) # option(TRANSPOSE2_OP "" ON)
# endif () # endif ()
if (NORM_OP)
add_definitions(-DNORM_OP)
endif()
if (BATCHNORM_OP) if (BATCHNORM_OP)
add_definitions(-DBATCHNORM_OP) add_definitions(-DBATCHNORM_OP)
endif() endif()
......
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