fix dash and space bug,

ISSUE=4586495

git-svn-id: https://svn.baidu.com/idl/trunk/paddle@1408 1ad973e4-5ce8-4261-8a94-b56d1f490c56
avx_docs
zhangjinchao01 9 years ago
commit b72beee4f0

@ -0,0 +1,29 @@
# This file is used by clang-format to autoformat paddle source code
#
# The clang-format is part of llvm toolchain.
# It need to install llvm and clang to format source code style.
#
# The basic usage is,
# clang-format -i -style=file PATH/TO/SOURCE/CODE
#
# The -style=file implicit use ".clang-format" file located in one of
# parent directory.
# The -i means inplace change.
#
# The document of clang-format is
# http://clang.llvm.org/docs/ClangFormat.html
# http://clang.llvm.org/docs/ClangFormatStyleOptions.html
#
# TODO(yuyang18): Add python and other language code style
---
Language: Cpp
BasedOnStyle: Google
IndentWidth: 2
TabWidth: 2
ContinuationIndentWidth: 4
AccessModifierOffset: -2 # The private/protected/public has no indent in class
PointerAlignment: Left # int* p/int& p, not int *p/int &p
Standard: Cpp11
AllowAllParametersOfDeclarationOnNextLine: true
...

2
.gitignore vendored

@ -0,0 +1,2 @@
*.DS_Store
build/

@ -0,0 +1,156 @@
cmake_minimum_required(VERSION 2.8)
project(paddle CXX C)
set(PADDLE_MAJOR_VERSION 0)
set(PADDLE_MINOR_VERSION 8)
set(PADDLE_PATCH_VERSION 0b)
set(PADDLE_VERSION ${PADDLE_MAJOR_VERSION}.${PADDLE_MINOR_VERSION}.${PADDLE_PATCH_VERSION})
set(CMAKE_MODULE_PATH ${CMAKE_MODULE_PATH} "${CMAKE_SOURCE_DIR}/cmake")
set(PROJ_ROOT ${CMAKE_SOURCE_DIR})
include(package)
include(swig)
find_package(CUDA QUIET)
find_package(Protobuf REQUIRED)
find_package(PythonLibs 2.7 REQUIRED)
find_package(PythonInterp 2.7 REQUIRED)
find_package(NumPy)
find_package(Threads REQUIRED)
find_package(Glog)
find_package(Gflags QUIET)
find_package(GTest)
find_package(Sphinx)
find_package(Doxygen)
include(cblas)
find_program(M4_EXECUTABLE m4)
###################### Configurations ###########################
option(WITH_DSO "Compile PaddlePaddle with dynamic linked libraries" ON)
option(WITH_GPU "Compile PaddlePaddle with gpu" ${CUDA_FOUND})
option(WITH_DOUBLE "Compile PaddlePaddle with double precision, otherwise use single precision" OFF)
option(WITH_AVX "Compile PaddlePaddle with avx instructs" ON) # TODO(yuyang18): Check AVX is supported or not as default value
option(WITH_PYTHON "Compile PaddlePaddle with python interpretor" ON)
option(WITH_STYLE_CHECK "Style Check for PaddlePaddle" ${PYTHONINTERP_FOUND})
option(WITH_RDMA "Compile PaddlePaddle with rdma support" OFF)
option(WITH_GLOG "Compile PaddlePaddle use glog, otherwise use a log implement internally" ${LIBGLOG_FOUND})
option(WITH_GFLAGS "Compile PaddlePaddle use gflags, otherwise use a flag implement internally" ${GFLAGS_FOUND})
option(WITH_TIMER "Compile PaddlePaddle use timer" OFF)
option(WITH_TESTING "Compile and run unittest for PaddlePaddle" ${GTEST_FOUND})
option(WITH_DOC "Compile PaddlePaddle with documentation" OFF)
option(WITH_DOC_CN "Compile PaddlePaddle with Chinese documentation" OFF)
option(WITH_SWIG_PY "Compile PaddlePaddle with py PaddlePaddle predict api" ${SWIG_FOUND})
if(NOT CMAKE_BUILD_TYPE)
set(CMAKE_BUILD_TYPE "RelWithDebInfo" CACHE STRING
"Choose the type of build, options are: Debug Release RelWithDebInfo MinSizeRel"
FORCE)
endif()
include(enableCXX11)
include(cpplint)
include(ccache)
include(util)
include(flags)
include(cudnn)
include(FindPythonModule)
include(check_packages)
# add PaddlePaddle version
if(DEFINED ENV{PADDLE_VERSION})
add_definitions(-DPADDLE_VERSION=\"$ENV{PADDLE_VERSION}\")
else()
if(EXISTS ${PROJ_ROOT}/.svn/)
find_package(Subversion REQUIRED)
if(SUBVERSION_FOUND)
Subversion_WC_INFO(${PROJ_ROOT} Project)
add_definitions(-DPADDLE_VERSION=${Project_WC_REVISION})
endif()
endif()
endif()
if(NOT WITH_GPU)
add_definitions(-DPADDLE_ONLY_CPU)
add_definitions(-DHPPL_STUB_FUNC)
list(APPEND CMAKE_CXX_SOURCE_FILE_EXTENSIONS cu)
else()
# TODO(yuyang18): Change it to remove std=c++11 in cuda compile.
set(CUDA_PROPAGATE_HOST_FLAGS OFF)
if(NOT CUDNN_FOUND)
message(FATAL_ERROR "Paddle need cudnn to compile")
endif()
if(WITH_DSO)
set(CUDA_LIBRARIES "")
add_definitions(-DPADDLE_USE_DSO)
endif(WITH_DSO)
# Include cuda and cudnn
include_directories(${CUDNN_INCLUDE_DIR})
include_directories(${CUDA_TOOLKIT_INCLUDE})
endif(NOT WITH_GPU)
if(WITH_DOUBLE)
add_definitions(-DPADDLE_TYPE_DOUBLE -DHPPL_TYPE_DOUBLE)
set(ACCURACY double)
else(WITH_DOUBLE)
set(ACCURACY float)
endif(WITH_DOUBLE)
if(NOT WITH_TIMER)
add_definitions(-DPADDLE_DISABLE_TIMER)
endif(NOT WITH_TIMER)
if(WITH_AVX)
set(CMAKE_C_FLAGS "${CMAKE_C_FLAGS} -mavx")
set(CMAKE_CXX_FLAGS "${CMAKE_CXX_FLAGS} -mavx")
else(WITH_AVX)
set(CMAKE_C_FLAGS "${CMAKE_C_FLAGS} -msse3")
set(CMAKE_CXX_FLAGS "${CMAKE_CXX_FLAGS} -msse3")
endif(WITH_AVX)
if(WITH_PYTHON)
include_directories(${PYTHON_INCLUDE_DIR})
include_directories(${PYTHON_NUMPY_INCLUDE_DIR})
else(WITH_PYTHON)
add_definitions(-DPADDLE_NO_PYTHON)
endif(WITH_PYTHON)
if(NOT WITH_RDMA)
add_definitions(-DPADDLE_DISABLE_RDMA)
endif()
if(WITH_GLOG)
add_definitions(-DPADDLE_USE_GLOG)
endif()
if(WITH_GFLAGS)
add_definitions(-DPADDLE_USE_GFLAGS)
add_definitions(-DGFLAGS_NS=${GFLAGS_NAMESPACE})
include_directories(${GFLAGS_INCLUDE_DIRS})
endif()
if(WITH_TESTING)
enable_testing()
include_directories(${GTEST_INCLUDE_DIRS})
endif()
include_directories("${CBLAS_INC_DIR}")
include_directories("${PROJ_ROOT}")
include_directories("${PROJ_ROOT}/paddle/cuda/include")
include_directories(${PROTOBUF_INCLUDE_DIRS})
include_directories("${CMAKE_CURRENT_BINARY_DIR}/proto")
if(EXISTS "${PROJ_ROOT}/paddle/internals/CMakeLists.txt")
set(PADDLE_WITH_INTERNAL ON)
include(paddle/internals/CMakeLists.txt)
else()
set(PADDLE_WITH_INTERNAL OFF)
set(INTERNAL_PROTO_PATH "")
endif()
add_subdirectory(proto)
add_subdirectory(paddle)
add_subdirectory(python)
if(WITH_DOC)
add_subdirectory(doc)
endif()
if(WITH_DOC_CN)
add_subdirectory(doc_cn)
endif()

@ -0,0 +1,203 @@
Copyright (c) 2016 Baidu, Inc. All Rights Reserved
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END OF TERMS AND CONDITIONS
APPENDIX: How to apply the Apache License to your work.
To apply the Apache License to your work, attach the following
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Unless required by applicable law or agreed to in writing, software
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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.

@ -0,0 +1,84 @@
# PaddlePaddle
[![Documentation Status](https://readthedocs.org/projects/ctcspeechrecognition/badge/?version=latest)](http://ctcspeechrecognition.readthedocs.io/en/latest/?badge=latest)
PaddlePaddle (PArallel Distributed Deep LEarning) is an easy-to-use,
efficient, flexible and scalable deep learning platform, which is originally
developed by Baidu scientists and engineers for the purpose of applying deep
learning to many products at Baidu.
## Features
- **Flexibility**
PaddlePaddle supports a wide range of neural network architectures and
optimization algorithms. It is easy to configure complex models such as
neural machine translation model with attention mechanism or complex memory
connection.
- **Efficiency**
In order to unleash the power of heterogeneous computing resource,
optimization occurs at different levels of PaddlePaddle, including
computing, memory, architecture and communication. The following are some
examples:
1. Optimized math operations through SSE/AVX intrinsics, BLAS libraries
(e.g. MKL, ATLAS, cuBLAS) or customized CPU/GPU kernels.
2. Highly optimized recurrent networks which can handle **variable-length**
sequence without padding.
3. Optimized local and distributed training for models with high dimensional
sparse data.
- **Scalability**
With PaddlePaddle, it is easy to use many CPUs/GPUs and machines to speed
up your training. PaddlePaddle can achieve high throughput and performance
via optimized communication.
- **Connected to Products**
In addition, PaddlePaddle is also designed to be easily deployable. At Baidu,
PaddlePaddle has been deployed into products or service with a vast number
of users, including ad click-through rate (CTR) prediction, large-scale image
classification, optical character recognition(OCR), search ranking, computer
virus detection, recommendation, etc. It is widely utilized in products at
Baidu and it has achieved a significant impact. We hope you can also exploit
the capability of PaddlePaddle to make a huge impact for your product.
## Installation
See [installation guide]() to build and install from the source code or install
the Docker Image.
## Documentation
- [Quick Start]() <br>
You can follow the quick start tutorial to learn how use PaddlePaddle
step-by-step.
- [Example and Demo]() <br>
We provide five demos, including: image classification, sentiment analysis,
sequence to sequence model, recommendation, semantic role labelling.
- [Distributed Training]() <br>
This system supports training deep learning models on multiple machines
with data parallelism.
- [Python API]() <br>
PaddlePaddle supports using either Python interface or C++ to build your
system. We also use SWIG to wrap C++ source code to create a user friendly
interface for Python. You can also use SWIG to create interface for your
favorite programming language.
- [How to Contribute]() <br>
We sincerely appreciate your interest and contributions. If youd like to
contribute, please read the contribution guide.
- [Source Code Documents]() <br>
## Ask Questions
If you want to ask questions and discuss about methods and models, welcome
to send email to paddle-dev@baidu.com. Framework development discussions and
bug reports are collected on [Issues](https://github.com/paddle/paddle/issues).
## Copyright and License
PaddlePaddle is provided under the [Apache-2.0 license](LICENSE).

@ -0,0 +1,53 @@
Cao, Ying
Cheng, Yujuan
Dang, Qingqing
Dong, Tengfei
Du, Dalong
Feng, Shouqiang
Gao, Haoyuan
Han, Baochang
Han, Jinchen
Hao, Nanyu
He, Daoyuan
He, Zhengyan
Hou, Jue
Huang, Chang
Huang, Zhiheng
Hu, Na
Kong, Qi
Liao, Gang
Li, Bo
Li, Jiajie
Li, Jing
Li, Lei
Li, Peng
Liu, Sheng
Liu, Yuan
Li, Yuze
Luo, Heng
Luo, Tao
Lyu, Qin
Mao, Hongyue
Qian, Xiaojun
Qi, Jun
Qin, Duohao
Shen, Guolong
Shi, Guangchuan
Song, Xiang
Wang, Jiang
Wang, Yanfei
Wang, Yong
Weng, Renliang
Xu, Tianbing
Xu, Wei
Xu, Xingyu
Yan, Chong
Yan, Chunwei
Yang, Yi
Yu, Yang
Yu, Yinan
Zhang, Jian
Zhang, Ruiqing
Zhang, Weide
Zhao, Liang
Zhou, Jie

File diff suppressed because it is too large Load Diff

@ -0,0 +1,24 @@
#
# Find libglog
#
# LIBGLOG_INCLUDE_DIR - where to find glog/logging.h, etc.
# LIBGLOG_LIBRARY - List of libraries when using libglog.
# LIBGLOG_FOUND - True if libglog found.
#
# from https://github.com/facebook/hhvm/blob/master/CMake/FindGlog.cmake
IF (LIBGLOG_INCLUDE_DIR)
# Already in cache, be silent
SET(LIBGLOG_FIND_QUIETLY TRUE)
ENDIF ()
FIND_PATH(LIBGLOG_INCLUDE_DIR glog/logging.h)
FIND_LIBRARY(LIBGLOG_LIBRARY glog)
# handle the QUIETLY and REQUIRED arguments and set LIBGLOG_FOUND to TRUE if
# all listed variables are TRUE
INCLUDE(FindPackageHandleStandardArgs)
FIND_PACKAGE_HANDLE_STANDARD_ARGS(LIBGLOG DEFAULT_MSG LIBGLOG_LIBRARY LIBGLOG_INCLUDE_DIR)
MARK_AS_ADVANCED(LIBGLOG_LIBRARY LIBGLOG_INCLUDE_DIR)

@ -0,0 +1,38 @@
# Find the Python NumPy package
# PYTHON_NUMPY_INCLUDE_DIR
# NUMPY_FOUND
# will be set by this script
cmake_minimum_required(VERSION 2.6)
if(NOT PYTHON_EXECUTABLE)
if(NumPy_FIND_QUIETLY)
find_package(PythonInterp QUIET)
else()
find_package(PythonInterp)
set(_numpy_out 1)
endif()
endif()
if (PYTHON_EXECUTABLE)
# write a python script that finds the numpy path
file(WRITE ${PROJECT_BINARY_DIR}/FindNumpyPath.py
"try: import numpy; print(numpy.get_include())\nexcept:pass\n")
# execute the find script
exec_program("${PYTHON_EXECUTABLE}" ${PROJECT_BINARY_DIR}
ARGS "FindNumpyPath.py"
OUTPUT_VARIABLE NUMPY_PATH)
elseif(_numpy_out)
message(STATUS "Python executable not found.")
endif(PYTHON_EXECUTABLE)
find_path(PYTHON_NUMPY_INCLUDE_DIR numpy/arrayobject.h
HINTS "${NUMPY_PATH}" "${PYTHON_INCLUDE_PATH}")
if(PYTHON_NUMPY_INCLUDE_DIR)
set(PYTHON_NUMPY_FOUND 1 CACHE INTERNAL "Python numpy found")
endif(PYTHON_NUMPY_INCLUDE_DIR)
include(FindPackageHandleStandardArgs)
find_package_handle_standard_args(NumPy DEFAULT_MSG PYTHON_NUMPY_INCLUDE_DIR)

@ -0,0 +1,30 @@
# Find if a Python module is installed
# Found at http://www.cmake.org/pipermail/cmake/2011-January/041666.html
# To use do: find_python_module(PyQt4 REQUIRED)
function(find_python_module module)
string(TOUPPER ${module} module_upper)
if(NOT PY_${module_upper})
if(ARGC GREATER 1 AND ARGV1 STREQUAL "REQUIRED")
set(${module}_FIND_REQUIRED TRUE)
else()
set(${module}_FIND_REQUIRED FALSE)
endif()
# A module's location is usually a directory, but for binary modules
# it's a .so file.
execute_process(COMMAND "${PYTHON_EXECUTABLE}" "-c"
"import re, ${module}; print(re.compile('/__init__.py.*').sub('',${module}.__file__))"
RESULT_VARIABLE _${module}_status
OUTPUT_VARIABLE _${module}_location
ERROR_QUIET
OUTPUT_STRIP_TRAILING_WHITESPACE)
if(NOT _${module}_status)
set(PY_${module_upper} ${_${module}_location} CACHE STRING
"Location of Python module ${module}")
endif(NOT _${module}_status)
endif(NOT PY_${module_upper})
find_package_handle_standard_args(PY_${module} DEFAULT_MSG PY_${module_upper})
if(NOT PY_${module_upper}_FOUND AND ${module}_FIND_REQUIRED)
message(FATAL_ERROR "python module ${module} is not found")
endif()
set(PY_${module_upper}_FOUND ${PY_${module_upper}_FOUND} PARENT_SCOPE)
endfunction(find_python_module)

@ -0,0 +1,146 @@
# - This module looks for Sphinx
# Find the Sphinx documentation generator
#
# This modules defines
# SPHINX_EXECUTABLE
# SPHINX_FOUND
find_program(SPHINX_EXECUTABLE
NAMES sphinx-build
PATHS
/usr/bin
/usr/local/bin
/opt/local/bin
DOC "Sphinx documentation generator"
)
if( NOT SPHINX_EXECUTABLE )
set(_Python_VERSIONS
2.7 2.6 2.5 2.4 2.3 2.2 2.1 2.0 1.6 1.5
)
foreach( _version ${_Python_VERSIONS} )
set( _sphinx_NAMES sphinx-build-${_version} )
find_program( SPHINX_EXECUTABLE
NAMES ${_sphinx_NAMES}
PATHS
/usr/bin
/usr/local/bin
/opt/loca/bin
DOC "Sphinx documentation generator"
)
endforeach()
endif()
include(FindPackageHandleStandardArgs)
find_package_handle_standard_args(Sphinx DEFAULT_MSG
SPHINX_EXECUTABLE
)
option( SPHINX_HTML_OUTPUT "Build a single HTML with the whole content." ON )
option( SPHINX_DIRHTML_OUTPUT "Build HTML pages, but with a single directory per document." OFF )
option( SPHINX_HTMLHELP_OUTPUT "Build HTML pages with additional information for building a documentation collection in htmlhelp." OFF )
option( SPHINX_QTHELP_OUTPUT "Build HTML pages with additional information for building a documentation collection in qthelp." OFF )
option( SPHINX_DEVHELP_OUTPUT "Build HTML pages with additional information for building a documentation collection in devhelp." OFF )
option( SPHINX_EPUB_OUTPUT "Build HTML pages with additional information for building a documentation collection in epub." OFF )
option( SPHINX_LATEX_OUTPUT "Build LaTeX sources that can be compiled to a PDF document using pdflatex." OFF )
option( SPHINX_MAN_OUTPUT "Build manual pages in groff format for UNIX systems." OFF )
option( SPHINX_TEXT_OUTPUT "Build plain text files." OFF )
mark_as_advanced(
SPHINX_EXECUTABLE
SPHINX_HTML_OUTPUT
SPHINX_DIRHTML_OUTPUT
SPHINX_HTMLHELP_OUTPUT
SPHINX_QTHELP_OUTPUT
SPHINX_DEVHELP_OUTPUT
SPHINX_EPUB_OUTPUT
SPHINX_LATEX_OUTPUT
SPHINX_MAN_OUTPUT
SPHINX_TEXT_OUTPUT
)
function( Sphinx_add_target target_name builder conf cache source destination )
add_custom_target( ${target_name} ALL
COMMAND ${SPHINX_EXECUTABLE} -b ${builder}
-d ${cache}
-c ${conf}
${source}
${destination}
COMMENT "Generating sphinx documentation: ${builder}"
)
set_property(
DIRECTORY APPEND PROPERTY
ADDITIONAL_MAKE_CLEAN_FILES
${destination}
)
endfunction()
# Target dependencies can be optionally listed at the end.
function( Sphinx_add_targets target_base_name conf source base_destination )
set( _dependencies )
foreach( arg IN LISTS ARGN )
set( _dependencies ${_dependencies} ${arg} )
endforeach()
if( ${SPHINX_HTML_OUTPUT} )
Sphinx_add_target( ${target_base_name}_html html ${conf} ${source} ${base_destination}/html )
add_dependencies( ${target_base_name}_html ${_dependencies} )
endif()
if( ${SPHINX_DIRHTML_OUTPUT} )
Sphinx_add_target( ${target_base_name}_dirhtml dirhtml ${conf} ${source} ${base_destination}/dirhtml )
add_dependencies( ${target_base_name}_dirhtml ${_dependencies} )
endif()
if( ${SPHINX_QTHELP_OUTPUT} )
Sphinx_add_target( ${target_base_name}_qthelp qthelp ${conf} ${source} ${base_destination}/qthelp )
add_dependencies( ${target_base_name}_qthelp ${_dependencies} )
endif()
if( ${SPHINX_DEVHELP_OUTPUT} )
Sphinx_add_target( ${target_base_name}_devhelp devhelp ${conf} ${source} ${base_destination}/devhelp )
add_dependencies( ${target_base_name}_devhelp ${_dependencies} )
endif()
if( ${SPHINX_EPUB_OUTPUT} )
Sphinx_add_target( ${target_base_name}_epub epub ${conf} ${source} ${base_destination}/epub )
add_dependencies( ${target_base_name}_epub ${_dependencies} )
endif()
if( ${SPHINX_LATEX_OUTPUT} )
Sphinx_add_target( ${target_base_name}_latex latex ${conf} ${source} ${base_destination}/latex )
add_dependencies( ${target_base_name}_latex ${_dependencies} )
endif()
if( ${SPHINX_MAN_OUTPUT} )
Sphinx_add_target( ${target_base_name}_man man ${conf} ${source} ${base_destination}/man )
add_dependencies( ${target_base_name}_man ${_dependencies} )
endif()
if( ${SPHINX_TEXT_OUTPUT} )
Sphinx_add_target( ${target_base_name}_text text ${conf} ${source} ${base_destination}/text )
add_dependencies( ${target_base_name}_text ${_dependencies} )
endif()
if( ${BUILD_TESTING} )
sphinx_add_target( ${target_base_name}_linkcheck linkcheck ${conf} ${source} ${base_destination}/linkcheck )
add_dependencies( ${target_base_name}_linkcheck ${_dependencies} )
endif()
endfunction()

@ -0,0 +1,119 @@
# Find the CBlas libraries
#
# It will search MKL, atlas, OpenBlas, reference-cblas in order.
#
# If any cblas implementation found, the following variable will be set.
# CBLAS_PROVIDER # one of MKL, ATLAS, OPENBLAS, REFERENCE
# CBLAS_INC_DIR # the include directory for cblas.
# CBLAS_LIBS # a list of libraries should be linked by paddle.
# # Each library should be full path to object file.
#
# User should set one of MKL_ROOT, ATLAS_ROOT, OPENBLAS_ROOT, REFERENCE_CBLAS_ROOT
# during cmake. If none of them set, it will try to find cblas implementation in
# system paths.
#
## Find MKL First.
set(MKL_ROOT $ENV{MKL_ROOT} CACHE PATH "Folder contains MKL")
find_path(MKL_INCLUDE_DIR mkl.h PATHS ${MKL_ROOT}/include)
find_library(MKL_CORE_LIB NAMES mkl_core PATHS ${MKL_ROOT}/lib)
find_library(MKL_SEQUENTIAL_LIB NAMES mkl_sequential PATHS ${MKL_ROOT}/lib)
find_library(MKL_INTEL_LP64 NAMES mkl_intel_lp64 PATHS ${MKL_ROOT}/lib)
if(MKL_INCLUDE_DIR AND MKL_CORE_LIB AND MKL_SEQUENTIAL_LIB AND MKL_INTEL_LP64)
set(CBLAS_PROVIDER MKL)
set(CBLAS_INC_DIR ${MKL_INCLUDE_DIR})
set(CBLAS_LIBS ${MKL_INTEL_LP64}
${MKL_SEQUENTIAL_LIB}
${MKL_CORE_LIB})
add_definitions(-DPADDLE_USE_MKL)
return() # return file.
endif()
## Then find atlas.
set(ATLAS_ROOT $ENV{ATLAS_ROOT} CACHE PATH "Folder contains Atlas")
set(ATLAS_INCLUDE_SEARCH_PATHS
${ATLAS_ROOT}/include
/usr/include
/usr/include/atlas)
set(ATLAS_LIB_SEARCH_PATHS
${ATLAS_ROOT}/lib
/usr/lib
/usr/lib/blas/atlas
/usr/lib/atlas
/usr/lib/atlas-base # special for ubuntu 14.04.
)
find_path(ATLAS_INC_DIR NAMES cblas.h
PATHS ${ATLAS_INCLUDE_SEARCH_PATHS})
find_library(ATLAS_CBLAS_LIB NAMES cblas libcblas.so.3
PATHS ${ATLAS_LIB_SEARCH_PATHS})
find_library(ATLAS_LIB NAMES atlas libatlas.so.3
PATHS ${ATLAS_LIB_SEARCH_PATHS})
if(ATLAS_INC_DIR AND ATLAS_CBLAS_LIB AND ATLAS_LIB)
set(CBLAS_PROVIDER ATLAS)
set(CBLAS_INC_DIR ${ATLAS_INC_DIR})
set(CBLAS_LIBS ${ATLAS_LIB} ${ATLAS_CBLAS_LIB})
return()
endif()
## Then find openblas.
set(OPENBLAS_ROOT $ENV{OPENBLAS_ROOT} CACHE PATH "Folder contains Openblas")
set(OPENBLAS_INCLUDE_SEARCH_PATHS
${OPENBLAS_ROOT}/include
/usr/include
/usr/include/openblas)
set(OPENBLAS_LIB_SEARCH_PATHS
${OPENBLAS_ROOT}/lib
/usr/lib
/usr/lib/blas/openblas
/usr/lib/openblas)
find_path(OPENBLAS_INC_DIR NAMES cblas.h
PATHS ${OPENBLAS_INCLUDE_SEARCH_PATHS})
find_library(OPENBLAS_LIB NAMES openblas
PATHS ${OPENBLAS_LIB_SEARCH_PATHS})
if(OPENBLAS_INC_DIR AND OPENBLAS_LIB)
set(CBLAS_PROVIDER OPENBLAS)
set(CBLAS_INC_DIR ${OPENBLAS_INC_DIR})
set(CBLAS_LIBS ${OPENBLAS_LIB})
return()
endif()
## Then find the reference-cblas. www.netlib.org/blas/
set(REFERENCE_CBLAS_ROOT $ENV{REFERENCE_CBLAS_ROOT} CACHE PATH
"Folder contains reference-cblas")
set(REFERENCE_CBLAS_INCLUDE_SEARCH_PATHS
${REFERENCE_CBLAS_ROOT}/include
/usr/include
/usr/include/cblas
)
set(REFERENCE_CBLAS_LIB_SEARCH_PATHS
${REFERENCE_CBLAS_ROOT}/lib
/usr/lib
/usr/lib/blas/reference/
/usr/lib/reference/
)
find_path(REFERENCE_CBLAS_INCLUDE_DIR NAMES cblas.h PATHS
${REFERENCE_CBLAS_INCLUDE_SEARCH_PATHS})
find_library(REFERENCE_CBLAS_LIBRARY NAMES cblas PATHS
${REFERENCE_CBLAS_LIB_SEARCH_PATHS})
if (REFERENCE_CBLAS_INCLUDE_DIR AND REFERENCE_CBLAS_LIBRARY)
set(CBLAS_PROVIDER REFERENCE)
set(CBLAS_INC_DIR ${REFERENCE_CBLAS_INCLUDE_DIR})
set(CBLAS_LIBS ${REFERENCE_CBLAS_LIBRARY})
return()
endif()
message(FATAL_ERROR "CBlas must be set. Paddle support MKL, ATLAS, OpenBlas, reference-cblas."
" Try set MKL_ROOT, ATLAS_ROOT, OPENBLAS_ROOT or REFERENCE_CBLAS_ROOT.")

@ -0,0 +1,9 @@
# Use ccache if found ccache program
find_program(CCACHE_FOUND ccache)
if(CCACHE_FOUND)
message(STATUS "Ccache is founded, use ccache to speed up compile.")
set_property(GLOBAL PROPERTY RULE_LAUNCH_COMPILE ccache)
set_property(GLOBAL PROPERTY RULE_LAUNCH_LINK ccache)
endif(CCACHE_FOUND)

@ -0,0 +1,45 @@
# Check package for each cmake option
if(WITH_GPU)
find_package(CUDA REQUIRED) # CUDA is required when use gpu
endif()
if(WITH_PYTHON)
find_package(PythonLibs 2.6 REQUIRED)
find_package(PythonInterp REQUIRED)
find_package(NumPy REQUIRED)
endif()
if(WITH_STYLE_CHECK)
find_package(PythonInterp REQUIRED)
endif()
if(WITH_GLOG)
find_package(Glog REQUIRED)
endif()
if(WITH_GFLAGS)
find_package(Gflags REQUIRED)
endif()
if(WITH_TESTING)
find_package(GTest REQUIRED)
endif()
if(WITH_DOC)
find_package(Sphinx REQUIRED)
find_package(Doxygen REQUIRED)
find_python_module(recommonmark REQUIRED)
find_python_module(breathe REQUIRED)
endif()
if(WITH_SWIG_PY)
if(NOT SWIG_FOUND)
message(FATAL_ERROR "SWIG is not found. Please install swig or disable WITH_SWIG_PY")
endif()
find_python_module(wheel REQUIRED) # package wheel
endif()
if(NOT M4_EXECUTABLE)
message(FATAL_ERROR "Paddle need m4 to generate proto file.")
endif()

@ -0,0 +1,62 @@
# util to check C++ file style
# * it basically use google cpplint.py.
# * It provide "add_style_check_target" for cmake.
# Usage see add_style_check_target's document
#
# TODO(yuyang18): Add python style check.
set(STYLE_FILTER)
# diable unwanted filters
# paddle do not indent public/potected/private in class
set(STYLE_FILTER "${STYLE_FILTER}-whitespace/indent,")
# paddle use mutable reference. BUT IT IS NOT RECOMMANDED
set(STYLE_FILTER "${STYLE_FILTER}-runtime/references,")
# paddle use relative path for include.
set(STYLE_FILTER "${STYLE_FILTER}-build/include,")
# paddle use <thread>, <mutex>, etc.
set(STYLE_FILTER "${STYLE_FILTER}-build/c++11,")
# paddle use c style casting. BUT IT IS NOT RECOMMANDED
set(STYLE_FILTER "${STYLE_FILTER}-readability/casting")
# IGNORE SOME FILES
set(IGNORE_PATTERN
.*ImportanceSampler.*
.*cblas\\.h.*
.*LtrDataProvider.*
.*MultiDataProvider.*)
# add_style_check_target
#
# attach check code style step for target.
#
# first argument: target name to attach
# rest arguments: source list to check code style.
#
# NOTE: If WITH_STYLE_CHECK is OFF, then this macro just do nothing.
macro(add_style_check_target TARGET_NAME)
if(WITH_STYLE_CHECK)
set(SOURCES_LIST ${ARGN})
list(REMOVE_DUPLICATES SOURCES_LIST)
list(SORT SOURCES_LIST)
foreach(filename ${SOURCES_LIST})
set(LINT ON)
foreach(pattern ${IGNORE_PATTERN})
if(filename MATCHES ${pattern})
message(STATUS "DROP LINT ${filename}")
set(LINT OFF)
endif()
endforeach()
if(LINT MATCHES ON)
add_custom_command(TARGET ${TARGET_NAME}
PRE_BUILD
COMMAND "${PYTHON_EXECUTABLE}" "${PROJ_ROOT}/paddle/scripts/cpplint.py"
"--filter=${STYLE_FILTER}" ${filename}
WORKING_DIRECTORY ${CMAKE_CURRENT_LIST_DIR})
endif()
endforeach()
endif()
endmacro()

@ -0,0 +1,68 @@
set(CUDNN_ROOT "" CACHE PATH "CUDNN ROOT")
find_path(CUDNN_INCLUDE_DIR cudnn.h
PATHS ${CUDNN_ROOT} ${CUDNN_ROOT}/include
$ENV{CUDNN_ROOT} $ENV{CUDNN_ROOT}/include ${CUDA_TOOLKIT_INCLUDE}
NO_DEFAULT_PATH
)
get_filename_component(__libpath_hist ${CUDA_CUDART_LIBRARY} PATH)
list(APPEND CUDNN_CHECK_LIBRARY_DIRS
${CUDNN_ROOT}
${CUDNN_ROOT}/lib64
${CUDNN_ROOT}/lib
$ENV{CUDNN_ROOT}
$ENV{CUDNN_ROOT}/lib64
$ENV{CUDNN_ROOT}/lib
/usr/lib)
find_library(CUDNN_LIBRARY NAMES libcudnn.so # libcudnn_static.a
PATHS ${CUDNN_CHECK_LIBRARY_DIRS} ${CUDNN_INCLUDE_DIR} ${__libpath_hist}
NO_DEFAULT_PATH
DOC "Path to cuDNN library.")
if(CUDNN_INCLUDE_DIR AND CUDNN_LIBRARY)
set(CUDNN_FOUND ON)
else()
set(CUDNN_FOUND OFF)
endif()
if(CUDNN_FOUND)
file(READ ${CUDNN_INCLUDE_DIR}/cudnn.h CUDNN_VERSION_FILE_CONTENTS)
get_filename_component(CUDNN_LIB_PATH ${CUDNN_LIBRARY} DIRECTORY)
string(REGEX MATCH "define CUDNN_VERSION +([0-9]+)"
CUDNN_VERSION "${CUDNN_VERSION_FILE_CONTENTS}")
string(REGEX REPLACE "define CUDNN_VERSION +([0-9]+)" "\\1"
CUDNN_VERSION "${CUDNN_VERSION}")
if("${CUDNN_VERSION}" STREQUAL "2000")
message(STATUS "Current cuDNN version is v2. ")
else()
string(REGEX MATCH "define CUDNN_MAJOR +([0-9]+)" CUDNN_MAJOR_VERSION
"${CUDNN_VERSION_FILE_CONTENTS}")
string(REGEX REPLACE "define CUDNN_MAJOR +([0-9]+)" "\\1"
CUDNN_MAJOR_VERSION "${CUDNN_MAJOR_VERSION}")
string(REGEX MATCH "define CUDNN_MINOR +([0-9]+)" CUDNN_MINOR_VERSION
"${CUDNN_VERSION_FILE_CONTENTS}")
string(REGEX REPLACE "define CUDNN_MINOR +([0-9]+)" "\\1"
CUDNN_MINOR_VERSION "${CUDNN_MINOR_VERSION}")
string(REGEX MATCH "define CUDNN_PATCHLEVEL +([0-9]+)"
CUDNN_PATCHLEVEL_VERSION "${CUDNN_VERSION_FILE_CONTENTS}")
string(REGEX REPLACE "define CUDNN_PATCHLEVEL +([0-9]+)" "\\1"
CUDNN_PATCHLEVEL_VERSION "${CUDNN_PATCHLEVEL_VERSION}")
if(NOT CUDNN_MAJOR_VERSION)
set(CUDNN_VERSION "???")
else()
math(EXPR CUDNN_VERSION
"${CUDNN_MAJOR_VERSION} * 1000 +
${CUDNN_MINOR_VERSION} * 100 + ${CUDNN_PATCHLEVEL_VERSION}")
endif()
message(STATUS "Current cuDNN header is ${CUDNN_INCLUDE_DIR}/cudnn.h. "
"Current cuDNN version is v${CUDNN_MAJOR_VERSION}. ")
endif()
endif()

@ -0,0 +1,13 @@
# Enable C++ 11 for GCC.
# NOTE: It's only tested for gcc.
include(CheckCXXCompilerFlag)
CHECK_CXX_COMPILER_FLAG("-std=c++11" COMPILER_SUPPORT_CXX11)
CHECK_CXX_COMPILER_FLAG("-std=c++0x" COMPILER_SUPPORT_CXX0X)
if(COMPILER_SUPPORT_CXX11)
set(CMAKE_CXX_FLAGS "${CMAKE_CXX_FLAGS} -std=c++11")
elseif(COMPILER_SUPPORT_CXX0X)
set(CMAKE_CXX_FLAGS "${CMAKE_CXX_FLAGS} -std=c++0x")
else()
message(FATAL_ERROR "Your compiler must support c++11")
endif()

@ -0,0 +1,86 @@
# Setting Paddle Compile Flags
include(CheckCXXCompilerFlag)
include(CheckCCompilerFlag)
include(CheckCXXSymbolExists)
# safe_set_flag
#
# Set a compile flag only if compiler is support
# is_c: is C flag or C++ flag, bool type.
# src_list: The list name which the flag name will be append to.
# flag_name: the flag name for compiler, such as '-Werror' '-Wall' etc
# rest arguments: not used.
function(safe_set_flag is_c src_list flag_name)
string(REPLACE "-" "_" safe_name ${flag_name})
string(REPLACE "=" "_" safe_name ${safe_name})
if(is_c)
CHECK_C_COMPILER_FLAG(${flag_name} C_COMPILER_SUPPORT_FLAG_${safe_name})
set(safe_name C_COMPILER_SUPPORT_FLAG_${safe_name})
else()
CHECK_CXX_COMPILER_FLAG(${flag_name} CXX_COMPILER_SUPPORT_FLAG_${safe_name})
set(safe_name CXX_COMPILER_SUPPORT_FLAG_${safe_name})
endif()
if(${safe_name})
set(${src_list} "${${src_list}} ${flag_name}" PARENT_SCOPE)
if(is_c)
set(CUDA_NVCC_FLAGS
--compiler-options;${flag_name}
${CUDA_NVCC_FLAGS}
PARENT_SCOPE)
endif()
endif()
endfunction()
# helper macro to set cflag
macro(safe_set_cflag src_list flag_name)
safe_set_flag(ON ${src_list} ${flag_name})
endmacro()
# helper macro to set cxxflag
macro(safe_set_cxxflag src_list flag_name)
safe_set_flag(OFF ${src_list} ${flag_name})
endmacro()
CHECK_CXX_SYMBOL_EXISTS(UINT64_MAX "stdint.h" UINT64_MAX_EXISTS)
if(NOT UINT64_MAX_EXISTS)
set(CMAKE_REQUIRED_DEFINITIONS -D__STDC_LIMIT_MACROS)
CHECK_CXX_SYMBOL_EXISTS(UINT64_MAX "stdint.h" UINT64_MAX_EXISTS_HERE)
if(UINT64_MAX_EXISTS_HERE)
set(CMAKE_REQUIRED_DEFINITIONS)
add_definitions(-D__STDC_LIMIT_MACROS)
else()
message(FATAL_ERROR "Cannot find symbol UINT64_MAX")
endif()
endif()
# Common flags. the compiler flag used for C/C++ sources whenever release or debug
# Do not care if this flag is support for gcc.
set(COMMON_FLAGS
-fPIC
-fno-omit-frame-pointer
-Wall
-Wextra
-Werror
-Wnon-virtual-dtor
-Wdelete-non-virtual-dtor
-Wno-unused-parameter
-Wno-error=literal-suffix
-Wno-error=unused-local-typedefs)
foreach(flag ${COMMON_FLAGS})
safe_set_cflag(CMAKE_C_FLAGS ${flag})
safe_set_cxxflag(CMAKE_CXX_FLAGS ${flag})
endforeach()
# Release/Debug flags set by cmake. Such as -O3 -g -DNDEBUG etc.
# So, don't set these flags here.
foreach(capability 30 35 50)
list(APPEND __arch_flags "-gencode arch=compute_${capability},code=sm_${capability}")
endforeach()
if (CUDA_VERSION VERSION_GREATER "7.0")
list(APPEND __arch_flags "-gencode arch=compute_52,code=sm_52")
endif()
set(CUDA_NVCC_FLAGS ${__arch_flags} ${CUDA_NVCC_FLAGS})

@ -0,0 +1,21 @@
set(CPACK_PACKAGE_NAME paddle)
set(CPACK_PACKAGE_DESCRIPTION_SUMMARY "")
set(CPACK_PACKAGE_VERSION_MAJOR ${PADDLE_MAJOR_VERSION})
set(CPACK_PACKAGE_VERSION_MINOR ${PADDLE_MINOR_VERSION})
set(CPACK_PACKAGE_VERSION_PATCH ${PADDLE_PATCH_VERSION})
set(CPACK_PACKAGE_VERSION ${PADDLE_VERSION})
## DEB Settings
set(CPACK_DEBIAN_PACKAGE_NAME paddle)
set(CPACK_DEBIAN_PACKAGE_ARCHITECTURE amd64)
set(CPACK_DEBIAN_PACKAGE_MAINTAINER PaddlePaddle Dev <paddle-dev@baidu.com>)
set(CPACK_PACKAGE_DESCRIPTION_SUMMARY "Paddle")
set(CPACK_PACKAGE_DESCRIPTION "")
set(CPACK_DEBIAN_PACKAGE_DEPENDS "libatlas3-base, libgflags2, libgoogle-glog0, libprotobuf8, libpython2.7, libstdc++6, python-numpy, python-pip, python-pip-whl, python-protobuf")
set(CPACK_DEBIAN_PACKAGE_SECTION Devel)
set(CPACK_DEBIAN_PACKAGE_CONTROL_EXTRA "${PROJ_ROOT}/paddle/scripts/deb/postinst")
#set(CPACK_GENERATOR "DEB")
# Start cpack
include (CMakePackageConfigHelpers)
include (CPack)

@ -0,0 +1,36 @@
find_program(
SWIG_BINARY_PATH
swig)
if(${SWIG_BINARY_PATH} STREQUAL "SWIG_BINARY_PATH-NOTFOUND")
set(SWIG_FOUND OFF)
else()
set(SWIG_FOUND ON)
endif()
set(MIN_SWIG_VERSION 2)
if(SWIG_FOUND)
execute_process(COMMAND sh -c "${SWIG_BINARY_PATH} -version | grep Version | cut -f3 -d' '"
OUTPUT_VARIABLE _SWIG_VERSION
OUTPUT_STRIP_TRAILING_WHITESPACE)
if(${_SWIG_VERSION} VERSION_LESS ${MIN_SWIG_VERSION})
message("swig version ${MIN_SWIG_VERSION} or greater is needed for generating python api. "
"Only version ${_SWIG_VERSION} is found. Set SWIG_FOUND to FALSE")
set(SWIG_FOUND FALSE)
endif(${_SWIG_VERSION} VERSION_LESS ${MIN_SWIG_VERSION})
endif(SWIG_FOUND)
function(generate_python_api target_name)
add_custom_command(OUTPUT ${PROJ_ROOT}/paddle/py_paddle/swig_paddle.py
${PROJ_ROOT}/paddle/Paddle_wrap.cxx
${PROJ_ROOT}/paddle/Paddle_wrap.h
COMMAND swig -python -c++ -outcurrentdir -I../ api/Paddle.swig
&& mv ${PROJ_ROOT}/paddle/swig_paddle.py ${PROJ_ROOT}/paddle/py_paddle/swig_paddle.py
DEPENDS ${PROJ_ROOT}/paddle/api/Paddle.swig
WORKING_DIRECTORY ${PROJ_ROOT}/paddle
COMMENT "Generate Python API from swig")
add_custom_target(${target_name} ALL DEPENDS
${PROJ_ROOT}/paddle/Paddle_wrap.cxx
${PROJ_ROOT}/paddle/Paddle_wrap.h
${PROJ_ROOT}/paddle/py_paddle/swig_paddle.py)
endfunction(generate_python_api)

@ -0,0 +1,147 @@
# Some common routine for paddle compile.
# target_circle_link_libraries
# Link libraries to target which has circle dependencies.
#
# First Argument: target name want to be linked with libraries
# Rest Arguments: libraries which link together.
function(target_circle_link_libraries TARGET_NAME)
target_link_libraries(${TARGET_NAME}
-Wl,--start-group
${ARGN}
-Wl,--end-group)
endfunction()
# compile_cu_as_cpp
# Make a cu file compiled as C++
# Arguments: Source files
macro(compile_cu_as_cpp)
foreach(s ${ARGN})
set_source_files_properties(${s} PROPERTIES LANGUAGE CXX)
set_source_files_properties(${s} PROPERTIES COMPILE_FLAGS "-x c++")
endforeach()
endmacro()
# link_paddle_exe
# add paddle library for a paddle executable, such as trainer, pserver.
#
# It will handle WITH_PYTHON/WITH_GLOG etc.
function(link_paddle_exe TARGET_NAME)
if(WITH_METRIC)
if(WITH_GPU)
set(METRIC_LIBS paddle_metric_learning paddle_dserver_lib metric metric_cpu)
else()
set(METRIC_LIBS paddle_metric_learning paddle_dserver_lib metric_cpu)
endif()
else()
set(METRIC_LIBS "")
endif()
if(PADDLE_WITH_INTERNAL)
set(INTERAL_LIBS paddle_internal_gserver paddle_internal_parameter)
target_circle_link_libraries(${TARGET_NAME}
-Wl,--whole-archive
paddle_internal_gserver
paddle_internal_owlqn
-Wl,--no-whole-archive
paddle_internal_parameter)
else()
set(INTERAL_LIBS "")
endif()
target_circle_link_libraries(${TARGET_NAME}
-Wl,--whole-archive
paddle_gserver
${METRIC_LIBS}
-Wl,--no-whole-archive
paddle_pserver
paddle_trainer_lib
paddle_network
paddle_math
paddle_utils
paddle_parameter
paddle_proto
paddle_cuda
${METRIC_LIBS}
${PROTOBUF_LIBRARY}
${CMAKE_THREAD_LIBS_INIT}
${CBLAS_LIBS}
${CMAKE_DL_LIBS}
${INTERAL_LIBS}
-lz)
if(WITH_PYTHON)
target_link_libraries(${TARGET_NAME}
${PYTHON_LIBRARIES})
endif()
if(WITH_GLOG)
target_link_libraries(${TARGET_NAME}
${LIBGLOG_LIBRARY})
endif()
if(WITH_GFLAGS)
target_link_libraries(${TARGET_NAME}
${GFLAGS_LIBRARIES})
endif()
if(WITH_GPU)
if(NOT WITH_DSO OR WITH_METRIC)
target_link_libraries(${TARGET_NAME}
${CUDNN_LIBRARY}
${CUDA_curand_LIBRARY})
CUDA_ADD_CUBLAS_TO_TARGET(${TARGET_NAME})
endif()
check_library_exists(rt clock_gettime "time.h" HAVE_CLOCK_GETTIME )
if(HAVE_CLOCK_GETTIME)
target_link_libraries(${TARGET_NAME} rt)
endif()
endif()
endfunction()
# link_paddle_test
# Link a paddle unittest for target
# TARGET_NAME: the unittest target name
# Rest Arguemnts: not used.
function(link_paddle_test TARGET_NAME)
link_paddle_exe(${TARGET_NAME})
target_link_libraries(${TARGET_NAME} ${GTEST_MAIN_LIBRARIES}
${GTEST_LIBRARIES})
endfunction()
# add_unittest_without_exec
#
# create a paddle unittest. not specifically define how to run this unittest.
# TARGET_NAME: the unittest target name, same as executable file name
# Rest Arguments: the source files to compile this unittest.
macro(add_unittest_without_exec TARGET_NAME)
add_executable(${TARGET_NAME} ${ARGN})
link_paddle_test(${TARGET_NAME})
add_style_check_target(${TARGET_NAME} ${ARGN})
endmacro()
# add_unittest
# create a paddle unittest and just to execute this binary to make unittest.
#
# TARGET_NAME: the unittest target name, same as executable file name
# Rest Arguments: the source files to compile this unittest.
macro(add_unittest TARGET_NAME)
add_unittest_without_exec(${TARGET_NAME} ${ARGN})
add_test(${TARGET_NAME} ${TARGET_NAME})
endmacro()
# add_simple_unittest
# create a paddle unittest with file name. It just compile ${TARGET_NAME}.cpp to
# ${TARGET_NAME} and then execute it.
macro(add_simple_unittest TARGET_NAME)
add_unittest(${TARGET_NAME} ${TARGET_NAME}.cpp)
endmacro()
macro(add_paddle_culib TARGET_NAME)
set(NVCC_FLAG ${CUDA_NVCC_FLAGS})
set(CUDA_NVCC_FLAGS ${CUDA_NVCC_FLAGS};--use_fast_math)
cuda_add_library(${TARGET_NAME} STATIC ${ARGN})
set(CUDA_NVCC_FLAGS ${NVCC_FLAG})
endmacro()

@ -0,0 +1,7 @@
data/cifar-10-batches-py
data/cifar-out
cifar_vgg_model/*
plot.png
train.log
image_provider_copy_1.py
*pyc

@ -0,0 +1 @@
../model_zoo/resnet/classify.py

@ -0,0 +1,22 @@
#!/bin/bash
# Copyright (c) 2016 Baidu, Inc. 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.
set -e
python classify.py \
--job=predict \
--conf=vgg_16_cifar.py \
--model=./cifar_vgg_model/pass-00299 \
--multi_crop \
--data=./example/test.list

@ -0,0 +1,20 @@
# Copyright (c) 2016 Baidu, Inc. 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.
set -e
wget https://www.cs.toronto.edu/~kriz/cifar-10-python.tar.gz
tar zxf cifar-10-python.tar.gz
rm cifar-10-python.tar.gz
rm -rf cifar-out/*
echo Converting CIFAR data to images.....
python process_cifar.py ./cifar-10-batches-py ./cifar-out

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