Merge branch 'develop' of https://github.com/PaddlePaddle/Paddle into add_depthwiseConv_op_gpu

add_depthwiseConv_op_gpu
xzl 8 years ago
commit fc9b2b9aa3

@ -39,7 +39,7 @@ option(WITH_GPU "Compile PaddlePaddle with NVIDIA GPU" ${CUDA_F
option(WITH_AVX "Compile PaddlePaddle with AVX intrinsics" ${AVX_FOUND})
option(WITH_MKL "Compile PaddlePaddle with MKL support." ${AVX_FOUND})
option(WITH_DSO "Compile PaddlePaddle with dynamic linked CUDA" ON)
option(WITH_TESTING "Compile PaddlePaddle with unit testing" ON)
option(WITH_TESTING "Compile PaddlePaddle with unit testing" OFF)
option(WITH_SWIG_PY "Compile PaddlePaddle with inference api" ON)
option(WITH_STYLE_CHECK "Compile PaddlePaddle with style check" ON)
option(WITH_PYTHON "Compile PaddlePaddle with python interpreter" ON)

@ -15,9 +15,9 @@
include(ExternalProject)
set(BOOST_PROJECT "extern_boost")
set(BOOST_VER "1.66.0")
set(BOOST_TAR "boost_1_66_0")
set(BOOST_URL "https://dl.bintray.com/boostorg/release/${BOOST_VER}/source/${BOOST_TAR}.tar.gz")
set(BOOST_VER "1.41.0")
set(BOOST_TAR "boost_1_41_0")
set(BOOST_URL "http://sourceforge.net/projects/boost/files/boost/${BOOST_VER}/${BOOST_TAR}.tar.gz")
set(BOOST_SOURCES_DIR ${THIRD_PARTY_PATH}/boost)
set(BOOST_DOWNLOAD_DIR "${BOOST_SOURCES_DIR}/src/${BOOST_PROJECT}")
set(BOOST_INCLUDE_DIR "${BOOST_DOWNLOAD_DIR}/${BOOST_TAR}" CACHE PATH "boost include directory." FORCE)

@ -186,6 +186,11 @@ function(cc_library TARGET_NAME)
add_library(${TARGET_NAME} STATIC ${cc_library_SRCS})
endif()
if (cc_library_DEPS)
# Don't need link libwarpctc.so
if ("${cc_library_DEPS};" MATCHES "warpctc;")
list(REMOVE_ITEM cc_library_DEPS warpctc)
add_dependencies(${TARGET_NAME} warpctc)
endif()
add_dependencies(${TARGET_NAME} ${cc_library_DEPS})
target_link_libraries(${TARGET_NAME} ${cc_library_DEPS})
endif()
@ -224,12 +229,18 @@ function(cc_test TARGET_NAME)
if(WITH_TESTING)
set(options "")
set(oneValueArgs "")
set(multiValueArgs SRCS DEPS)
set(multiValueArgs SRCS DEPS ARGS)
cmake_parse_arguments(cc_test "${options}" "${oneValueArgs}" "${multiValueArgs}" ${ARGN})
add_executable(${TARGET_NAME} ${cc_test_SRCS})
target_link_libraries(${TARGET_NAME} ${cc_test_DEPS} paddle_gtest_main paddle_memory gtest gflags)
# Support linking flags: --whole-archive (Linux) / -force_load (MacOS)
target_circle_link_libraries(${TARGET_NAME} ${cc_test_DEPS} paddle_gtest_main paddle_memory gtest gflags)
if("${cc_test_DEPS}" MATCHES "ARCHIVE_START")
list(REMOVE_ITEM cc_test_DEPS ARCHIVE_START ARCHIVE_END)
endif()
add_dependencies(${TARGET_NAME} ${cc_test_DEPS} paddle_gtest_main paddle_memory gtest gflags)
add_test(NAME ${TARGET_NAME} COMMAND ${TARGET_NAME} WORKING_DIRECTORY ${CMAKE_CURRENT_SOURCE_DIR})
add_test(NAME ${TARGET_NAME}
COMMAND ${TARGET_NAME} ${cc_test_ARGS}
WORKING_DIRECTORY ${CMAKE_CURRENT_SOURCE_DIR})
endif()
endfunction(cc_test)
@ -457,12 +468,12 @@ endfunction()
function(py_test TARGET_NAME)
if(WITH_TESTING)
set(options STATIC static SHARED shared)
set(options "")
set(oneValueArgs "")
set(multiValueArgs SRCS DEPS ARGS)
set(multiValueArgs SRCS DEPS ARGS ENVS)
cmake_parse_arguments(py_test "${options}" "${oneValueArgs}" "${multiValueArgs}" ${ARGN})
add_test(NAME ${TARGET_NAME}
COMMAND env PYTHONPATH=${PADDLE_PYTHON_BUILD_DIR}/lib-python
COMMAND env PYTHONPATH=${PADDLE_PYTHON_BUILD_DIR}/lib-python ${py_test_ENVS}
${PYTHON_EXECUTABLE} -u ${py_test_SRCS} ${py_test_ARGS}
WORKING_DIRECTORY ${CMAKE_CURRENT_SOURCE_DIR})
endif()

@ -1,9 +1,14 @@
.. THIS FILE IS GENERATED BY `gen_doc.{py|sh}`
!DO NOT EDIT THIS FILE MANUALLY!
===========
DataFeeder
data_feeder
===========
DataFeeder
-----------
.. automodule:: paddle.v2.fluid.data_feeder
:members: DataFeeder
----------
.. autoclass:: paddle.v2.fluid.data_feeder.DataFeeder
:members:
:noindex:

@ -1,9 +1,21 @@
===========
Evaluator
===========
Evaluator
-----------
.. automodule:: paddle.v2.fluid.evaluator
:members: Evaluator
.. THIS FILE IS GENERATED BY `gen_doc.{py|sh}`
!DO NOT EDIT THIS FILE MANUALLY!
=========
evaluator
=========
Accuracy
--------
.. autoclass:: paddle.v2.fluid.evaluator.Accuracy
:members:
:noindex:
ChunkEvaluator
--------------
.. autoclass:: paddle.v2.fluid.evaluator.ChunkEvaluator
:members:
:noindex:

@ -1,9 +1,32 @@
===========
Executor
===========
.. THIS FILE IS GENERATED BY `gen_doc.{py|sh}`
!DO NOT EDIT THIS FILE MANUALLY!
========
executor
========
Executor
--------
.. autoclass:: paddle.v2.fluid.executor.Executor
:members:
:noindex:
global_scope
------------
.. autofunction:: paddle.v2.fluid.executor.global_scope
:noindex:
scope_guard
-----------
.. automodule:: paddle.v2.fluid.executor
:members: Executor
.. autofunction:: paddle.v2.fluid.executor.scope_guard
:noindex:
switch_scope
------------
.. autofunction:: paddle.v2.fluid.executor.switch_scope
:noindex:

@ -0,0 +1,109 @@
# 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.
from __future__ import print_function
import argparse
import sys
import types
import paddle.v2.fluid as fluid
def parse_arg():
parser = argparse.ArgumentParser()
parser.add_argument('--submodules', nargs="*")
parser.add_argument(
'module', type=str, help='Generate the documentation of which module')
return parser.parse_args()
class DocGenerator(object):
def __init__(self, module_name, stream=sys.stdout):
self.stream = stream
self.module_name = module_name
if not hasattr(fluid, module_name):
raise ValueError("Cannot find fluid.{0}".format(module_name))
else:
self.module = getattr(fluid, module_name)
self.stream.write('''.. THIS FILE IS GENERATED BY `gen_doc.{py|sh}`
!DO NOT EDIT THIS FILE MANUALLY!
''')
self._print_header_(module_name, dot='=', is_title=True)
def print_submodule(self, submodule_name):
submodule = getattr(self.module, submodule_name)
if submodule is None:
raise ValueError("Cannot find submodule {0}".format(submodule_name))
self.print_section(submodule_name)
for item in submodule.__all__:
self.print_item(item)
def print_current_module(self):
for item in self.module.__all__:
self.print_item(item)
def print_section(self, name):
self._print_header_(name, dot='=', is_title=False)
def print_item(self, name):
item = getattr(self.module, name)
if isinstance(item, types.TypeType):
self.print_class(name)
elif isinstance(item, types.FunctionType):
self.print_method(name)
else:
raise RuntimeError("Unsupported item {0}".format(name))
def print_class(self, name):
self._print_header_(name, dot='-', is_title=False)
self.stream.write('''.. autoclass:: paddle.v2.fluid.{0}.{1}
:members:
:noindex:
'''.format(self.module_name, name))
def print_method(self, name):
self._print_header_(name, dot='-', is_title=False)
self.stream.write('''.. autofunction:: paddle.v2.fluid.{0}.{1}
:noindex:
'''.format(self.module_name, name))
def _print_header_(self, name, dot, is_title):
dot_line = dot * len(name)
if is_title:
self.stream.write(dot_line)
self.stream.write('\n')
self.stream.write(name)
self.stream.write('\n')
self.stream.write(dot_line)
self.stream.write('\n')
self.stream.write('\n')
def main():
args = parse_arg()
gen = DocGenerator(args.module)
if args.submodules is None:
gen.print_current_module()
else:
for submodule_name in args.submodules:
gen.print_submodule(submodule_name)
if __name__ == '__main__':
main()

@ -0,0 +1,7 @@
#!/bin/bash
python gen_doc.py layers --submodules control_flow device io nn ops tensor > layers.rst
for module in io data_feeder evaluator executor initializer io nets optimizer param_attr profiler regularizer
do
python gen_doc.py ${module} > ${module}.rst
done

@ -1,50 +1,35 @@
.. THIS FILE IS GENERATED BY `gen_doc.{py|sh}`
!DO NOT EDIT THIS FILE MANUALLY!
===========
Initializer
initializer
===========
Constant
--------
Initializer
-----------
.. automodule:: paddle.v2.fluid.initializer
:members: Initializer
:noindex:
ConstantInitializer
-------------------
.. automodule:: paddle.v2.fluid.initializer
:members: ConstantInitializer
.. autoclass:: paddle.v2.fluid.initializer.Constant
:members:
:noindex:
Uniform
-------
UniformInitializer
------------------
.. automodule:: paddle.v2.fluid.initializer
:members: UniformInitializer
:noindex:
NormalInitializer
-----------------
.. automodule:: paddle.v2.fluid.initializer
:members: NormalInitializer
.. autoclass:: paddle.v2.fluid.initializer.Uniform
:members:
:noindex:
Normal
------
XavierInitializer
-----------------
.. automodule:: paddle.v2.fluid.initializer
:members: XavierInitializer
.. autoclass:: paddle.v2.fluid.initializer.Normal
:members:
:noindex:
Xavier
------
MSRAInitializer
---------------
.. automodule:: paddle.v2.fluid.initializer
:members: MSRAInitializer
.. autoclass:: paddle.v2.fluid.initializer.Xavier
:members:
:noindex:

@ -1,10 +1,61 @@
===========
IO
===========
.. THIS FILE IS GENERATED BY `gen_doc.{py|sh}`
!DO NOT EDIT THIS FILE MANUALLY!
==
io
==
save_vars
---------
is_parameter
.. autofunction:: paddle.v2.fluid.io.save_vars
:noindex:
save_params
-----------
.. autofunction:: paddle.v2.fluid.io.is_parameter
.. autofunction:: paddle.v2.fluid.io.save_params
:noindex:
save_persistables
-----------------
.. autofunction:: paddle.v2.fluid.io.save_persistables
:noindex:
load_vars
---------
.. autofunction:: paddle.v2.fluid.io.load_vars
:noindex:
load_params
-----------
.. autofunction:: paddle.v2.fluid.io.load_params
:noindex:
load_persistables
-----------------
.. autofunction:: paddle.v2.fluid.io.load_persistables
:noindex:
save_inference_model
--------------------
.. autofunction:: paddle.v2.fluid.io.save_inference_model
:noindex:
load_inference_model
--------------------
.. autofunction:: paddle.v2.fluid.io.load_inference_model
:noindex:
get_inference_program
---------------------
.. autofunction:: paddle.v2.fluid.io.get_inference_program
:noindex:

File diff suppressed because it is too large Load Diff

@ -1,33 +1,31 @@
===========
Nets
===========
.. THIS FILE IS GENERATED BY `gen_doc.{py|sh}`
!DO NOT EDIT THIS FILE MANUALLY!
====
nets
====
simple_img_conv_pool
--------------------
.. autofunction:: paddle.v2.fluid.nets.simple_img_conv_pool
:noindex:
img_conv_group
---------------
.. autofunction:: paddle.v2.fluid.nets.img_conv_group
.. autofunction:: paddle.v2.fluid.nets.simple_img_conv_pool
:noindex:
sequence_conv_pool
------------------
.. autofunction:: paddle.v2.fluid.nets.sequence_conv_pool
:noindex:
glu
---
.. autofunction:: paddle.v2.fluid.nets.glu
:noindex:
scaled_dot_product_attention
----------------------------
.. autofunction:: paddle.v2.fluid.nets.scaled_dot_product_attention
:noindex:

@ -1,54 +1,49 @@
===========
Optimizer
===========
Optimizer
-----------
.. automodule:: paddle.v2.fluid.optimizer
:members: Optimizer
:noindex:
.. THIS FILE IS GENERATED BY `gen_doc.{py|sh}`
!DO NOT EDIT THIS FILE MANUALLY!
=========
optimizer
=========
SGDOptimizer
-----------
.. automodule:: paddle.v2.fluid.optimizer
:members: SGDOptimizer
:noindex:
SGD
---
.. autoclass:: paddle.v2.fluid.optimizer.SGD
:members:
:noindex:
Momentum
--------
MomentumOptimizer
-----------------
.. automodule:: paddle.v2.fluid.optimizer
:members: MomentumOptimizer
.. autoclass:: paddle.v2.fluid.optimizer.Momentum
:members:
:noindex:
Adagrad
-------
AdagradOptimizer
----------------
.. automodule:: paddle.v2.fluid.optimizer
:members: AdagradOptimizer
.. autoclass:: paddle.v2.fluid.optimizer.Adagrad
:members:
:noindex:
Adam
----
AdamOptimizer
-------------
.. automodule:: paddle.v2.fluid.optimizer
:members: AdamOptimizer
.. autoclass:: paddle.v2.fluid.optimizer.Adam
:members:
:noindex:
Adamax
------
AdamaxOptimizer
-----------
.. automodule:: paddle.v2.fluid.optimizer
:members: AdamaxOptimizer
.. autoclass:: paddle.v2.fluid.optimizer.Adamax
:members:
:noindex:
DecayedAdagrad
--------------
DecayedAdagradOptimizer
-----------------------
.. automodule:: paddle.v2.fluid.optimizer
:members: DecayedAdagradOptimizer
.. autoclass:: paddle.v2.fluid.optimizer.DecayedAdagrad
:members:
:noindex:

@ -1,11 +1,21 @@
===========
.. THIS FILE IS GENERATED BY `gen_doc.{py|sh}`
!DO NOT EDIT THIS FILE MANUALLY!
==========
param_attr
==========
ParamAttr
===========
---------
.. autoclass:: paddle.v2.fluid.param_attr.ParamAttr
:members:
:noindex:
WeightNormParamAttr
-------------------
ParamAttr
-----------
.. automodule:: paddle.v2.fluid.param_attr
:members: ParamAttr
.. autoclass:: paddle.v2.fluid.param_attr.WeightNormParamAttr
:members:
:noindex:

@ -1,10 +1,25 @@
===========
Profiler
===========
.. THIS FILE IS GENERATED BY `gen_doc.{py|sh}`
!DO NOT EDIT THIS FILE MANUALLY!
========
profiler
========
cuda_profiler
-------------
Profiler
-----------
.. autofunction:: paddle.v2.fluid.profiler.cuda_profiler
:noindex:
reset_profiler
--------------
.. autofunction:: paddle.v2.fluid.profiler.reset_profiler
:noindex:
profiler
--------
.. autofunction:: paddle.v2.fluid.profiler.profiler
:noindex:

@ -1,25 +1,27 @@
.. THIS FILE IS GENERATED BY `gen_doc.{py|sh}`
!DO NOT EDIT THIS FILE MANUALLY!
===========
Regularizer
regularizer
===========
WeightDecayRegularizer
----------------------
.. automodule:: paddle.v2.fluid.regularizer
:members: WeightDecayRegularizer
:noindex:
append_regularization_ops
-------------------------
L2DecayRegularizer
------------------
.. automodule:: paddle.v2.fluid.regularizer
:members: L2DecayRegularizer
.. autofunction:: paddle.v2.fluid.regularizer.append_regularization_ops
:noindex:
L1Decay
-------
.. autoclass:: paddle.v2.fluid.regularizer.L1Decay
:members:
:noindex:
L1DecayRegularizer
-------------------
.. automodule:: paddle.v2.fluid.regularizer
:members: L1DecayRegularizer
L2Decay
-------
.. autoclass:: paddle.v2.fluid.regularizer.L2Decay
:members:
:noindex:

@ -140,7 +140,19 @@ TODO by Assignees
### Beam Search with CTC and LM
TODO by Assignees
<div align="center">
<img src="image/beam_search.png" width=600><br/>
Figure 2. Algorithm for CTC Beam Search Decoder.
</div>
- The **Beam Search Decoder** for DS2 CTC-trained network follows the similar approach in \[[3](#references)\] as shown in Figure 2, with two important modifications for the ambiguous parts:
- 1) in the iterative computation of probabilities, the assignment operation is changed to accumulation for one prefix may comes from different paths;
- 2) the if condition ```if l^+ not in A_prev then``` after probabilities' computation is deprecated for it is hard to understand and seems unnecessary.
- An **external scorer** would be passed into the decoder to evaluate a candidate prefix during decoding whenever a white space appended in English decoding and any character appended in Mandarin decoding.
- Such external scorer consists of language model, word count or any other custom scorers.
- The **language model** is built from Task 5, with parameters should be carefully tuned to achieve minimum WER/CER (c.f. Task 7)
- This decoder needs to perform with **high efficiency** for the convenience of parameters tuning and speech recognition in reality.
## Future Work
@ -153,3 +165,4 @@ TODO by Assignees
1. Dario Amodei, etc., [Deep Speech 2 : End-to-End Speech Recognition in English and Mandarin](http://proceedings.mlr.press/v48/amodei16.pdf). ICML 2016.
2. Dario Amodei, etc., [Deep Speech 2 : End-to-End Speech Recognition in English and Mandarin](https://arxiv.org/abs/1512.02595). arXiv:1512.02595.
3. Awni Y. Hannun, etc. [First-Pass Large Vocabulary Continuous Speech Recognition using Bi-Directional Recurrent DNNs](https://arxiv.org/abs/1408.2873). arXiv:1408.2873

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@ -2,9 +2,9 @@
## Background
Deep learning has a high demand for computing resources. New high-performance devices and computing libraries are appearing very frequently. Deep learning frameworks have to integrate these high-performance devices and computing libraries flexibly and efficiently.
Deep learning has a high demand for computing resources. New high-performance devices and computing libraries are appearing very frequently. Deep learning frameworks have to integrate these high-performance devices and computing libraries in a flexible and efficient manner.
On one hand, hardware and computing libraries usually do not have a one-to-one correspondence. For example,Intel CPUs support Eigen and MKL computing libraries while Nvidia GPUs support Eigen and cuDNN computing libraries. We have to implement operator specific kernels for each computing library.
On one hand, hardware and computing libraries usually do not have a one-to-one correspondence. For example, Intel CPUs support Eigen and MKL computing libraries while Nvidia GPUs support Eigen and cuDNN computing libraries. We have to implement operator specific kernels for each computing library.
On the other hand, users usually do not want to care about the low-level hardware and computing libraries when writing a neural network configuration. In Fluid, `Layer` is exposed in `Python`, and `Operator` is exposed in `C++`. Both `Layer` and `Operator` are hardware independent.
@ -17,7 +17,7 @@ For a general overview of fluid, please refer to the [overview doc](https://gith
There are mainly three parts that we have to consider while integrating a new device/library:
- Place and DeviceContext: indicates the device id and manages hardware resources
- Place and DeviceContext: indicate the device id and manage hardware resources
- Memory and Tensor: malloc/free data on certain device
@ -25,10 +25,10 @@ There are mainly three parts that we have to consider while integrating a new de
### Place and DeviceContext
Please remind that device and computing library are not one-to-one corresponding. A device can have a lot of computing libraries and a computing library can also support several devices.
Please note that device and computing library are not one-to-one corresponding. A device can have a lot of computing libraries and a computing library can also support several devices.
#### Place
Fluid uses class [Place](https://github.com/PaddlePaddle/Paddle/blob/develop/paddle/platform/place.h#L55) to represent the device memory where data is located. If we add another device, we have to add corresponding `DevicePlace`.
Fluid uses class [Place](https://github.com/PaddlePaddle/Paddle/blob/develop/paddle/platform/place.h#L55) to represent the device memory where data is located. If we add another device, we have to add the corresponding `DevicePlace`.
```
| CPUPlace
@ -144,7 +144,7 @@ class Tensor {
};
```
`Placeholder` is used to delay memory allocation; that is, we can first define a tensor, using `Resize` to configure its shape, and then call `mutuable_data` to allocate the actual memory.
`Placeholder` is used to delay memory allocation; that is, we can first define a tensor, using `Resize` to configurate its shape, and then call `mutuable_data` to allocate the actual memory.
```cpp
paddle::framework::Tensor t;
@ -163,7 +163,7 @@ Fluid implements computing units based on different DeviceContexts. Some computi
Let's take [MaxOutFunctor](https://github.com/PaddlePaddle/Paddle/blob/develop/paddle/operators/math/maxouting.h#L27) as an example:
The interface is defined in header file.
The interface is defined in the header file.
```
template <typename DeviceContext, typename T>
@ -174,7 +174,7 @@ class MaxOutFunctor {
};
```
CPU implemention is in .cc file
CPU implementation is in .cc file
```
template <typename T>
@ -188,7 +188,7 @@ class MaxOutFunctor<platform::CPUDeviceContext, T> {
};
```
CUDA implemention is in .cu file
CUDA implementation is in .cu file
```
template <typename T>
@ -203,9 +203,9 @@ class MaxOutFunctor<platform::CUDADeviceContext, T> {
```
We get computing handle from a concrete DeviceContext, and make compution on tensors.
We first obtain the computing handle from a concrete DeviceContext and then compute on tensors.
The implemention of `OpKernel` is similar to math functors, the extra thing we need to do is to register the OpKernel in a global map.
The implementation of `OpKernel` is similar to math functors, the extra thing we need to do is to register the OpKernel in a global map.
Fluid provides different register interfaces in op_registry.h
@ -231,7 +231,7 @@ REGISTER_OP_CUDA_KERNEL(
## Advanced topics: How to switch between different Device/Library
Generally, we will impelement OpKernel for all Device/Library of an Operator. We can easily train a Convolutional Neural Network in GPU. However, some OpKernel is not sutibale on a specific Device. For example, crf operator can only run on CPU, whereas most other operators can run at GPU. To achieve high performance in such circumstance, we have to switch between different Device/Library.
Generally, we will implement OpKernel for all Device/Library of an Operator. We can easily train a Convolutional Neural Network in GPU. However, some OpKernel is not suitable on a specific Device. For example, crf operator can only run on CPU, whereas most other operators can run on GPU. To achieve high performance in such circumstance, we have to switch between different Device/Library.
For more details, please refer to following docs:

@ -115,7 +115,7 @@ PaddlePaddle的编译选项包括生成CPU/GPU二进制文件、链接何种B
"WITH_AVX", "是否编译含有AVX指令集的PaddlePaddle二进制文件", "ON"
"WITH_PYTHON", "是否内嵌PYTHON解释器", "ON"
"WITH_STYLE_CHECK", "是否编译时进行代码风格检查", "ON"
"WITH_TESTING", "是否开启单元测试", "ON"
"WITH_TESTING", "是否开启单元测试", "OFF"
"WITH_DOC", "是否编译中英文文档", "OFF"
"WITH_SWIG_PY", "是否编译PYTHON的SWIG接口该接口可用于预测和定制化训练", "Auto"
"WITH_GOLANG", "是否编译go语言的可容错parameter server", "ON"

@ -126,7 +126,7 @@ You can add :code:`-D` argument to pass such options, like:
"WITH_AVX", "Build with AVX support", "ON"
"WITH_PYTHON", "Build with integrated Python interpreter", "ON"
"WITH_STYLE_CHECK", "Check code style when building", "ON"
"WITH_TESTING", "Build unit tests", "ON"
"WITH_TESTING", "Build unit tests", "OFF"
"WITH_DOC", "Build documentations", "OFF"
"WITH_SWIG_PY", "Build Python SWIG interface for V2 API", "Auto"
"WITH_GOLANG", "Build fault-tolerant parameter server written in go", "ON"

@ -95,6 +95,12 @@ PaddlePaddle Book是为用户和开发者制作的一个交互式的Jupyter Note
docker run -p 8888:8888 paddlepaddle/book
国内用户可以使用下面的镜像源来加速访问:
.. code-block: bash
docker run -p 8888:8888 docker.paddlepaddlehub.com/book
然后在浏览器中输入以下网址:
.. code-block:: text

@ -102,6 +102,12 @@ We provide a packaged book image, simply issue the command:
docker run -p 8888:8888 paddlepaddle/book
For users in China, we provide a faster mirror:
.. code-block: bash
docker run -p 8888:8888 docker.paddlepaddlehub.com/book
Then, you would back and paste the address into the local browser:
.. code-block:: text

@ -92,11 +92,11 @@ paddle.init(
参数说明
- use_gpu **可选默认False**是否启用GPU训练
- trainer_count**必选默认1**,当前训练任务trainer总个数
- trainer_count**必选默认1**,当前trainer的线程数目
- port**必选默认7164**连接到pserver的端口
- ports_num**必选默认1**连接到pserver的端口个数
- ports_num_for_sparse**必选默认0**和pserver之间用于稀疏类型参数通信的端口个数
- num_gradient_servers**必选默认1**,当前训练任务pserver总数
- num_gradient_servers**必选默认1**,当前训练任务trainer总数
- trainer_id**必选默认0**每个trainer的唯一ID从0开始的整数
- pservers**必选默认127.0.0.1**当前训练任务启动的pserver的IP列表多个IP使用“,”隔开

@ -95,11 +95,11 @@ paddle.init(
Parameter Description
- use_gpu: **optional, default False**, set to "True" to enable GPU training.
- trainer_count: **required, default 1**, total count of trainers in the training job.
- trainer_count: **required, default 1**, number of threads in current trainer.
- port: **required, default 7164**, port to connect to parameter server.
- ports_num: **required, default 1**, number of ports for communication.
- ports_num_for_sparse: **required, default 0**, number of ports for sparse type caculation.
- num_gradient_servers: **required, default 1**, total number of gradient server.
- num_gradient_servers: **required, default 1**, number of trainers in current job.
- trainer_id: **required, default 0**, ID for every trainer, start from 0.
- pservers: **required, default 127.0.0.1**, list of IPs of parameter servers, separated by ",".

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