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体验新版 GitCode,发现更多精彩内容 >>
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c4b28f47
编写于
5月 02, 2017
作者:
Y
Yu Yang
提交者:
GitHub
5月 02, 2017
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差异文件
Merge pull request #1957 from wangkuiyi/polish-release-note
Polish release notes
上级
c3e23a99
99687e38
变更
2
隐藏空白更改
内联
并排
Showing
2 changed file
with
80 addition
and
48 deletion
+80
-48
.pre-commit-config.yaml
.pre-commit-config.yaml
+4
-4
RELEASE.md
RELEASE.md
+76
-44
未找到文件。
.pre-commit-config.yaml
浏览文件 @
c4b28f47
-
repo
:
https://github.com/Lucas-C/pre-commit-hooks.git
sha
:
c25201a00e6b0514370501050cf2a8538ac12270
sha
:
v1.0.1
hooks
:
-
id
:
remove-crlf
files
:
(?!.*third_party)^.*$ | (?!.*book)^.*$
-
repo
:
https://github.com/reyoung/mirrors-yapf.git
sha
:
v0.13.2
hooks
:
-
id
:
yapf
files
:
(.*\.(py|bzl)|BUILD|.*\.BUILD|WORKSPACE)$
-
id
:
yapf
files
:
(.*\.(py|bzl)|BUILD|.*\.BUILD|WORKSPACE)$
-
repo
:
https://github.com/pre-commit/pre-commit-hooks
sha
:
7539d8bd1a00a3c1bfd34cdb606d3a6372e83469
sha
:
5bf6c09bfa1297d3692cadd621ef95f1284e33c0
hooks
:
-
id
:
check-added-large-files
-
id
:
check-merge-conflict
...
...
RELEASE.md
浏览文件 @
c4b28f47
# Release v0.10.0
We are glad to release version 0.10.0. In this version, we are happy to
release the
new
[
Python API
](
http://research.baidu.com/paddlepaddles-new-api-simplifies-deep-learning-programs/
)
.
-
Our old Python API is kind of out of date. It's hard to learn and hard to
use. To write a PaddlePaddle program using the old API, we'd have to write
at least two Python files: one
`data provider`
and another one that defines
the network topology. Users start a PaddlePaddle job by running the
`paddle_trainer`
C++ program, which calls Python interpreter to run the
network topology configuration script and then start the training loop,
which iteratively calls the data provider function to load minibatches.
This prevents us from writing a Python program in a modern way, e.g., in the
Jupyter Notebook.
-
The new API, which we often refer to as the
*v2 API*
, allows us to write
much shorter Python programs to define the network and the data in a single
.py file. Also, this program can run in Jupyter Notebook, since the entry
point is in Python program and PaddlePaddle runs as a shared library loaded
and invoked by this Python program.
Basing on the new API, we delivered an online interative
book,
[
Deep Learning 101
](
http://book.paddlepaddle.org/index.en.html
)
and
[
its Chinese version
](
http://book.paddlepaddle.org/
)
.
We also worked on updating our online documentation to describe the new API.
But this is an ongoing work. We will release more documentation improvements
in the next version.
We also worked on bring the new API to distributed model training (via MPI and
Kubernetes). This work is ongoing. We will release more about it in the next
version.
## New Features
*
We release
[
new
p
ython API
](
http://research.baidu.com/paddlepaddles-new-api-simplifies-deep-learning-programs/
)
.
*
We release
[
new
P
ython API
](
http://research.baidu.com/paddlepaddles-new-api-simplifies-deep-learning-programs/
)
.
*
Deep Learning 101 book in
[
English
](
http://book.paddlepaddle.org/index.en.html
)
and
[
Chinese
](
http://book.paddlepaddle.org/
)
.
*
Support rectangle input for CNN.
*
Support stride pooling for seqlastin and seqfirstin.
*
Expose seq_concat_layer/seq_reshape_layer in
`trainer_config_helpers`
.
*
Add dataset package
-
CIFAR, MNIST, IMDB, WMT14, CONLL05, movielens, imikolov.
*
Expose
`seq_concat_layer/seq_reshape_layer`
in
`trainer_config_helpers`
.
*
Add dataset package: CIFAR, MNIST, IMDB, WMT14, CONLL05, movielens, imikolov.
*
Add Priorbox layer for Single Shot Multibox Detection.
*
Add smooth L1 cost.
*
Add data reader creator and data reader decorator for v2 API.
*
Add the
cpu implementation of cmrnorm-
projection.
*
Add the
CPU implementation of cmrnorm
projection.
## Improvements
*
Support
python virtualenv for
`paddle_trainer`
process
.
*
Support
Python virtualenv for
`paddle_trainer`
.
*
Add pre-commit hooks, used for automatically format our code.
*
U
se Protobuf 3.X as the default Paddle Protobuf version
.
*
Add an option to check data type in
p
ython data provider.
*
U
pgrade protobuf to version 3.x
.
*
Add an option to check data type in
P
ython data provider.
*
Speedup the backward of average layer on GPU.
*
Reorganize the catalog of doc/ and refine several docs
.
*
Add Travis-CI for checking dead links
.
*
Add a example for explaining
sparse_vector
.
*
Add Re
lu
in layer_math.py
*
Simplify data processing flow for
quick s
tart.
*
Documentation refinement
.
*
Check dead links in documents using Travis-CI
.
*
Add a example for explaining
`sparse_vector`
.
*
Add Re
LU
in layer_math.py
*
Simplify data processing flow for
Quick S
tart.
*
Support CUDNN Deconv.
*
Add data feeder
for
v2 API.
*
Add data feeder
in
v2 API.
*
Support predicting the samples from sys.stdin for sentiment demo.
*
Provide multi-proccess interface for image preprocessing.
*
Add benchmark document for v1 API.
*
Add Re
lu in layer_math.py
.
*
Add Re
LU in
`layer_math.py`
.
*
Add packages for automatically downloading public datasets.
*
Rename
Argument::sumCost to Argument::sum since Argument does not have to have any relationship
with cost.
*
Expose Argument::sum to Python
*
Rename
`Argument::sumCost`
to
`Argument::sum`
since class
`Argument`
is nothing
with cost.
*
Expose Argument::sum to Python
*
Add a new
`TensorExpression`
implementation for matrix-related expression evaluations.
*
Add
Lazy Assignment for optimize the calculation
of multiple expressions.
*
Add
`Function`
to reconstruct the computation function.
*
PadFunc and PadGradFunc
.
*
ContextProjectionForwardFunc and ContextProjectionBackwardFunc
.
*
CosSimBackward and CosSimBackwardFunc
.
*
CrossMapNormalFunc and CrossMapNormalGradFunc
.
*
MulFunc
.
*
Add
`AutoCompare`
and
`FunctionCompare`
, which make it easier to write unittest
for comparing gpu and cpu version of a function.
*
Add
`libpaddle_test_main.a`
and remove the main function inside the test file.
*
Add
lazy assignment for optimizing the calculation of a batch
of multiple expressions.
*
Add
abstract calss
`Function`
and its implementation:
*
`PadFunc`
and
`PadGradFunc`
.
*
`ContextProjectionForwardFunc`
and
`ContextProjectionBackwardFunc`
.
*
`CosSimBackward`
and
`CosSimBackwardFunc`
.
*
`CrossMapNormalFunc`
and
`CrossMapNormalGradFunc`
.
*
`MulFunc`
.
*
Add
class
`AutoCompare`
and
`FunctionCompare`
, which make it easier to write unit tests
for comparing gpu and cpu version of a function.
*
Generate
`libpaddle_test_main.a`
and remove the main function inside the test file.
*
Support dense numpy vector in PyDataProvider2.
*
Clean code base, remove some copy
& paste codes before.
*
Extract
RowBuffer class for SparseRowMatrix
.
*
Clean
GradientMachine's interface
.
*
Try u
se
`override`
keyword in layer.
*
Simplify
Evaluator::create, use
`ClassRegister`
to create Evaluator
.
*
Add md5 check
when downloading demo's dataset.
*
Clean code base, remove some copy
-n-pasted code snippets:
*
Extract
`RowBuffer`
class for
`SparseRowMatrix`
.
*
Clean
the interface of
`GradientMachine`
.
*
U
se
`override`
keyword in layer.
*
Simplify
`Evaluator::create`
, use
`ClassRegister`
to create
`Evaluator`
s
.
*
Check MD5 checksum
when downloading demo's dataset.
*
Add
`paddle::Error`
which intentially replace
`LOG(FATAL)`
in Paddle.
## Bug Fixes
*
Add layer check for recurrent_group
.
*
Clang-format off on some cuda .cc
files.
*
Fix
LogActivation which is not defined
.
*
Fix
bug when run test_layerHelpers
multiple times.
*
Fix
protobuf size limit on seq2seq demo
.
*
Fix
bug for
dataprovider converter in GPU mode.
*
Fix
bug in GatedRecurrentLayer which only occurs in predicting or
`job=test`
mode
.
*
Fix bug for
BatchNorm when testing more than models in test mode
.
*
Fix unit test of paramRelu.
*
Fix some
warning about CpuSparseMatrix
.
*
Fix
MultiGradientMachine error if trainer_count > batch_size
.
*
Fix
when async load data in PyDataProvider2
.
*
Check layer input types for
`recurrent_group`
.
*
Don't run
`clang-format`
with .cu source
files.
*
Fix
bugs with
`LogActivation`
.
*
Fix
the bug that runs
`test_layerHelpers`
multiple times.
*
Fix
the bug that the seq2seq demo exceeds protobuf message size limit
.
*
Fix
the bug in
dataprovider converter in GPU mode.
*
Fix
a bug in
`GatedRecurrentLayer`
.
*
Fix bug for
`BatchNorm`
when testing more than one models
.
*
Fix
broken
unit test of paramRelu.
*
Fix some
compile-time warnings about
`CpuSparseMatrix`
.
*
Fix
`MultiGradientMachine`
error when
`trainer_count > batch_size`
.
*
Fix
bugs that prevents from asynchronous data loading in
`PyDataProvider2`
.
# Release v0.9.0
...
...
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