名称 最后提交 最后更新
..
contrib [cherry-pick] clean redundant API alias in 2.0 - part 1 #29928 (#29960)
dataloader Fix doc format for callbacks, metrics and Model (#28638)
distributed Upgrade string literals to raw string (#28989)
dygraph add the paddle.distributed.split api (#29970) (#30041)
incubate cherry pick heter ps (#29955)
inference Refine python inference api (#26958)
layers cherry pick heter ps (#29955)
tests add the paddle.distributed.split api (#29970) (#30041)
transpiler Integrated Trainer of Parameter Server (API add `fluid.contrib.layers.sparse_embedding` only) (#22957)
.gitignore Fix CI and enhance gitignore
__init__.py 2 0 ps core 2 (#29894)
average.py add "import paddle.fluid as fluid" to examples lack of it
backward.py 2 0 ps core 2 (#29894)
clip.py Upgrade string literals to raw string (#28989)
communicator.py 2 0 ps core 2 (#29894)
compiler.py [Kunlun] 2.0 cherry-pick:Support for Baidu Kunlun XPU multi card training (#29713)
core.py Support type promote for basic math ops (quantum required) (#29265) (#29354)
data.py Add static mode check on data() (#27495)
data_feed_desc.py English API Docs Optimization Part 1 (#24536)
data_feeder.py add complex64 and complex128 type; add +-*/@ and slice opreator for c… (#29199)
dataset.py add set_trainer_num api in dataset (#29133)
debugger.py fix typo words (#22653)
default_scope_funcs.py Add print_function for all python files
device_worker.py enable pipeline to run with Executor.run() (#28373)
distribute_lookup_table.py add doc string for downpour.py and distribute_lookup_table.py
dygraph_utils.py
entry_attr.py
evaluator.py
executor.py
framework.py
generator.py
graphviz.py
initializer.py
input.py
install_check.py
io.py
layer_helper.py
layer_helper_base.py
lod_tensor.py
log_helper.py
metrics.py
multiprocess_utils.py
net_drawer.py
nets.py
op.py
optimizer.py
parallel_executor.py
param_attr.py
profiler.py
reader.py
regularizer.py
trainer_desc.py
trainer_factory.py
unique_name.py
wrapped_decorator.py

项目简介

PArallel Distributed Deep LEarning: Machine Learning Framework from Industrial Practice (『飞桨』核心框架,深度学习&机器学习高性能单机、分布式训练和跨平台部署)

:rocket: Github 镜像仓库 :rocket:

源项目地址 :arrow_down: :arrow_down: :arrow_down:

https://github.com/paddlepaddle/paddle

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贡献者 233

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开发语言

  • C++ 47.1 %
  • Python 43.6 %
  • Cuda 7.0 %
  • CMake 1.1 %
  • Shell 0.7 %
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