From b6122aa265e2f4668c530171b4295b9a18355b34 Mon Sep 17 00:00:00 2001 From: Bo Zhou <2466956298@qq.com> Date: Mon, 26 Aug 2019 15:36:15 +0800 Subject: [PATCH] fix minor problems in the docs (#138) * fix minor probmels in the docs * typo * remove pip source * fix monitor * add performance of A2C * Update README.md * modify logger for GPU detection --- .teamcity/build.sh | 4 ++-- docs/parallel_training/overview.rst | 13 +++++++------ docs/parallel_training/setup.rst | 2 +- examples/A2C/README.md | 11 +++++++---- examples/A2C/learning_curve.png | Bin 0 -> 295391 bytes examples/A2C/result.png | Bin 0 -> 208369 bytes parl/remote/tests/cluster_monitor_3_test.py | 4 ++-- parl/utils/machine_info.py | 4 ++-- 8 files changed, 21 insertions(+), 17 deletions(-) create mode 100644 examples/A2C/learning_curve.png create mode 100644 examples/A2C/result.png diff --git a/.teamcity/build.sh b/.teamcity/build.sh index 1382e68..40029c6 100755 --- a/.teamcity/build.sh +++ b/.teamcity/build.sh @@ -155,8 +155,8 @@ function main() { echo Running tests in $env .. echo `which pip` echo ======================================== - pip install -i https://pypi.tuna.tsinghua.edu.cn/simple . - pip install -i https://pypi.tuna.tsinghua.edu.cn/simple -r .teamcity/requirements.txt + pip install . + pip install -r .teamcity/requirements.txt run_test_with_cpu $env run_test_with_cpu $env "DIS_TESTING_SERIALLY" done diff --git a/docs/parallel_training/overview.rst b/docs/parallel_training/overview.rst index cc5e087..30c553b 100644 --- a/docs/parallel_training/overview.rst +++ b/docs/parallel_training/overview.rst @@ -1,4 +1,4 @@ -Summary +Overview ======= Easy-to-use @@ -22,10 +22,11 @@ Web UI for computation resources to the cluster. Users can view the cluster status at a WEB UI. It shows the detailed information for each worker(e.g, memory used) and each task submitted. -Board compatibility + +Supporting vairous frameworks ################### -| Our framework for distributed training is compatible with any other - frameworks, like tensorflow, pytorch or mxnet. By adding `@parl.remote_class` +| PARL for distributed training is compatible with any other + frameworks, like tensorflow, pytorch and mxnet. By adding `@parl.remote_class` decorator to their codes, users can easily convert their codes to distributed computation. @@ -33,7 +34,7 @@ Why PARL ######## High throughput -############### +------------------------- | PARL uses a point-to-point connection for network communication in the cluster. Unlike other framework like RLlib which replies on redis for communication, PARL is able to achieve much higher throughput. The results @@ -41,7 +42,7 @@ High throughput achieved an increase of 160% on data throughout over Ray(RLlib). Automatic deployment -#################### +------------------------- | Unlike other parallel frameworks which fail to import modules from external file, PARL will automatically package all related files and send them to remote machines. diff --git a/docs/parallel_training/setup.rst b/docs/parallel_training/setup.rst index ce2189d..2caed60 100644 --- a/docs/parallel_training/setup.rst +++ b/docs/parallel_training/setup.rst @@ -61,4 +61,4 @@ Further Reading | Now we know how to set up a cluster and use this cluster by simply adding ``@parl.remote_class``. | In `next_tutorial`_, we will show how this decorator help us implement the **real** multi-thread computation in Python, breaking the limitation of Python Global Interpreter Lock(GIL). -.. _`next_tutorial`: https://parl.readthedocs.io/parallel_training/recommended_practice.html +.. _`next_tutorial`: https://parl.readthedocs.io/en/latest/parallel_training/recommended_practice.html diff --git a/examples/A2C/README.md b/examples/A2C/README.md index 469b353..bb69f56 100755 --- a/examples/A2C/README.md +++ b/examples/A2C/README.md @@ -8,11 +8,14 @@ Please see [here](https://gym.openai.com/envs/#atari) to know more about Atari g ### Benchmark result Mean episode reward in training process after 10 million sample steps. + + +Performance of A2C on various envrionments + +
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