A Configurable Recommender Systems Simulation Platform
Caffe2 is a lightweight, modular, and scalable deep learning framework.
Python package built to ease deep learning on graph, on top of existing DL frameworks.
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kittipatv/emacs-ipython-notebook 0
Jupyter notebook client in Emacs
EOS Governance
A distributed, fast open-source graph database featuring horizontal scalability and high availability
A GraphQL to Cypher query execution layer for Neo4j and JavaScript GraphQL implementations.
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pull request commentfacebookresearch/ReAgent
Hi @alexnikulkov, I created this PR on February 7, at that time this fix was not there.
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pull request commentfacebookresearch/ReAgent
@MisterTea merged this pull request in facebookresearch/ReAgent@fd387a55d637fb4f0b16d39a47324ef64f9b3a1e.
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commit sha fd387a55d637fb4f0b16d39a47324ef64f9b3a1e
Fix discrete samplers (#393) Summary: fix bugs: GreedyActionSampler returned one as a log prob and EpsilonGreedyActionSampler didn't work. Pull Request resolved: https://github.com/facebookresearch/ReAgent/pull/393 Test Plan: Imported from GitHub, without a `Test Plan:` line. ...but without running open source tests. Reviewed By: kaiwenw Differential Revision: D27842450 Pulled By: MisterTea fbshipit-source-id: 9b4aa85f352f2d7565473127b280d61bcc6d3b71
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PR closed facebookresearch/ReAgent
fix bugs: GreedyActionSampler returned one as a log prob and EpsilonGreedyActionSampler didn't work.
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pull request commentfacebookresearch/ReAgent
Make sure that trainer.train(batch) throws an error for Lightining trainers
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commit sha d507a5703331e728d2dc7a2d90ba262e1554c54a
Make sure that trainer.train(batch) throws an error for Lightining trainers (#457) Summary: Pull Request resolved: https://github.com/facebookresearch/ReAgent/pull/457 trainer.train(batch) was the old, pre-Lightning ReAgent trainer API. With this diff we make sure that nobody is trying to call trainer.train(batch). trainer.train() or trainer.train(True/False) is allowed - this puts the network into training/eval mode. Reviewed By: MisterTea Differential Revision: D27862583 fbshipit-source-id: b0875e11cd4ef214c75fd1bef5b696f1cdf2b8d6
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PR closed facebookresearch/ReAgent
Summary: trainer.train(batch) was the old, pre-Lightning ReAgent trainer API. With this diff we make sure that nobody is trying to call trainer.train(batch). trainer.train() or trainer.train(True/False) is allowed - this puts the network into training/eval mode.
Reviewed By: MisterTea
Differential Revision: D27862583
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pull request commentfacebookresearch/ReAgent
This pull request was exported from Phabricator. Differential Revision: D27842449
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pull request commentfacebookresearch/ReAgent
move use_gpu out of model manager
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pull request commentfacebookresearch/ReAgent
Hi @wall-ed-coder are you on master branch? We fixed the bug with the order of arguments in full_like() 2 months ago: https://github.com/facebookresearch/ReAgent/commit/5fd724322cd51bf268fa1e17263d66f74083356d
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pull request commentfacebookresearch/ReAgent
This pull request was exported from Phabricator. Differential Revision: D27842449
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pull request commentfacebookresearch/ReAgent
Make sure that trainer.train(batch) throws an error for Lightining trainers
This pull request was exported from Phabricator. Differential Revision: D27862583
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PR opened facebookresearch/ReAgent
Summary: trainer.train(batch) was the old, pre-Lightning ReAgent trainer API. With this diff we make sure that nobody is trying to call trainer.train(batch). trainer.train() or trainer.train(True/False) is allowed - this puts the network into training/eval mode.
Reviewed By: MisterTea
Differential Revision: D27862583
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issue openedfacebookresearch/ReAgent
Hi,
I have been reading through the code and I have a few questions regarding the CPE functionality.
In particular, with the DQN model you have separate Q-networks, both normal and target, dedicated just for CPE that I would like to better understand. At present their purpose is not really clear to me. In particular, what is the purpose of these additional networks over and above the standard Q-networks of the DQN model?
In the function _calculate_cpes, which is part of the RLTrainer class. Reading this function it seems that update the networks q_network_cpe and q_network_cpe_target to model not only the reward, but any additional metrics that could be on interest in CPE.
Am I right in thinking that performing CPE on these additional metrics is the main reason for these additional networks? Put another way, if one were only interested in performing CPE on the reward itself, would using the standard Q-networks of the DQN model suffice?
Thanks
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pull request commentfacebookresearch/ReAgent
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issue commentfacebookresearch/ReAgent
Sorry, maybe I am missing something, but don't we also have non-python dependencies. For example, I thought part of the project uses Spark.
From the error message above it was my impression that the error was coming from the spark pipeline to pre-process the data. Did I misunderstand something?
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pull request commentfacebookresearch/ReAgent
This pull request was exported from Phabricator. Differential Revision: D27842449
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pull request commentfacebookresearch/ReAgent
This pull request was exported from Phabricator. Differential Revision: D27842449
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pull request commentfacebookresearch/ReAgent
Update the ExprTk library commit
@MisterTea merged this pull request in facebookresearch/ReAgent@6c551e938f04f53c6436b700914f6212f26cccea.
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commit sha 6c551e938f04f53c6436b700914f6212f26cccea
Update the ExprTk library commit (#384) Summary: Pull Request resolved: https://github.com/facebookresearch/ReAgent/pull/384 Test Plan: CI Tests ...but without running open source tests. Reviewed By: gji1 Differential Revision: D27842452 Pulled By: MisterTea fbshipit-source-id: 6fb192d30217d358e86a04e6bcc5a69911276e71
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PR closed facebookresearch/ReAgent
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commit sha edc1c24f25d0212495b241613263362006d38cdb
Remove some pyre fixmes Reviewed By: divchenko Differential Revision: D27835360 fbshipit-source-id: cbb23793ee57382e43bd65bd40cfeb2820c6eec2
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pull request commentfacebookresearch/ReAgent
inc. training time for sparse dqn test
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commit sha 470f86032cdfa6b96899c85b9cfefc110cab9ee4
inc. training time for sparse dqn test (#454) Summary: Pull Request resolved: https://github.com/facebookresearch/ReAgent/pull/454 title Reviewed By: alexnikulkov Differential Revision: D27800185 fbshipit-source-id: 406001b48f55d7304d18e06237e7bf82ed07c11b
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PR closed facebookresearch/ReAgent
Summary: title
Differential Revision: D27800185
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pull request commentfacebookresearch/ReAgent
Update the ExprTk library commit
Thank you for signing our Contributor License Agreement. We can now accept your code for this (and any) Facebook open source project. Thanks!
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pull request commentfacebookresearch/ReAgent
Update the ExprTk library commit
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pull request commentfacebookresearch/ReAgent
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