Pytorch starter code for UC Berkeley's cs285 assignments

mdeib, updated 🕥 2022-01-21 20:42:37

UC Berkeley Deep RL in Pytorch

Pytorch starter code for UC Berkeley's CS285 Deep RL course. The code is meant to be used as a direct alternative to the official HW repository for those who would rather complete the course assignments in pytorch. Solutions to this starter code is available.

Changes

All tensorflow in the starter code was converted to pytorch and or numpy, and all solutions are to be written in pytorch. Overall structure of the HW starter code was kept mostly the same, although with the move to pytorch it made sense to delete some files and move thier contents elsewhere. The README.txt in each HW folder has been modified where necessary but the pdf has not - refer to the README.txt for any changes made in the pytorch version. Although tensorflow is not needed within the main code, the logging is still done with tensorboard and thus tensorflow is still needed to easily use and view tensorboard in your browser.

Please note that while this starter code has been shown to produce reasonable results when filled in correctly there may still exist small bugs/errors.

Issues

Bump ipython from 6.4.0 to 7.16.3 in /hw2

opened on 2022-01-21 20:42:36 by dependabot[bot]

Bumps ipython from 6.4.0 to 7.16.3.

Commits


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Bump ipython from 6.4.0 to 7.16.3 in /hw3

opened on 2022-01-21 20:33:08 by dependabot[bot]

Bumps ipython from 6.4.0 to 7.16.3.

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You can trigger Dependabot actions by commenting on this PR: - `@dependabot rebase` will rebase this PR - `@dependabot recreate` will recreate this PR, overwriting any edits that have been made to it - `@dependabot merge` will merge this PR after your CI passes on it - `@dependabot squash and merge` will squash and merge this PR after your CI passes on it - `@dependabot cancel merge` will cancel a previously requested merge and block automerging - `@dependabot reopen` will reopen this PR if it is closed - `@dependabot close` will close this PR and stop Dependabot recreating it. You can achieve the same result by closing it manually - `@dependabot ignore this major version` will close this PR and stop Dependabot creating any more for this major version (unless you reopen the PR or upgrade to it yourself) - `@dependabot ignore this minor version` will close this PR and stop Dependabot creating any more for this minor version (unless you reopen the PR or upgrade to it yourself) - `@dependabot ignore this dependency` will close this PR and stop Dependabot creating any more for this dependency (unless you reopen the PR or upgrade to it yourself) - `@dependabot use these labels` will set the current labels as the default for future PRs for this repo and language - `@dependabot use these reviewers` will set the current reviewers as the default for future PRs for this repo and language - `@dependabot use these assignees` will set the current assignees as the default for future PRs for this repo and language - `@dependabot use this milestone` will set the current milestone as the default for future PRs for this repo and language You can disable automated security fix PRs for this repo from the [Security Alerts page](https://github.com/mdeib/berkeley-deep-RL-pytorch-starter/network/alerts).

Bump ipython from 6.4.0 to 7.16.3 in /hw1

opened on 2022-01-21 20:29:49 by dependabot[bot]

Bumps ipython from 6.4.0 to 7.16.3.

Commits


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Dependabot will resolve any conflicts with this PR as long as you don't alter it yourself. You can also trigger a rebase manually by commenting @dependabot rebase.

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You can trigger Dependabot actions by commenting on this PR: - `@dependabot rebase` will rebase this PR - `@dependabot recreate` will recreate this PR, overwriting any edits that have been made to it - `@dependabot merge` will merge this PR after your CI passes on it - `@dependabot squash and merge` will squash and merge this PR after your CI passes on it - `@dependabot cancel merge` will cancel a previously requested merge and block automerging - `@dependabot reopen` will reopen this PR if it is closed - `@dependabot close` will close this PR and stop Dependabot recreating it. You can achieve the same result by closing it manually - `@dependabot ignore this major version` will close this PR and stop Dependabot creating any more for this major version (unless you reopen the PR or upgrade to it yourself) - `@dependabot ignore this minor version` will close this PR and stop Dependabot creating any more for this minor version (unless you reopen the PR or upgrade to it yourself) - `@dependabot ignore this dependency` will close this PR and stop Dependabot creating any more for this dependency (unless you reopen the PR or upgrade to it yourself) - `@dependabot use these labels` will set the current labels as the default for future PRs for this repo and language - `@dependabot use these reviewers` will set the current reviewers as the default for future PRs for this repo and language - `@dependabot use these assignees` will set the current assignees as the default for future PRs for this repo and language - `@dependabot use this milestone` will set the current milestone as the default for future PRs for this repo and language You can disable automated security fix PRs for this repo from the [Security Alerts page](https://github.com/mdeib/berkeley-deep-RL-pytorch-starter/network/alerts).
Matt Deible
GitHub Repository

cs285 reinforcement-learning pytorch-rl