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self.forward() -> self() #1211
self.forward() -> self() #1211
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Codecov Report
@@ Coverage Diff @@
## master #1211 +/- ##
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Coverage 91% 91%
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Files 61 61
Lines 3153 3153
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Hits 2879 2879
Misses 274 274 |
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LFTM 🚀
@jeremyjordan what about the TPU issue? |
This pull request is now in conflict... :( |
can’t edit the title on mobile but this is WIP until TPU issue is resolved |
@williamFalcon can you share more details about the TPU issue you ran into? i tried running the lightning_mnist_tpu notebook with this branch (and changing https://colab.research.google.com/drive/1CtGZs06fDUmNES4PsguTFZw5VbHnt8-k |
This pull request is now in conflict... :( |
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LGTM :)
Great job! =) |
Great job! =) |
2 similar comments
Great job! =) |
Great job! =) |
Great job! =) |
@Borda any idea what's up with the mergify bot? |
Great job! =) |
@jeremyjordan we have there the following rule:
looking to the master, it seems that there is some conflict with rebasing
see here it worked properly #1251 (comment) |
* Example: Simple RL example using DQN/Lightning * DQN RL Agent using Lightning * Uses Iterable Dataset for Replay Buffer * Buffer is populated by agent as training is carried out, updating the dataset * Applied autopep8 fixes * * Updated line length from 120 to 110 * Update pl_examples/domain_templates/dqn.py simplify get_device method Co-Authored-By: Jirka Borovec <Borda@users.noreply.github.com> * Update pl_examples/domain_templates/dqn.py Re-ordered imports Co-Authored-By: Jirka Borovec <Borda@users.noreply.github.com> * CI: split tests-examples (#990) * CI: split tests-examples * tests without template * comment depends * CircleCI typo * add doctest * update test req. * CI tests * setup macOS * longer train * lover pred acc * fix model * rename default model * lower tests acc * typo * imports * fix test optimizer * update calls * fix Win * lower Drone image * fix call * pytorch image * fix test * add dev image * add dev image * update image * drone volume * lint * update test notes * rename tests/models >> tests/base * group models * conftest * optim imports * typos * fix import * fix tests * install AMP * tests * fix import * Clean up * added module docstring * renamed variables to be more descriptive * Added missing docstrings and type annotations * Added gym to example requirements * Added note to changelog * updated example image * update types * rename script * Update CHANGELOG.md Co-Authored-By: Jirka Borovec <Borda@users.noreply.github.com> * another rename * Disable validation when val_percent_check=0 (#1251) * fix disable validation * add test * update changelog * update docs for val_percent_check * make "fast training" docs consistent * calling self.forward() -> self() (#1211) * self.forward() -> self() * update changelog Co-authored-by: Jirka Borovec <Borda@users.noreply.github.com> * Fix requirements-extra.txt Trains package to release version (#1229) * Fix requirement-extra use released Trains package * Update README.md add Trains and links to the external Visualization section Co-authored-by: Jirka Borovec <Borda@users.noreply.github.com> * Remove unnecessary parameters to super() in documentation and source code (#1240) Co-authored-by: Jirka Borovec <Borda@users.noreply.github.com> * update deprecation warning (#1258) * update docs for progress bat values (#1253) * lower timeouts for inactive issues (#1250) * update contrib list (#1241) Co-authored-by: William Falcon <waf2107@columbia.edu> * Fix outdated docs (#1227) * Fix typo (#1224) * drop unused Tox (#1242) * system info (#1234) * system info * update big info * test script * update config * rename script * import path * Changed smoothing in tqdm to decrease variability of time remaining between training / eval (#1194) * Example: Simple RL example using DQN/Lightning * DQN RL Agent using Lightning * Uses Iterable Dataset for Replay Buffer * Buffer is populated by agent as training is carried out, updating the dataset * Applied autopep8 fixes * * Updated line length from 120 to 110 * Update pl_examples/domain_templates/dqn.py simplify get_device method Co-Authored-By: Jirka Borovec <Borda@users.noreply.github.com> * Update pl_examples/domain_templates/dqn.py Re-ordered imports Co-Authored-By: Jirka Borovec <Borda@users.noreply.github.com> * Clean up * added module docstring * renamed variables to be more descriptive * Added missing docstrings and type annotations * Added gym to example requirements * Added note to changelog * update types * rename script * Update CHANGELOG.md Co-Authored-By: Jirka Borovec <Borda@users.noreply.github.com> * another rename Co-authored-by: Donal Byrne <Donal.Byrne@xperi.com> Co-authored-by: Jirka Borovec <Borda@users.noreply.github.com> Co-authored-by: William Falcon <waf2107@columbia.edu> Co-authored-by: Adrian Wälchli <adrian.waelchli@students.unibe.ch> Co-authored-by: Jeremy Jordan <13970565+jeremyjordan@users.noreply.github.com> Co-authored-by: Martin.B <51887611+bmartinn@users.noreply.github.com> Co-authored-by: Tyler Yep <tyep@stanford.edu> Co-authored-by: Shunta Komatsu <59395084+skmatz@users.noreply.github.com> Co-authored-by: Jack Pertschuk <jackpertschuk@gmail.com>
* self.forward() -> self() * update changelog Co-authored-by: Jirka Borovec <Borda@users.noreply.github.com>
* Example: Simple RL example using DQN/Lightning * DQN RL Agent using Lightning * Uses Iterable Dataset for Replay Buffer * Buffer is populated by agent as training is carried out, updating the dataset * Applied autopep8 fixes * * Updated line length from 120 to 110 * Update pl_examples/domain_templates/dqn.py simplify get_device method Co-Authored-By: Jirka Borovec <Borda@users.noreply.github.com> * Update pl_examples/domain_templates/dqn.py Re-ordered imports Co-Authored-By: Jirka Borovec <Borda@users.noreply.github.com> * CI: split tests-examples (Lightning-AI#990) * CI: split tests-examples * tests without template * comment depends * CircleCI typo * add doctest * update test req. * CI tests * setup macOS * longer train * lover pred acc * fix model * rename default model * lower tests acc * typo * imports * fix test optimizer * update calls * fix Win * lower Drone image * fix call * pytorch image * fix test * add dev image * add dev image * update image * drone volume * lint * update test notes * rename tests/models >> tests/base * group models * conftest * optim imports * typos * fix import * fix tests * install AMP * tests * fix import * Clean up * added module docstring * renamed variables to be more descriptive * Added missing docstrings and type annotations * Added gym to example requirements * Added note to changelog * updated example image * update types * rename script * Update CHANGELOG.md Co-Authored-By: Jirka Borovec <Borda@users.noreply.github.com> * another rename * Disable validation when val_percent_check=0 (Lightning-AI#1251) * fix disable validation * add test * update changelog * update docs for val_percent_check * make "fast training" docs consistent * calling self.forward() -> self() (Lightning-AI#1211) * self.forward() -> self() * update changelog Co-authored-by: Jirka Borovec <Borda@users.noreply.github.com> * Fix requirements-extra.txt Trains package to release version (Lightning-AI#1229) * Fix requirement-extra use released Trains package * Update README.md add Trains and links to the external Visualization section Co-authored-by: Jirka Borovec <Borda@users.noreply.github.com> * Remove unnecessary parameters to super() in documentation and source code (Lightning-AI#1240) Co-authored-by: Jirka Borovec <Borda@users.noreply.github.com> * update deprecation warning (Lightning-AI#1258) * update docs for progress bat values (Lightning-AI#1253) * lower timeouts for inactive issues (Lightning-AI#1250) * update contrib list (Lightning-AI#1241) Co-authored-by: William Falcon <waf2107@columbia.edu> * Fix outdated docs (Lightning-AI#1227) * Fix typo (Lightning-AI#1224) * drop unused Tox (Lightning-AI#1242) * system info (Lightning-AI#1234) * system info * update big info * test script * update config * rename script * import path * Changed smoothing in tqdm to decrease variability of time remaining between training / eval (Lightning-AI#1194) * Example: Simple RL example using DQN/Lightning * DQN RL Agent using Lightning * Uses Iterable Dataset for Replay Buffer * Buffer is populated by agent as training is carried out, updating the dataset * Applied autopep8 fixes * * Updated line length from 120 to 110 * Update pl_examples/domain_templates/dqn.py simplify get_device method Co-Authored-By: Jirka Borovec <Borda@users.noreply.github.com> * Update pl_examples/domain_templates/dqn.py Re-ordered imports Co-Authored-By: Jirka Borovec <Borda@users.noreply.github.com> * Clean up * added module docstring * renamed variables to be more descriptive * Added missing docstrings and type annotations * Added gym to example requirements * Added note to changelog * update types * rename script * Update CHANGELOG.md Co-Authored-By: Jirka Borovec <Borda@users.noreply.github.com> * another rename Co-authored-by: Donal Byrne <Donal.Byrne@xperi.com> Co-authored-by: Jirka Borovec <Borda@users.noreply.github.com> Co-authored-by: William Falcon <waf2107@columbia.edu> Co-authored-by: Adrian Wälchli <adrian.waelchli@students.unibe.ch> Co-authored-by: Jeremy Jordan <13970565+jeremyjordan@users.noreply.github.com> Co-authored-by: Martin.B <51887611+bmartinn@users.noreply.github.com> Co-authored-by: Tyler Yep <tyep@stanford.edu> Co-authored-by: Shunta Komatsu <59395084+skmatz@users.noreply.github.com> Co-authored-by: Jack Pertschuk <jackpertschuk@gmail.com>
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What does this PR do?
Fixes #1209
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