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Bumps [ruff](https://github.com/astral-sh/ruff) from 0.5.4 to 0.9.1. <details> <summary>Release notes</summary> <p><em>Sourced from <a href="https://github.com/astral-sh/ruff/releases">ruff's releases</a>.</em></p> <blockquote> <h2>0.9.1</h2> <h2>Release Notes</h2> <h3>Preview features</h3> <ul> <li>[<code>pycodestyle</code>] Run <code>too-many-newlines-at-end-of-file</code> on each cell in notebooks (<code>W391</code>) (<a href="https://redirect.github.com/astral-sh/ruff/pull/15308">#15308</a>)</li> <li>[<code>ruff</code>] Omit diagnostic for shadowed private function parameters in <code>used-dummy-variable</code> (<code>RUF052</code>) (<a href="https://redirect.github.com/astral-sh/ruff/pull/15376">#15376</a>)</li> </ul> <h3>Rule changes</h3> <ul> <li>[<code>flake8-bugbear</code>] Improve <code>assert-raises-exception</code> message (<code>B017</code>) (<a href="https://redirect.github.com/astral-sh/ruff/pull/15389">#15389</a>)</li> </ul> <h3>Formatter</h3> <ul> <li>Preserve trailing end-of line comments for the last string literal in implicitly concatenated strings (<a href="https://redirect.github.com/astral-sh/ruff/pull/15378">#15378</a>)</li> </ul> <h3>Server</h3> <ul> <li>Fix a bug where the server and client notebooks were out of sync after reordering cells (<a href="https://redirect.github.com/astral-sh/ruff/pull/15398">#15398</a>)</li> </ul> <h3>Bug fixes</h3> <ul> <li>[<code>flake8-pie</code>] Correctly remove wrapping parentheses (<code>PIE800</code>) (<a href="https://redirect.github.com/astral-sh/ruff/pull/15394">#15394</a>)</li> <li>[<code>pyupgrade</code>] Handle comments and multiline expressions correctly (<code>UP037</code>) (<a href="https://redirect.github.com/astral-sh/ruff/pull/15337">#15337</a>)</li> </ul> <h2>Contributors</h2> <ul> <li><a href="https://github.com/AntoineD"><code>@AntoineD</code></a></li> <li><a href="https://github.com/InSyncWithFoo"><code>@InSyncWithFoo</code></a></li> <li><a href="https://github.com/MichaReiser"><code>@MichaReiser</code></a></li> <li><a href="https://github.com/calumy"><code>@calumy</code></a></li> <li><a href="https://github.com/dcreager"><code>@dcreager</code></a></li> <li><a href="https://github.com/dhruvmanila"><code>@dhruvmanila</code></a></li> <li><a href="https://github.com/dylwil3"><code>@dylwil3</code></a></li> <li><a href="https://github.com/sharkdp"><code>@sharkdp</code></a></li> <li><a href="https://github.com/tjkuson"><code>@tjkuson</code></a></li> </ul> <h2>Install ruff 0.9.1</h2> <h3>Install prebuilt binaries via shell script</h3> <pre lang="sh"><code>curl --proto '=https' --tlsv1.2 -LsSf https://github.com/astral-sh/ruff/releases/download/0.9.1/ruff-installer.sh | sh </code></pre> <h3>Install prebuilt binaries via powershell script</h3> <pre lang="sh"><code>powershell -ExecutionPolicy ByPass -c "irm https://github.com/astral-sh/ruff/releases/download/0.9.1/ruff-installer.ps1 | iex" </code></pre> <!-- raw HTML omitted --> </blockquote> <p>... (truncated)</p> </details> <details> <summary>Changelog</summary> <p><em>Sourced from <a href="https://github.com/astral-sh/ruff/blob/main/CHANGELOG.md">ruff's changelog</a>.</em></p> <blockquote> <h2>0.9.1</h2> <h3>Preview features</h3> <ul> <li>[<code>pycodestyle</code>] Run <code>too-many-newlines-at-end-of-file</code> on each cell in notebooks (<code>W391</code>) (<a href="https://redirect.github.com/astral-sh/ruff/pull/15308">#15308</a>)</li> <li>[<code>ruff</code>] Omit diagnostic for shadowed private function parameters in <code>used-dummy-variable</code> (<code>RUF052</code>) (<a href="https://redirect.github.com/astral-sh/ruff/pull/15376">#15376</a>)</li> </ul> <h3>Rule changes</h3> <ul> <li>[<code>flake8-bugbear</code>] Improve <code>assert-raises-exception</code> message (<code>B017</code>) (<a href="https://redirect.github.com/astral-sh/ruff/pull/15389">#15389</a>)</li> </ul> <h3>Formatter</h3> <ul> <li>Preserve trailing end-of line comments for the last string literal in implicitly concatenated strings (<a href="https://redirect.github.com/astral-sh/ruff/pull/15378">#15378</a>)</li> </ul> <h3>Server</h3> <ul> <li>Fix a bug where the server and client notebooks were out of sync after reordering cells (<a href="https://redirect.github.com/astral-sh/ruff/pull/15398">#15398</a>)</li> </ul> <h3>Bug fixes</h3> <ul> <li>[<code>flake8-pie</code>] Correctly remove wrapping parentheses (<code>PIE800</code>) (<a href="https://redirect.github.com/astral-sh/ruff/pull/15394">#15394</a>)</li> <li>[<code>pyupgrade</code>] Handle comments and multiline expressions correctly (<code>UP037</code>) (<a href="https://redirect.github.com/astral-sh/ruff/pull/15337">#15337</a>)</li> </ul> <h2>0.9.0</h2> <p>Check out the <a href="https://astral.sh/blog/ruff-v0.9.0">blog post</a> for a migration guide and overview of the changes!</p> <h3>Breaking changes</h3> <p>Ruff now formats your code according to the 2025 style guide. As a result, your code might now get formatted differently. See the formatter section for a detailed list of changes.</p> <p>This release doesn’t remove or remap any existing stable rules.</p> <h3>Stabilization</h3> <p>The following rules have been stabilized and are no longer in preview:</p> <ul> <li><a href="https://docs.astral.sh/ruff/rules/stdlib-module-shadowing/"><code>stdlib-module-shadowing</code></a> (<code>A005</code>). This rule has also been renamed: previously, it was called <code>builtin-module-shadowing</code>.</li> <li><a href="https://docs.astral.sh/ruff/rules/builtin-lambda-argument-shadowing/"><code>builtin-lambda-argument-shadowing</code></a> (<code>A006</code>)</li> <li><a href="https://docs.astral.sh/ruff/rules/slice-to-remove-prefix-or-suffix/"><code>slice-to-remove-prefix-or-suffix</code></a> (<code>FURB188</code>)</li> <li><a href="https://docs.astral.sh/ruff/rules/boolean-chained-comparison/"><code>boolean-chained-comparison</code></a> (<code>PLR1716</code>)</li> <li><a href="https://docs.astral.sh/ruff/rules/decimal-from-float-literal/"><code>decimal-from-float-literal</code></a> (<code>RUF032</code>)</li> <li><a href="https://docs.astral.sh/ruff/rules/post-init-default/"><code>post-init-default</code></a> (<code>RUF033</code>)</li> <li><a href="https://docs.astral.sh/ruff/rules/useless-if-else/"><code>useless-if-else</code></a> (<code>RUF034</code>)</li> </ul> <p>The following behaviors have been stabilized:</p> <ul> <li><a href="https://docs.astral.sh/ruff/rules/pytest-parametrize-names-wrong-type/"><code>pytest-parametrize-names-wrong-type</code></a> (<code>PT006</code>): Detect <a href="https://docs.pytest.org/en/7.1.x/how-to/parametrize.html#parametrize"><code>pytest.parametrize</code></a> calls outside decorators and calls with keyword arguments.</li> </ul> <!-- raw HTML omitted --> </blockquote> <p>... (truncated)</p> </details> <details> <summary>Commits</summary> <ul> <li><a href=" |
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|---|---|---|
| .. | ||
| experiment.py | ||
| gpt2_model_transform.py | ||
| layer_norm_transform.py | ||
| model_transform.py | ||
| nv_run_pretraining.py | ||
| opset12_model_transform.py | ||
| performance_investigation.py | ||
| pipeline_model_split.py | ||
| README.txt | ||
| single_node_perf.sh | ||
| sqldb_to_tensors.py | ||
| train.py | ||
| watch_experiment.py | ||
Procedure to export NV's pytorch model to ONNX. 1. cd into BERT in DeepLearningExamples and launch the docker. 2. run nv_run_pretraining.py using the same parameter you run run_pretraining.py. It will produce a model in your checkpoint directory. 3. Assume that the exported model's name is 'bert.onnx'. Run model_transform.py bert.onnx 4. Then run layer_norm_transform.py bert_optimized.onnx. The final model name would be bert_optimized_layer_norm.onnx 5. Now, you can run training with the newly created model. Note that if you want to change model's configuration, you can edit bert_config.json in the BERT directory. Example commands: Step 2 (inside docker): python3 /workspace/bert/nv_run_pretraining.py --input_dir=data/bookcorpus/hdf5_shards/ --output_dir=/results/checkpoints1 --config_file=bert_config.json --bert_model=bert-large-uncased --warmup_proportion=0 --num_steps_per_checkpoint=2000 --learning_rate=0.875e-4 --seed=42 --do_train --phase2 --max_seq_length=512 --max_predictions_per_seq=80 --max_steps=200 --train_batch_size=2 Step 3 (inside onnxruntime/build/Linux/RelWithDeb): sudo /data/anaconda/envs/py35/bin/python /bert_ort/wechi/DeepLearningExamples/PyTorch/LanguageModeling/BERT/model_transform.py /bert_ort/wechi/DeepLearningExamples/PyTorch/LanguageModeling/BERT/results/checkpoints1/bert_for_pretraining_without_loss_vocab_30528_hidden_1024_maxpos_512.onnx Step 4 (inside onnxruntime/build/Linux/RelWithDeb): sudo /data/anaconda/envs/py35/bin/python /bert_ort/wechi/DeepLearningExamples/PyTorch/LanguageModeling/BERT/layer_norm_transform.py /bert_ort/wechi/DeepLearningExamples/PyTorch/LanguageModeling/BERT/results/checkpoints1/bert_for_pretraining_without_loss_vocab_30528_hidden_1024_maxpos_512_optimized.onnx Step 5 (inside onnxruntime/build/Linux/RelWithDeb): ./onnxruntime_training_bert --num_of_perf_samples=100 --train_batch_size=1 --mode=perf --model_name /bert_ort/wechi/DeepLearningExamples/PyTorch/LanguageModeling/BERT/results/checkpoints1/bert_for_pretraining_without_loss_vocab_30528_hidden_1024_maxpos_512_optimized_layer_norm