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132
.gitignore
vendored
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132
.gitignore
vendored
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# Byte-compiled / optimized / DLL files
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**/__pycache__/
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__pycache__/
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*.py[cod]
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*$py.class
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.github
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# C extensions
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*.so
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# Distribution / packaging
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.Python
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build/
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develop-eggs/
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dist/
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downloads/
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eggs/
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.eggs/
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lib/
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lib64/
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parts/
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sdist/
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var/
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wheels/
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*.egg-info/
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.installed.cfg
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*.egg
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MANIFEST
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# Lightning /research
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test_tube_exp/
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tests/tests_tt_dir/
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tests/save_dir
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default/
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data/
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test_tube_logs/
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test_tube_data/
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datasets/
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model_weights/
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tests/save_dir
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tests/tests_tt_dir/
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processed/
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raw/
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# PyInstaller
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# Usually these files are written by a python script from a template
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# before PyInstaller builds the exe, so as to inject date/other infos into it.
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*.manifest
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*.spec
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# Installer logs
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pip-log.txt
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pip-delete-this-directory.txt
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# Unit test / coverage reports
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htmlcov/
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.tox/
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.coverage
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.coverage.*
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.cache
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nosetests.xml
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coverage.xml
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*.cover
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.hypothesis/
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.pytest_cache/
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# Translations
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*.mo
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*.pot
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# Django stuff:
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*.log
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local_settings.py
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db.sqlite3
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# Flask stuff:
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instance/
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.webassets-cache
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# Scrapy stuff:
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.scrapy
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# Sphinx documentation
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docs/_build/
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# PyBuilder
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target/
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# Jupyter Notebook
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.ipynb_checkpoints
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# pyenv
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.python-version
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# celery beat schedule file
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celerybeat-schedule
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# SageMath parsed files
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*.sage.py
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# Environments
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.env
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.venv
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env/
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venv/
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ENV/
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env.bak/
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venv.bak/
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# Spyder project settings
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.spyderproject
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.spyproject
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# Rope project settings
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.ropeproject
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# mkdocs documentation
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/site
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# mypy
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.mypy_cache/
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# IDEs
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.idea
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.vscode
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# seed project
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lightning_logs/
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MNIST
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.DS_Store
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**/nohup
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*.out
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@@ -460,7 +460,6 @@ class FlowModule(LightningModule):
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diffuse_mask = torch.ones(1, sample_length, device=device)
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self.prot_df = pd.DataFrame(columns=['prot_path','length'])
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for i in range(num_batch):
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sample_dir = sample_dirs[i]
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@@ -478,11 +477,6 @@ class FlowModule(LightningModule):
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trans_1=trans_1, rotmats_1=rotmats_1, diffuse_mask=diffuse_mask
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)
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append = pd.DataFrame([[prot_traj_dir, sample_length]], columns=self.prot_df.columns)
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if not os.path.exists(os.path.join(self.inference_dir, 'prot_df.csv')):
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append.to_csv(os.path.join(self.inference_dir, 'prot_df.csv'), index=False)
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else:
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append.to_csv(os.path.join(self.inference_dir, 'prot_df.csv'), mode='a', header=False, index=False)
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finish_sample_time = time.time()
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