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setup configuration files
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.gitignore

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.ipynb_checkpoints
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lab1/*.pyc
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lab2/*.pyc
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*.pyc
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*.h5
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lab2/logs/*
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# Byte-compiled / optimized / DLL files
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__pycache__/
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*.py[cod]
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*$py.class
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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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pip-wheel-metadata/
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share/python-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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# 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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.nox/
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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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*.py,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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db.sqlite3-journal
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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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# IPython
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profile_default/
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ipython_config.py
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# pyenv
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.python-version
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# pipenv
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# According to pypa/pipenv#598, it is recommended to include Pipfile.lock in version control.
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# However, in case of collaboration, if having platform-specific dependencies or dependencies
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# having no cross-platform support, pipenv may install dependencies that don't work, or not
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# install all needed dependencies.
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#Pipfile.lock
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# PEP 582; used by e.g. github.com/David-OConnor/pyflow
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__pypackages__/
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# Celery stuff
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celerybeat-schedule
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celerybeat.pid
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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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.dmypy.json
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dmypy.json
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# Pyre type checker
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.pyre/

LICENSE.txt

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MIT License
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Copyright (c) 2018 YOUR NAME
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Permission is hereby granted, free of charge, to any person obtaining a copy
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of this software and associated documentation files (the "Software"), to deal
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in the Software without restriction, including without limitation the rights
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to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
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copies of the Software, and to permit persons to whom the Software is
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furnished to do so, subject to the following conditions:
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The above copyright notice and this permission notice shall be included in all
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copies or substantial portions of the Software.
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THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
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IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
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FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
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AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
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LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
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OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
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SOFTWARE.

mitdeeplearning/lab1.py

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def func():
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print("hi")
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print("test package")

setup.cfg

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# Inside of setup.cfg
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[metadata]
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description-file = README.md

setup.py

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from pkg_resources import DistributionNotFound, get_distribution
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from distutils.core import setup
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def get_dist(pkgname):
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try:
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return get_distribution(pkgname)
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except DistributionNotFound:
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return None
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install_deps = [
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'numpy',
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'regex',
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]
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if get_dist('tensorflow>=2.0.0') is None and get_dist('tensorflow_gpu>=2.0.0') is None:
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install_deps.append('tensorflow>=2.0.0a')
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setup(
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name = 'mitdeeplearning', # How you named your package folder (MyLib)
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packages = ['mitdeeplearning'], # Chose the same as "name"
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version = '0.1', # Start with a small number and increase it with every change you make
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license='MIT', # Chose a license from here: https://help.github.com/articles/licensing-a-repository
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description = 'Official software labs for MIT Introduction to Deep Learning (http://introtodeeplearning.com)', # Give a short description about your library
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author = 'Alexander Amini', # Type in your name
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author_email = '[email protected]', # Type in your E-Mail
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url = 'http://introtodeeplearning.com', # Provide either the link to your github or to your website
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download_url = 'https://github.com/aamini/introtodeeplearning_labs/archive/v0.1.tar.gz', # I explain this later on
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keywords = ['deep learning', 'neural networks', 'tensorflow', 'introduction'], # Keywords that define your package best
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install_requires=install_deps,
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classifiers=[
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'Development Status :: 3 - Alpha', # Chose either "3 - Alpha", "4 - Beta" or "5 - Production/Stable" as the current state of your package
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'License :: OSI Approved :: MIT License', # Again, pick a license
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'Programming Language :: Python :: 3', #Specify which pyhton versions that you want to support',
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'Programming Language :: Python :: 3.6',
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],
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)

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