├── .gitignore ├── LICENSE ├── Makefile ├── README.md ├── docs ├── Makefile ├── commands.rst ├── conf.py ├── getting-started.rst ├── index.rst └── make.bat ├── models ├── .gitkeep └── 3.0-fb-conv-classifier.pkl ├── notebooks ├── .gitkeep ├── 1.0-fb-data-exploration.ipynb ├── 2.0-fb-fully-connected-classifier.ipynb ├── 3.0-fb-conv-classifier.ipynb └── 4.0-fb-autoencoder.ipynb ├── references └── .gitkeep ├── reports ├── .gitkeep └── figures │ └── .gitkeep ├── requirements.txt ├── src ├── __init__.py ├── data │ ├── .gitkeep │ ├── fashion.py │ └── make_dataset.py ├── features │ ├── .gitkeep │ └── build_features.py ├── models │ ├── .gitkeep │ ├── flatten.py │ ├── predict_model.py │ └── train_model.py └── visualization │ ├── .gitkeep │ └── visualize.py ├── test_environment.py └── tox.ini /.gitignore: -------------------------------------------------------------------------------- 1 | # Byte-compiled / optimized / DLL files 2 | __pycache__/ 3 | *.py[cod] 4 | 5 | # C extensions 6 | *.so 7 | 8 | # Distribution / packaging 9 | .Python 10 | env/ 11 | build/ 12 | develop-eggs/ 13 | dist/ 14 | downloads/ 15 | eggs/ 16 | .eggs/ 17 | lib/ 18 | lib64/ 19 | parts/ 20 | sdist/ 21 | var/ 22 | *.egg-info/ 23 | .installed.cfg 24 | *.egg 25 | 26 | # PyInstaller 27 | # Usually these files are written by a python script from a template 28 | # before PyInstaller builds the exe, so as to inject date/other infos into it. 29 | *.manifest 30 | *.spec 31 | 32 | # Installer logs 33 | pip-log.txt 34 | pip-delete-this-directory.txt 35 | 36 | # Unit test / coverage reports 37 | htmlcov/ 38 | .tox/ 39 | .coverage 40 | .coverage.* 41 | .cache 42 | nosetests.xml 43 | coverage.xml 44 | *,cover 45 | 46 | # Translations 47 | *.mo 48 | *.pot 49 | 50 | # Django stuff: 51 | *.log 52 | 53 | # Sphinx documentation 54 | docs/_build/ 55 | 56 | # PyBuilder 57 | target/ 58 | 59 | # DotEnv configuration 60 | .env 61 | 62 | # Database 63 | *.db 64 | *.rdb 65 | 66 | # Pycharm 67 | .idea 68 | 69 | # Jupyter NB Checkpoints 70 | .ipynb_checkpoints/ 71 | 72 | # exclude data from source control by default 73 | /data/ 74 | -------------------------------------------------------------------------------- /LICENSE: -------------------------------------------------------------------------------- 1 | 2 | The MIT License (MIT) 3 | Copyright (c) 2017, Federico Baldassarre 4 | 5 | Permission is hereby granted, free of charge, to any person obtaining a copy of this software and associated documentation files (the "Software"), to deal in the Software without restriction, including without limitation the rights to use, copy, modify, merge, publish, distribute, sublicense, and/or sell copies of the Software, and to permit persons to whom the Software is furnished to do so, subject to the following conditions: 6 | 7 | The above copyright notice and this permission notice shall be included in all copies or substantial portions of the Software. 8 | 9 | THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE SOFTWARE. 10 | 11 | -------------------------------------------------------------------------------- /Makefile: -------------------------------------------------------------------------------- 1 | .PHONY: clean data lint requirements sync_data_to_s3 sync_data_from_s3 2 | 3 | ################################################################################# 4 | # GLOBALS # 5 | ################################################################################# 6 | 7 | PROJECT_DIR := $(shell dirname $(realpath $(lastword $(MAKEFILE_LIST)))) 8 | BUCKET = [OPTIONAL] your-bucket-for-syncing-data (do not include 's3://') 9 | PROFILE = default 10 | PROJECT_NAME = zalando-pytorch 11 | PYTHON_INTERPRETER = python3 12 | 13 | ifeq (,$(shell which conda)) 14 | HAS_CONDA=False 15 | else 16 | HAS_CONDA=True 17 | endif 18 | 19 | ################################################################################# 20 | # COMMANDS # 21 | ################################################################################# 22 | 23 | ## Install Python Dependencies 24 | requirements: test_environment 25 | pip3 install -r requirements.txt 26 | 27 | ## Make Dataset 28 | data: requirements 29 | $(PYTHON_INTERPRETER) src/data/make_dataset.py 30 | 31 | ## Delete all compiled Python files 32 | clean: 33 | find . -name "*.pyc" -exec rm {} \; 34 | 35 | ## Lint using flake8 36 | lint: 37 | flake8 --exclude=lib/,bin/,docs/conf.py . 38 | 39 | ## Upload Data to S3 40 | sync_data_to_s3: 41 | ifeq (default,$(PROFILE)) 42 | aws s3 sync data/ s3://$(BUCKET)/data/ 43 | else 44 | aws s3 sync data/ s3://$(BUCKET)/data/ --profile $(PROFILE) 45 | endif 46 | 47 | ## Download Data from S3 48 | sync_data_from_s3: 49 | ifeq (default,$(PROFILE)) 50 | aws s3 sync s3://$(BUCKET)/data/ data/ 51 | else 52 | aws s3 sync s3://$(BUCKET)/data/ data/ --profile $(PROFILE) 53 | endif 54 | 55 | ## Set up python interpreter environment 56 | create_environment: 57 | ifeq (True,$(HAS_CONDA)) 58 | @echo ">>> Detected conda, creating conda environment." 59 | ifeq (3,$(findstring 3,$(PYTHON_INTERPRETER))) 60 | conda create --name $(PROJECT_NAME) python=3 61 | else 62 | conda create --name $(PROJECT_NAME) python=2.7 63 | endif 64 | @echo ">>> New conda env created. Activate with:\nsource activate $(PROJECT_NAME)" 65 | else 66 | @pip install -q virtualenv virtualenvwrapper 67 | @echo ">>> Installing virtualenvwrapper if not already intalled.\nMake sure the following lines are in shell startup file\n\ 68 | export WORKON_HOME=$$HOME/.virtualenvs\nexport PROJECT_HOME=$$HOME/Devel\nsource /usr/local/bin/virtualenvwrapper.sh\n" 69 | @bash -c "source `which virtualenvwrapper.sh`;mkvirtualenv $(PROJECT_NAME) --python=$(PYTHON_INTERPRETER)" 70 | @echo ">>> New virtualenv created. Activate with:\nworkon $(PROJECT_NAME)" 71 | endif 72 | 73 | ## Test python environment is setup correctly 74 | test_environment: 75 | $(PYTHON_INTERPRETER) test_environment.py 76 | 77 | ################################################################################# 78 | # PROJECT RULES # 79 | ################################################################################# 80 | 81 | 82 | 83 | ################################################################################# 84 | # Self Documenting Commands # 85 | ################################################################################# 86 | 87 | .DEFAULT_GOAL := show-help 88 | 89 | # Inspired by 90 | # sed script explained: 91 | # /^##/: 92 | # * save line in hold space 93 | # * purge line 94 | # * Loop: 95 | # * append newline + line to hold space 96 | # * go to next line 97 | # * if line starts with doc comment, strip comment character off and loop 98 | # * remove target prerequisites 99 | # * append hold space (+ newline) to line 100 | # * replace newline plus comments by `---` 101 | # * print line 102 | # Separate expressions are necessary because labels cannot be delimited by 103 | # semicolon; see 104 | .PHONY: show-help 105 | show-help: 106 | @echo "$$(tput bold)Available rules:$$(tput sgr0)" 107 | @echo 108 | @sed -n -e "/^## / { \ 109 | h; \ 110 | s/.*//; \ 111 | :doc" \ 112 | -e "H; \ 113 | n; \ 114 | s/^## //; \ 115 | t doc" \ 116 | -e "s/:.*//; \ 117 | G; \ 118 | s/\\n## /---/; \ 119 | s/\\n/ /g; \ 120 | p; \ 121 | }" ${MAKEFILE_LIST} \ 122 | | LC_ALL='C' sort --ignore-case \ 123 | | awk -F '---' \ 124 | -v ncol=$$(tput cols) \ 125 | -v indent=19 \ 126 | -v col_on="$$(tput setaf 6)" \ 127 | -v col_off="$$(tput sgr0)" \ 128 | '{ \ 129 | printf "%s%*s%s ", col_on, -indent, $$1, col_off; \ 130 | n = split($$2, words, " "); \ 131 | line_length = ncol - indent; \ 132 | for (i = 1; i <= n; i++) { \ 133 | line_length -= length(words[i]) + 1; \ 134 | if (line_length <= 0) { \ 135 | line_length = ncol - indent - length(words[i]) - 1; \ 136 | printf "\n%*s ", -indent, " "; \ 137 | } \ 138 | printf "%s ", words[i]; \ 139 | } \ 140 | printf "\n"; \ 141 | }' \ 142 | | more $(shell test $(shell uname) = Darwin && echo '--no-init --raw-control-chars') 143 | -------------------------------------------------------------------------------- /README.md: -------------------------------------------------------------------------------- 1 | zalando-pytorch 2 | ============================== 3 | 4 | PyTorch experiments with the Zalando fashion-mnist dataset 5 | 6 | Project Organization 7 | ------------ 8 | 9 | ├── LICENSE 10 | ├── Makefile <- Makefile with commands like `make data` or `make train` 11 | ├── README.md <- The top-level README for developers using this project. 12 | ├── data 13 | │   ├── external <- Data from third party sources. 14 | │   ├── interim <- Intermediate data that has been transformed. 15 | │   ├── processed <- The final, canonical data sets for modeling. 16 | │   └── raw <- The original, immutable data dump. 17 | │ 18 | ├── docs <- A default Sphinx project; see sphinx-doc.org for details 19 | │ 20 | ├── models <- Trained and serialized models, model predictions, or model summaries 21 | │ 22 | ├── notebooks <- Jupyter notebooks. Naming convention is a number (for ordering), 23 | │ the creator's initials, and a short `-` delimited description, e.g. 24 | │ `1.0-jqp-initial-data-exploration`. 25 | │ 26 | ├── references <- Data dictionaries, manuals, and all other explanatory materials. 27 | │ 28 | ├── reports <- Generated analysis as HTML, PDF, LaTeX, etc. 29 | │   └── figures <- Generated graphics and figures to be used in reporting 30 | │ 31 | ├── requirements.txt <- The requirements file for reproducing the analysis environment, e.g. 32 | │ generated with `pip freeze > requirements.txt` 33 | │ 34 | ├── src <- Source code for use in this project. 35 | │   ├── __init__.py <- Makes src a Python module 36 | │ │ 37 | │   ├── data <- Scripts to download or generate data 38 | │   │   └── make_dataset.py 39 | │ │ 40 | │   ├── features <- Scripts to turn raw data into features for modeling 41 | │   │   └── build_features.py 42 | │ │ 43 | │   ├── models <- Scripts to train models and then use trained models to make 44 | │ │ │ predictions 45 | │   │   ├── predict_model.py 46 | │   │   └── train_model.py 47 | │ │ 48 | │   └── visualization <- Scripts to create exploratory and results oriented visualizations 49 | │   └── visualize.py 50 | │ 51 | └── tox.ini <- tox file with settings for running tox; see tox.testrun.org 52 | 53 | 54 | -------- 55 | 56 |

Project based on the cookiecutter data science project template. #cookiecutterdatascience

57 | -------------------------------------------------------------------------------- /docs/Makefile: -------------------------------------------------------------------------------- 1 | # Makefile for Sphinx documentation 2 | # 3 | 4 | # You can set these variables from the command line. 5 | SPHINXOPTS = 6 | SPHINXBUILD = sphinx-build 7 | PAPER = 8 | BUILDDIR = _build 9 | 10 | # Internal variables. 11 | PAPEROPT_a4 = -D latex_paper_size=a4 12 | PAPEROPT_letter = -D latex_paper_size=letter 13 | ALLSPHINXOPTS = -d $(BUILDDIR)/doctrees $(PAPEROPT_$(PAPER)) $(SPHINXOPTS) . 14 | # the i18n builder cannot share the environment and doctrees with the others 15 | I18NSPHINXOPTS = $(PAPEROPT_$(PAPER)) $(SPHINXOPTS) . 16 | 17 | .PHONY: help clean html dirhtml singlehtml pickle json htmlhelp qthelp devhelp epub latex latexpdf text man changes linkcheck doctest gettext 18 | 19 | help: 20 | @echo "Please use \`make ' where is one of" 21 | @echo " html to make standalone HTML files" 22 | @echo " dirhtml to make HTML files named index.html in directories" 23 | @echo " singlehtml to make a single large HTML file" 24 | @echo " pickle to make pickle files" 25 | @echo " json to make JSON files" 26 | @echo " htmlhelp to make HTML files and a HTML help project" 27 | @echo " qthelp to make HTML files and a qthelp project" 28 | @echo " devhelp to make HTML files and a Devhelp project" 29 | @echo " epub to make an epub" 30 | @echo " latex to make LaTeX files, you can set PAPER=a4 or PAPER=letter" 31 | @echo " latexpdf to make LaTeX files and run them through pdflatex" 32 | @echo " text to make text files" 33 | @echo " man to make manual pages" 34 | @echo " texinfo to make Texinfo files" 35 | @echo " info to make Texinfo files and run them through makeinfo" 36 | @echo " gettext to make PO message catalogs" 37 | @echo " changes to make an overview of all changed/added/deprecated items" 38 | @echo " linkcheck to check all external links for integrity" 39 | @echo " doctest to run all doctests embedded in the documentation (if enabled)" 40 | 41 | clean: 42 | -rm -rf $(BUILDDIR)/* 43 | 44 | html: 45 | $(SPHINXBUILD) -b html $(ALLSPHINXOPTS) $(BUILDDIR)/html 46 | @echo 47 | @echo "Build finished. The HTML pages are in $(BUILDDIR)/html." 48 | 49 | dirhtml: 50 | $(SPHINXBUILD) -b dirhtml $(ALLSPHINXOPTS) $(BUILDDIR)/dirhtml 51 | @echo 52 | @echo "Build finished. The HTML pages are in $(BUILDDIR)/dirhtml." 53 | 54 | singlehtml: 55 | $(SPHINXBUILD) -b singlehtml $(ALLSPHINXOPTS) $(BUILDDIR)/singlehtml 56 | @echo 57 | @echo "Build finished. The HTML page is in $(BUILDDIR)/singlehtml." 58 | 59 | pickle: 60 | $(SPHINXBUILD) -b pickle $(ALLSPHINXOPTS) $(BUILDDIR)/pickle 61 | @echo 62 | @echo "Build finished; now you can process the pickle files." 63 | 64 | json: 65 | $(SPHINXBUILD) -b json $(ALLSPHINXOPTS) $(BUILDDIR)/json 66 | @echo 67 | @echo "Build finished; now you can process the JSON files." 68 | 69 | htmlhelp: 70 | $(SPHINXBUILD) -b htmlhelp $(ALLSPHINXOPTS) $(BUILDDIR)/htmlhelp 71 | @echo 72 | @echo "Build finished; now you can run HTML Help Workshop with the" \ 73 | ".hhp project file in $(BUILDDIR)/htmlhelp." 74 | 75 | qthelp: 76 | $(SPHINXBUILD) -b qthelp $(ALLSPHINXOPTS) $(BUILDDIR)/qthelp 77 | @echo 78 | @echo "Build finished; now you can run "qcollectiongenerator" with the" \ 79 | ".qhcp project file in $(BUILDDIR)/qthelp, like this:" 80 | @echo "# qcollectiongenerator $(BUILDDIR)/qthelp/zalando-pytorch.qhcp" 81 | @echo "To view the help file:" 82 | @echo "# assistant -collectionFile $(BUILDDIR)/qthelp/zalando-pytorch.qhc" 83 | 84 | devhelp: 85 | $(SPHINXBUILD) -b devhelp $(ALLSPHINXOPTS) $(BUILDDIR)/devhelp 86 | @echo 87 | @echo "Build finished." 88 | @echo "To view the help file:" 89 | @echo "# mkdir -p $$HOME/.local/share/devhelp/zalando-pytorch" 90 | @echo "# ln -s $(BUILDDIR)/devhelp $$HOME/.local/share/devhelp/zalando-pytorch" 91 | @echo "# devhelp" 92 | 93 | epub: 94 | $(SPHINXBUILD) -b epub $(ALLSPHINXOPTS) $(BUILDDIR)/epub 95 | @echo 96 | @echo "Build finished. The epub file is in $(BUILDDIR)/epub." 97 | 98 | latex: 99 | $(SPHINXBUILD) -b latex $(ALLSPHINXOPTS) $(BUILDDIR)/latex 100 | @echo 101 | @echo "Build finished; the LaTeX files are in $(BUILDDIR)/latex." 102 | @echo "Run \`make' in that directory to run these through (pdf)latex" \ 103 | "(use \`make latexpdf' here to do that automatically)." 104 | 105 | latexpdf: 106 | $(SPHINXBUILD) -b latex $(ALLSPHINXOPTS) $(BUILDDIR)/latex 107 | @echo "Running LaTeX files through pdflatex..." 108 | $(MAKE) -C $(BUILDDIR)/latex all-pdf 109 | @echo "pdflatex finished; the PDF files are in $(BUILDDIR)/latex." 110 | 111 | text: 112 | $(SPHINXBUILD) -b text $(ALLSPHINXOPTS) $(BUILDDIR)/text 113 | @echo 114 | @echo "Build finished. The text files are in $(BUILDDIR)/text." 115 | 116 | man: 117 | $(SPHINXBUILD) -b man $(ALLSPHINXOPTS) $(BUILDDIR)/man 118 | @echo 119 | @echo "Build finished. The manual pages are in $(BUILDDIR)/man." 120 | 121 | texinfo: 122 | $(SPHINXBUILD) -b texinfo $(ALLSPHINXOPTS) $(BUILDDIR)/texinfo 123 | @echo 124 | @echo "Build finished. The Texinfo files are in $(BUILDDIR)/texinfo." 125 | @echo "Run \`make' in that directory to run these through makeinfo" \ 126 | "(use \`make info' here to do that automatically)." 127 | 128 | info: 129 | $(SPHINXBUILD) -b texinfo $(ALLSPHINXOPTS) $(BUILDDIR)/texinfo 130 | @echo "Running Texinfo files through makeinfo..." 131 | make -C $(BUILDDIR)/texinfo info 132 | @echo "makeinfo finished; the Info files are in $(BUILDDIR)/texinfo." 133 | 134 | gettext: 135 | $(SPHINXBUILD) -b gettext $(I18NSPHINXOPTS) $(BUILDDIR)/locale 136 | @echo 137 | @echo "Build finished. The message catalogs are in $(BUILDDIR)/locale." 138 | 139 | changes: 140 | $(SPHINXBUILD) -b changes $(ALLSPHINXOPTS) $(BUILDDIR)/changes 141 | @echo 142 | @echo "The overview file is in $(BUILDDIR)/changes." 143 | 144 | linkcheck: 145 | $(SPHINXBUILD) -b linkcheck $(ALLSPHINXOPTS) $(BUILDDIR)/linkcheck 146 | @echo 147 | @echo "Link check complete; look for any errors in the above output " \ 148 | "or in $(BUILDDIR)/linkcheck/output.txt." 149 | 150 | doctest: 151 | $(SPHINXBUILD) -b doctest $(ALLSPHINXOPTS) $(BUILDDIR)/doctest 152 | @echo "Testing of doctests in the sources finished, look at the " \ 153 | "results in $(BUILDDIR)/doctest/output.txt." 154 | -------------------------------------------------------------------------------- /docs/commands.rst: -------------------------------------------------------------------------------- 1 | Commands 2 | ======== 3 | 4 | The Makefile contains the central entry points for common tasks related to this project. 5 | 6 | Syncing data to S3 7 | ^^^^^^^^^^^^^^^^^^ 8 | 9 | * `make sync_data_to_s3` will use `aws s3 sync` to recursively sync files in `data/` up to `s3://[OPTIONAL] your-bucket-for-syncing-data (do not include 's3://')/data/`. 10 | * `make sync_data_from_s3` will use `aws s3 sync` to recursively sync files from `s3://[OPTIONAL] your-bucket-for-syncing-data (do not include 's3://')/data/` to `data/`. 11 | -------------------------------------------------------------------------------- /docs/conf.py: -------------------------------------------------------------------------------- 1 | # -*- coding: utf-8 -*- 2 | # 3 | # zalando-pytorch documentation build configuration file, created by 4 | # sphinx-quickstart. 5 | # 6 | # This file is execfile()d with the current directory set to its containing dir. 7 | # 8 | # Note that not all possible configuration values are present in this 9 | # autogenerated file. 10 | # 11 | # All configuration values have a default; values that are commented out 12 | # serve to show the default. 13 | 14 | import os 15 | import sys 16 | 17 | # If extensions (or modules to document with autodoc) are in another directory, 18 | # add these directories to sys.path here. If the directory is relative to the 19 | # documentation root, use os.path.abspath to make it absolute, like shown here. 20 | # sys.path.insert(0, os.path.abspath('.')) 21 | 22 | # -- General configuration ----------------------------------------------------- 23 | 24 | # If your documentation needs a minimal Sphinx version, state it here. 25 | # needs_sphinx = '1.0' 26 | 27 | # Add any Sphinx extension module names here, as strings. They can be extensions 28 | # coming with Sphinx (named 'sphinx.ext.*') or your custom ones. 29 | extensions = [] 30 | 31 | # Add any paths that contain templates here, relative to this directory. 32 | templates_path = ['_templates'] 33 | 34 | # The suffix of source filenames. 35 | source_suffix = '.rst' 36 | 37 | # The encoding of source files. 38 | # source_encoding = 'utf-8-sig' 39 | 40 | # The master toctree document. 41 | master_doc = 'index' 42 | 43 | # General information about the project. 44 | project = u'zalando-pytorch' 45 | 46 | # The version info for the project you're documenting, acts as replacement for 47 | # |version| and |release|, also used in various other places throughout the 48 | # built documents. 49 | # 50 | # The short X.Y version. 51 | version = '0.1' 52 | # The full version, including alpha/beta/rc tags. 53 | release = '0.1' 54 | 55 | # The language for content autogenerated by Sphinx. Refer to documentation 56 | # for a list of supported languages. 57 | # language = None 58 | 59 | # There are two options for replacing |today|: either, you set today to some 60 | # non-false value, then it is used: 61 | # today = '' 62 | # Else, today_fmt is used as the format for a strftime call. 63 | # today_fmt = '%B %d, %Y' 64 | 65 | # List of patterns, relative to source directory, that match files and 66 | # directories to ignore when looking for source files. 67 | exclude_patterns = ['_build'] 68 | 69 | # The reST default role (used for this markup: `text`) to use for all documents. 70 | # default_role = None 71 | 72 | # If true, '()' will be appended to :func: etc. cross-reference text. 73 | # add_function_parentheses = True 74 | 75 | # If true, the current module name will be prepended to all description 76 | # unit titles (such as .. function::). 77 | # add_module_names = True 78 | 79 | # If true, sectionauthor and moduleauthor directives will be shown in the 80 | # output. They are ignored by default. 81 | # show_authors = False 82 | 83 | # The name of the Pygments (syntax highlighting) style to use. 84 | pygments_style = 'sphinx' 85 | 86 | # A list of ignored prefixes for module index sorting. 87 | # modindex_common_prefix = [] 88 | 89 | 90 | # -- Options for HTML output --------------------------------------------------- 91 | 92 | # The theme to use for HTML and HTML Help pages. See the documentation for 93 | # a list of builtin themes. 94 | html_theme = 'default' 95 | 96 | # Theme options are theme-specific and customize the look and feel of a theme 97 | # further. For a list of options available for each theme, see the 98 | # documentation. 99 | # html_theme_options = {} 100 | 101 | # Add any paths that contain custom themes here, relative to this directory. 102 | # html_theme_path = [] 103 | 104 | # The name for this set of Sphinx documents. If None, it defaults to 105 | # " v documentation". 106 | # html_title = None 107 | 108 | # A shorter title for the navigation bar. Default is the same as html_title. 109 | # html_short_title = None 110 | 111 | # The name of an image file (relative to this directory) to place at the top 112 | # of the sidebar. 113 | # html_logo = None 114 | 115 | # The name of an image file (within the static path) to use as favicon of the 116 | # docs. This file should be a Windows icon file (.ico) being 16x16 or 32x32 117 | # pixels large. 118 | # html_favicon = None 119 | 120 | # Add any paths that contain custom static files (such as style sheets) here, 121 | # relative to this directory. They are copied after the builtin static files, 122 | # so a file named "default.css" will overwrite the builtin "default.css". 123 | html_static_path = ['_static'] 124 | 125 | # If not '', a 'Last updated on:' timestamp is inserted at every page bottom, 126 | # using the given strftime format. 127 | # html_last_updated_fmt = '%b %d, %Y' 128 | 129 | # If true, SmartyPants will be used to convert quotes and dashes to 130 | # typographically correct entities. 131 | # html_use_smartypants = True 132 | 133 | # Custom sidebar templates, maps document names to template names. 134 | # html_sidebars = {} 135 | 136 | # Additional templates that should be rendered to pages, maps page names to 137 | # template names. 138 | # html_additional_pages = {} 139 | 140 | # If false, no module index is generated. 141 | # html_domain_indices = True 142 | 143 | # If false, no index is generated. 144 | # html_use_index = True 145 | 146 | # If true, the index is split into individual pages for each letter. 147 | # html_split_index = False 148 | 149 | # If true, links to the reST sources are added to the pages. 150 | # html_show_sourcelink = True 151 | 152 | # If true, "Created using Sphinx" is shown in the HTML footer. Default is True. 153 | # html_show_sphinx = True 154 | 155 | # If true, "(C) Copyright ..." is shown in the HTML footer. Default is True. 156 | # html_show_copyright = True 157 | 158 | # If true, an OpenSearch description file will be output, and all pages will 159 | # contain a tag referring to it. The value of this option must be the 160 | # base URL from which the finished HTML is served. 161 | # html_use_opensearch = '' 162 | 163 | # This is the file name suffix for HTML files (e.g. ".xhtml"). 164 | # html_file_suffix = None 165 | 166 | # Output file base name for HTML help builder. 167 | htmlhelp_basename = 'zalando-pytorchdoc' 168 | 169 | 170 | # -- Options for LaTeX output -------------------------------------------------- 171 | 172 | latex_elements = { 173 | # The paper size ('letterpaper' or 'a4paper'). 174 | # 'papersize': 'letterpaper', 175 | 176 | # The font size ('10pt', '11pt' or '12pt'). 177 | # 'pointsize': '10pt', 178 | 179 | # Additional stuff for the LaTeX preamble. 180 | # 'preamble': '', 181 | } 182 | 183 | # Grouping the document tree into LaTeX files. List of tuples 184 | # (source start file, target name, title, author, documentclass [howto/manual]). 185 | latex_documents = [ 186 | ('index', 187 | 'zalando-pytorch.tex', 188 | u'zalando-pytorch Documentation', 189 | u"Federico Baldassarre", 'manual'), 190 | ] 191 | 192 | # The name of an image file (relative to this directory) to place at the top of 193 | # the title page. 194 | # latex_logo = None 195 | 196 | # For "manual" documents, if this is true, then toplevel headings are parts, 197 | # not chapters. 198 | # latex_use_parts = False 199 | 200 | # If true, show page references after internal links. 201 | # latex_show_pagerefs = False 202 | 203 | # If true, show URL addresses after external links. 204 | # latex_show_urls = False 205 | 206 | # Documents to append as an appendix to all manuals. 207 | # latex_appendices = [] 208 | 209 | # If false, no module index is generated. 210 | # latex_domain_indices = True 211 | 212 | 213 | # -- Options for manual page output -------------------------------------------- 214 | 215 | # One entry per manual page. List of tuples 216 | # (source start file, name, description, authors, manual section). 217 | man_pages = [ 218 | ('index', 'zalando-pytorch', u'zalando-pytorch Documentation', 219 | [u"Federico Baldassarre"], 1) 220 | ] 221 | 222 | # If true, show URL addresses after external links. 223 | # man_show_urls = False 224 | 225 | 226 | # -- Options for Texinfo output ------------------------------------------------ 227 | 228 | # Grouping the document tree into Texinfo files. List of tuples 229 | # (source start file, target name, title, author, 230 | # dir menu entry, description, category) 231 | texinfo_documents = [ 232 | ('index', 'zalando-pytorch', u'zalando-pytorch Documentation', 233 | u"Federico Baldassarre", 'zalando-pytorch', 234 | 'PyTorch experiments with the Zalando fashion-mnist dataset', 'Miscellaneous'), 235 | ] 236 | 237 | # Documents to append as an appendix to all manuals. 238 | # texinfo_appendices = [] 239 | 240 | # If false, no module index is generated. 241 | # texinfo_domain_indices = True 242 | 243 | # How to display URL addresses: 'footnote', 'no', or 'inline'. 244 | # texinfo_show_urls = 'footnote' 245 | -------------------------------------------------------------------------------- /docs/getting-started.rst: -------------------------------------------------------------------------------- 1 | Getting started 2 | =============== 3 | 4 | This is where you describe how to get set up on a clean install, including the 5 | commands necessary to get the raw data (using the `sync_data_from_s3` command, 6 | for example), and then how to make the cleaned, final data sets. 7 | -------------------------------------------------------------------------------- /docs/index.rst: -------------------------------------------------------------------------------- 1 | .. zalando-pytorch documentation master file, created by 2 | sphinx-quickstart. 3 | You can adapt this file completely to your liking, but it should at least 4 | contain the root `toctree` directive. 5 | 6 | zalando-pytorch documentation! 7 | ============================================== 8 | 9 | Contents: 10 | 11 | .. toctree:: 12 | :maxdepth: 2 13 | 14 | getting-started 15 | commands 16 | 17 | 18 | 19 | Indices and tables 20 | ================== 21 | 22 | * :ref:`genindex` 23 | * :ref:`modindex` 24 | * :ref:`search` 25 | -------------------------------------------------------------------------------- /docs/make.bat: -------------------------------------------------------------------------------- 1 | @ECHO OFF 2 | 3 | REM Command file for Sphinx documentation 4 | 5 | if "%SPHINXBUILD%" == "" ( 6 | set SPHINXBUILD=sphinx-build 7 | ) 8 | set BUILDDIR=_build 9 | set ALLSPHINXOPTS=-d %BUILDDIR%/doctrees %SPHINXOPTS% . 10 | set I18NSPHINXOPTS=%SPHINXOPTS% . 11 | if NOT "%PAPER%" == "" ( 12 | set ALLSPHINXOPTS=-D latex_paper_size=%PAPER% %ALLSPHINXOPTS% 13 | set I18NSPHINXOPTS=-D latex_paper_size=%PAPER% %I18NSPHINXOPTS% 14 | ) 15 | 16 | if "%1" == "" goto help 17 | 18 | if "%1" == "help" ( 19 | :help 20 | echo.Please use `make ^` where ^ is one of 21 | echo. html to make standalone HTML files 22 | echo. dirhtml to make HTML files named index.html in directories 23 | echo. singlehtml to make a single large HTML file 24 | echo. pickle to make pickle files 25 | echo. json to make JSON files 26 | echo. htmlhelp to make HTML files and a HTML help project 27 | echo. qthelp to make HTML files and a qthelp project 28 | echo. devhelp to make HTML files and a Devhelp project 29 | echo. epub to make an epub 30 | echo. latex to make LaTeX files, you can set PAPER=a4 or PAPER=letter 31 | echo. text to make text files 32 | echo. man to make manual pages 33 | echo. texinfo to make Texinfo files 34 | echo. gettext to make PO message catalogs 35 | echo. changes to make an overview over all changed/added/deprecated items 36 | echo. linkcheck to check all external links for integrity 37 | echo. doctest to run all doctests embedded in the documentation if enabled 38 | goto end 39 | ) 40 | 41 | if "%1" == "clean" ( 42 | for /d %%i in (%BUILDDIR%\*) do rmdir /q /s %%i 43 | del /q /s %BUILDDIR%\* 44 | goto end 45 | ) 46 | 47 | if "%1" == "html" ( 48 | %SPHINXBUILD% -b html %ALLSPHINXOPTS% %BUILDDIR%/html 49 | if errorlevel 1 exit /b 1 50 | echo. 51 | echo.Build finished. The HTML pages are in %BUILDDIR%/html. 52 | goto end 53 | ) 54 | 55 | if "%1" == "dirhtml" ( 56 | %SPHINXBUILD% -b dirhtml %ALLSPHINXOPTS% %BUILDDIR%/dirhtml 57 | if errorlevel 1 exit /b 1 58 | echo. 59 | echo.Build finished. The HTML pages are in %BUILDDIR%/dirhtml. 60 | goto end 61 | ) 62 | 63 | if "%1" == "singlehtml" ( 64 | %SPHINXBUILD% -b singlehtml %ALLSPHINXOPTS% %BUILDDIR%/singlehtml 65 | if errorlevel 1 exit /b 1 66 | echo. 67 | echo.Build finished. The HTML pages are in %BUILDDIR%/singlehtml. 68 | goto end 69 | ) 70 | 71 | if "%1" == "pickle" ( 72 | %SPHINXBUILD% -b pickle %ALLSPHINXOPTS% %BUILDDIR%/pickle 73 | if errorlevel 1 exit /b 1 74 | echo. 75 | echo.Build finished; now you can process the pickle files. 76 | goto end 77 | ) 78 | 79 | if "%1" == "json" ( 80 | %SPHINXBUILD% -b json %ALLSPHINXOPTS% %BUILDDIR%/json 81 | if errorlevel 1 exit /b 1 82 | echo. 83 | echo.Build finished; now you can process the JSON files. 84 | goto end 85 | ) 86 | 87 | if "%1" == "htmlhelp" ( 88 | %SPHINXBUILD% -b htmlhelp %ALLSPHINXOPTS% %BUILDDIR%/htmlhelp 89 | if errorlevel 1 exit /b 1 90 | echo. 91 | echo.Build finished; now you can run HTML Help Workshop with the ^ 92 | .hhp project file in %BUILDDIR%/htmlhelp. 93 | goto end 94 | ) 95 | 96 | if "%1" == "qthelp" ( 97 | %SPHINXBUILD% -b qthelp %ALLSPHINXOPTS% %BUILDDIR%/qthelp 98 | if errorlevel 1 exit /b 1 99 | echo. 100 | echo.Build finished; now you can run "qcollectiongenerator" with the ^ 101 | .qhcp project file in %BUILDDIR%/qthelp, like this: 102 | echo.^> qcollectiongenerator %BUILDDIR%\qthelp\zalando-pytorch.qhcp 103 | echo.To view the help file: 104 | echo.^> assistant -collectionFile %BUILDDIR%\qthelp\zalando-pytorch.ghc 105 | goto end 106 | ) 107 | 108 | if "%1" == "devhelp" ( 109 | %SPHINXBUILD% -b devhelp %ALLSPHINXOPTS% %BUILDDIR%/devhelp 110 | if errorlevel 1 exit /b 1 111 | echo. 112 | echo.Build finished. 113 | goto end 114 | ) 115 | 116 | if "%1" == "epub" ( 117 | %SPHINXBUILD% -b epub %ALLSPHINXOPTS% %BUILDDIR%/epub 118 | if errorlevel 1 exit /b 1 119 | echo. 120 | echo.Build finished. The epub file is in %BUILDDIR%/epub. 121 | goto end 122 | ) 123 | 124 | if "%1" == "latex" ( 125 | %SPHINXBUILD% -b latex %ALLSPHINXOPTS% %BUILDDIR%/latex 126 | if errorlevel 1 exit /b 1 127 | echo. 128 | echo.Build finished; the LaTeX files are in %BUILDDIR%/latex. 129 | goto end 130 | ) 131 | 132 | if "%1" == "text" ( 133 | %SPHINXBUILD% -b text %ALLSPHINXOPTS% %BUILDDIR%/text 134 | if errorlevel 1 exit /b 1 135 | echo. 136 | echo.Build finished. The text files are in %BUILDDIR%/text. 137 | goto end 138 | ) 139 | 140 | if "%1" == "man" ( 141 | %SPHINXBUILD% -b man %ALLSPHINXOPTS% %BUILDDIR%/man 142 | if errorlevel 1 exit /b 1 143 | echo. 144 | echo.Build finished. The manual pages are in %BUILDDIR%/man. 145 | goto end 146 | ) 147 | 148 | if "%1" == "texinfo" ( 149 | %SPHINXBUILD% -b texinfo %ALLSPHINXOPTS% %BUILDDIR%/texinfo 150 | if errorlevel 1 exit /b 1 151 | echo. 152 | echo.Build finished. The Texinfo files are in %BUILDDIR%/texinfo. 153 | goto end 154 | ) 155 | 156 | if "%1" == "gettext" ( 157 | %SPHINXBUILD% -b gettext %I18NSPHINXOPTS% %BUILDDIR%/locale 158 | if errorlevel 1 exit /b 1 159 | echo. 160 | echo.Build finished. The message catalogs are in %BUILDDIR%/locale. 161 | goto end 162 | ) 163 | 164 | if "%1" == "changes" ( 165 | %SPHINXBUILD% -b changes %ALLSPHINXOPTS% %BUILDDIR%/changes 166 | if errorlevel 1 exit /b 1 167 | echo. 168 | echo.The overview file is in %BUILDDIR%/changes. 169 | goto end 170 | ) 171 | 172 | if "%1" == "linkcheck" ( 173 | %SPHINXBUILD% -b linkcheck %ALLSPHINXOPTS% %BUILDDIR%/linkcheck 174 | if errorlevel 1 exit /b 1 175 | echo. 176 | echo.Link check complete; look for any errors in the above output ^ 177 | or in %BUILDDIR%/linkcheck/output.txt. 178 | goto end 179 | ) 180 | 181 | if "%1" == "doctest" ( 182 | %SPHINXBUILD% -b doctest %ALLSPHINXOPTS% %BUILDDIR%/doctest 183 | if errorlevel 1 exit /b 1 184 | echo. 185 | echo.Testing of doctests in the sources finished, look at the ^ 186 | results in %BUILDDIR%/doctest/output.txt. 187 | goto end 188 | ) 189 | 190 | :end 191 | -------------------------------------------------------------------------------- /models/.gitkeep: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/baldassarreFe/zalando-pytorch/e37d70d7aabb5e8648b98ed4bd27320229d0c195/models/.gitkeep -------------------------------------------------------------------------------- /models/3.0-fb-conv-classifier.pkl: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/baldassarreFe/zalando-pytorch/e37d70d7aabb5e8648b98ed4bd27320229d0c195/models/3.0-fb-conv-classifier.pkl -------------------------------------------------------------------------------- /notebooks/.gitkeep: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/baldassarreFe/zalando-pytorch/e37d70d7aabb5e8648b98ed4bd27320229d0c195/notebooks/.gitkeep -------------------------------------------------------------------------------- /notebooks/1.0-fb-data-exploration.ipynb: -------------------------------------------------------------------------------- 1 | { 2 | "cells": [ 3 | { 4 | "cell_type": "markdown", 5 | "metadata": {}, 6 | "source": [ 7 | "# Data visualization" 8 | ] 9 | }, 10 | { 11 | "cell_type": "code", 12 | "execution_count": 1, 13 | "metadata": { 14 | "collapsed": true 15 | }, 16 | "outputs": [], 17 | "source": [ 18 | "%matplotlib inline\n", 19 | "import matplotlib.pyplot as plt\n", 20 | "\n", 21 | "from torch.utils.data import DataLoader\n", 22 | "from torchvision import transforms" 23 | ] 24 | }, 25 | { 26 | "cell_type": "markdown", 27 | "metadata": {}, 28 | "source": [ 29 | "Load a custom subclass of torchvision.datasets.MNIST that instead downloads the FashionMNIST dataset \n", 30 | "\n", 31 | "(waiting for [this commit](https://github.com/pytorch/vision/commit/eec5ba4405c8815bd1797619d9cc9276f81b76f4) be available in the pytorch version installable via pip)." 32 | ] 33 | }, 34 | { 35 | "cell_type": "code", 36 | "execution_count": 2, 37 | "metadata": { 38 | "collapsed": true 39 | }, 40 | "outputs": [], 41 | "source": [ 42 | "import os\n", 43 | "import sys\n", 44 | "sys.path.append(os.path.join(os.getcwd(), os.pardir, 'src'))\n", 45 | "from data.fashion import FashionMNIST" 46 | ] 47 | }, 48 | { 49 | "cell_type": "markdown", 50 | "metadata": {}, 51 | "source": [ 52 | "Load some images and visualize them" 53 | ] 54 | }, 55 | { 56 | "cell_type": "code", 57 | "execution_count": 3, 58 | "metadata": { 59 | "collapsed": true 60 | }, 61 | "outputs": [], 62 | "source": [ 63 | "batch_size = 64\n", 64 | "\n", 65 | "dataset = FashionMNIST('../data', train=True, download=True, transform=transforms.ToTensor())\n", 66 | "loader = DataLoader(dataset, batch_size=batch_size, shuffle=True)" 67 | ] 68 | }, 69 | { 70 | "cell_type": "code", 71 | "execution_count": 4, 72 | "metadata": {}, 73 | "outputs": [ 74 | { 75 | "data": { 76 | "image/png": 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SVStbZc477zxvc5vY+Yfl4ZzV2I7bNPmv/Tu3D8u/rF/l8V2TyJIkcl2xj7SS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pXsZR4tcoSyDHbLA87EVSY5qTbrYtn/ixY0rsU94HvN1+oX2WWZMMu9/DVwpq2NN9643dfXyPh7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\nlHpYjurdRIYPHx7ta6+9Ntpf//rXo/2Xv/wlOYfHrbJ7Q0N54PbDzyq+v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lYjkBOY0DEL6q5uNZ6SyH950+fXr0vFmhlRsCBx10UHQby2VYdsqyiqzcV9wvbKoOzvN56KGH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77 | "text/plain": [ 78 | "" 79 | ] 80 | }, 81 | "metadata": {}, 82 | "output_type": "display_data" 83 | } 84 | ], 85 | "source": [ 86 | "fig, axes = plt.subplots(8, 8, figsize=(16, 16))\n", 87 | "\n", 88 | "for ax, data, label in zip(axes.ravel(), *next(loader.__iter__())):\n", 89 | " ax.imshow(data.numpy().squeeze(), cmap='gray')\n", 90 | " ax.set_title(FashionMNIST.labels[label])\n", 91 | " ax.axes.get_xaxis().set_visible(False)\n", 92 | " ax.axes.get_yaxis().set_visible(False)" 93 | ] 94 | } 95 | ], 96 | "metadata": { 97 | "kernelspec": { 98 | "display_name": "Python 3", 99 | "language": "python", 100 | "name": "python3" 101 | }, 102 | "language_info": { 103 | "codemirror_mode": { 104 | "name": "ipython", 105 | "version": 3 106 | }, 107 | "file_extension": ".py", 108 | "mimetype": "text/x-python", 109 | "name": "python", 110 | "nbconvert_exporter": "python", 111 | "pygments_lexer": "ipython3", 112 | "version": "3.5.2" 113 | } 114 | }, 115 | "nbformat": 4, 116 | "nbformat_minor": 2 117 | } 118 | -------------------------------------------------------------------------------- /references/.gitkeep: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/baldassarreFe/zalando-pytorch/e37d70d7aabb5e8648b98ed4bd27320229d0c195/references/.gitkeep -------------------------------------------------------------------------------- /reports/.gitkeep: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/baldassarreFe/zalando-pytorch/e37d70d7aabb5e8648b98ed4bd27320229d0c195/reports/.gitkeep -------------------------------------------------------------------------------- /reports/figures/.gitkeep: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/baldassarreFe/zalando-pytorch/e37d70d7aabb5e8648b98ed4bd27320229d0c195/reports/figures/.gitkeep -------------------------------------------------------------------------------- /requirements.txt: -------------------------------------------------------------------------------- 1 | click 2 | Sphinx 3 | coverage 4 | awscli 5 | flake8 6 | python-dotenv>=0.5.1 7 | -------------------------------------------------------------------------------- /src/__init__.py: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/baldassarreFe/zalando-pytorch/e37d70d7aabb5e8648b98ed4bd27320229d0c195/src/__init__.py -------------------------------------------------------------------------------- /src/data/.gitkeep: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/baldassarreFe/zalando-pytorch/e37d70d7aabb5e8648b98ed4bd27320229d0c195/src/data/.gitkeep -------------------------------------------------------------------------------- /src/data/fashion.py: -------------------------------------------------------------------------------- 1 | from torchvision.datasets import MNIST 2 | 3 | class FashionMNIST(MNIST): 4 | """`Fashion MNIST `_ Dataset. 5 | """ 6 | urls = [ 7 | 'http://fashion-mnist.s3-website.eu-central-1.amazonaws.com/train-images-idx3-ubyte.gz', 8 | 'http://fashion-mnist.s3-website.eu-central-1.amazonaws.com/train-labels-idx1-ubyte.gz', 9 | 'http://fashion-mnist.s3-website.eu-central-1.amazonaws.com/t10k-images-idx3-ubyte.gz', 10 | 'http://fashion-mnist.s3-website.eu-central-1.amazonaws.com/t10k-labels-idx1-ubyte.gz', 11 | ] 12 | 13 | input_shape = (28, 28) 14 | num_classes = 10 15 | 16 | labels = [ 17 | 'T-shirt/top', 18 | 'Trouser', 19 | 'Pullover', 20 | 'Dress', 21 | 'Coat', 22 | 'Sandal', 23 | 'Shirt', 24 | 'Sneaker', 25 | 'Bag', 26 | 'Ankle boot' 27 | ] 28 | -------------------------------------------------------------------------------- /src/data/make_dataset.py: -------------------------------------------------------------------------------- 1 | # -*- coding: utf-8 -*- 2 | import os 3 | import click 4 | import logging 5 | from dotenv import find_dotenv, load_dotenv 6 | 7 | 8 | @click.command() 9 | @click.argument('input_filepath', type=click.Path(exists=True)) 10 | @click.argument('output_filepath', type=click.Path()) 11 | def main(input_filepath, output_filepath): 12 | """ Runs data processing scripts to turn raw data from (../raw) into 13 | cleaned data ready to be analyzed (saved in ../processed). 14 | """ 15 | logger = logging.getLogger(__name__) 16 | logger.info('making final data set from raw data') 17 | 18 | 19 | if __name__ == '__main__': 20 | log_fmt = '%(asctime)s - %(name)s - %(levelname)s - %(message)s' 21 | logging.basicConfig(level=logging.INFO, format=log_fmt) 22 | 23 | # not used in this stub but often useful for finding various files 24 | project_dir = os.path.join(os.path.dirname(__file__), os.pardir, os.pardir) 25 | 26 | # find .env automagically by walking up directories until it's found, then 27 | # load up the .env entries as environment variables 28 | load_dotenv(find_dotenv()) 29 | 30 | main() 31 | -------------------------------------------------------------------------------- /src/features/.gitkeep: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/baldassarreFe/zalando-pytorch/e37d70d7aabb5e8648b98ed4bd27320229d0c195/src/features/.gitkeep -------------------------------------------------------------------------------- /src/features/build_features.py: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/baldassarreFe/zalando-pytorch/e37d70d7aabb5e8648b98ed4bd27320229d0c195/src/features/build_features.py -------------------------------------------------------------------------------- /src/models/.gitkeep: 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/src/models/train_model.py: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/baldassarreFe/zalando-pytorch/e37d70d7aabb5e8648b98ed4bd27320229d0c195/src/models/train_model.py -------------------------------------------------------------------------------- /src/visualization/.gitkeep: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/baldassarreFe/zalando-pytorch/e37d70d7aabb5e8648b98ed4bd27320229d0c195/src/visualization/.gitkeep -------------------------------------------------------------------------------- /src/visualization/visualize.py: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/baldassarreFe/zalando-pytorch/e37d70d7aabb5e8648b98ed4bd27320229d0c195/src/visualization/visualize.py -------------------------------------------------------------------------------- /test_environment.py: -------------------------------------------------------------------------------- 1 | import sys 2 | 3 | REQUIRED_PYTHON = "python3" 4 | 5 | 6 | def main(): 7 | system_major = sys.version_info.major 8 | if REQUIRED_PYTHON == "python": 9 | required_major = 2 10 | elif REQUIRED_PYTHON == "python3": 11 | required_major = 3 12 | else: 13 | raise ValueError("Unrecognized python interpreter: {}".format( 14 | REQUIRED_PYTHON)) 15 | 16 | if system_major != required_major: 17 | raise TypeError( 18 | "This project requires Python {}. Found: Python {}".format( 19 | required_major, sys.version)) 20 | else: 21 | print(">>> Development environment passes all tests!") 22 | 23 | 24 | if __name__ == '__main__': 25 | main() -------------------------------------------------------------------------------- /tox.ini: -------------------------------------------------------------------------------- 1 | [flake8] 2 | max-line-length = 79 3 | max-complexity = 10 4 | --------------------------------------------------------------------------------