Add initial dataset
Browse files- .gitattributes +4 -0
- .gitignore +160 -0
- a-mnist.py +93 -0
- data/t10k-images-idx3-ubyte.gz +3 -0
- data/t10k-labels-idx1-ubyte.gz +3 -0
- data/train-images-idx3-ubyte.gz +3 -0
- data/train-labels-idx1-ubyte.gz +3 -0
.gitattributes
CHANGED
@@ -52,3 +52,7 @@ saved_model/**/* filter=lfs diff=lfs merge=lfs -text
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*.jpg filter=lfs diff=lfs merge=lfs -text
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*.jpeg filter=lfs diff=lfs merge=lfs -text
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*.webp filter=lfs diff=lfs merge=lfs -text
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*.jpg filter=lfs diff=lfs merge=lfs -text
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*.jpeg filter=lfs diff=lfs merge=lfs -text
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*.webp filter=lfs diff=lfs merge=lfs -text
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data/t10k-images-idx3-ubyte.gz filter=lfs diff=lfs merge=lfs -text
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data/t10k-labels-idx1-ubyte.gz filter=lfs diff=lfs merge=lfs -text
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data/train-images-idx3-ubyte.gz filter=lfs diff=lfs merge=lfs -text
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data/train-labels-idx1-ubyte.gz filter=lfs diff=lfs merge=lfs -text
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.gitignore
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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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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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cover/
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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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.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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# For a library or package, you might want to ignore these files since the code is
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# intended to run in multiple environments; otherwise, check them in:
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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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# poetry
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# Similar to Pipfile.lock, it is generally recommended to include poetry.lock in version control.
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# This is especially recommended for binary packages to ensure reproducibility, and is more
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# commonly ignored for libraries.
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# https://python-poetry.org/docs/basic-usage/#commit-your-poetrylock-file-to-version-control
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#poetry.lock
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# pdm
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# Similar to Pipfile.lock, it is generally recommended to include pdm.lock in version control.
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#pdm.lock
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# pdm stores project-wide configurations in .pdm.toml, but it is recommended to not include it
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# in version control.
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# https://pdm.fming.dev/#use-with-ide
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.pdm.toml
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# PEP 582; used by e.g. github.com/David-OConnor/pyflow and github.com/pdm-project/pdm
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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/
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# pytype static type analyzer
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.pytype/
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# Cython debug symbols
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cython_debug/
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# PyCharm
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# JetBrains specific template is maintained in a separate JetBrains.gitignore that can
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# be found at https://github.com/github/gitignore/blob/main/Global/JetBrains.gitignore
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# and can be added to the global gitignore or merged into this file. For a more nuclear
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# option (not recommended) you can uncomment the following to ignore the entire idea folder.
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.idea/
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a-mnist.py
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"""Augmented MNIST Data Set"""
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import struct
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import numpy as np
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import datasets
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from datasets.tasks import ImageClassification
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_DESCRIPTION = """\
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The dataset is built on top of MNIST.
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It consists from 130K of images in 10 classes - 120K training and 10K test samples.
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The training set was augmented with additional 60K images.
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"""
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_URLS = {
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"train_images": "data/train-images-idx3-ubyte.gz",
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"train_labels": "data/train-labels-idx1-ubyte.gz",
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"test_images": "data/t10k-images-idx3-ubyte.gz",
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"test_labels": "data/t10k-labels-idx1-ubyte.gz",
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}
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class AMNIST(datasets.GeneratorBasedBuilder):
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"""A-MNIST Data Set"""
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BUILDER_CONFIGS = [
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datasets.BuilderConfig(
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name="amnist",
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version=datasets.Version("1.0.0"),
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description=_DESCRIPTION,
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)
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]
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def _info(self):
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return datasets.DatasetInfo(
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description=_DESCRIPTION,
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features=datasets.Features(
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{
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"image": datasets.Image(),
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"label": datasets.features.ClassLabel(names=["0", "1", "2", "3", "4", "5", "6", "7", "8", "9"]),
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}
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),
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supervised_keys=("image", "label"),
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task_templates=[
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ImageClassification(
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image_column="image",
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label_column="label",
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)
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],
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)
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def _split_generators(self, dl_manager):
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urls_to_download = _URLS
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downloaded_files = dl_manager.download_and_extract(urls_to_download)
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return [
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datasets.SplitGenerator(
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name=datasets.Split.TRAIN,
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gen_kwargs={
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"filepath": [downloaded_files["train_images"],
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downloaded_files["train_labels"]],
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"split": "train",
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},
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),
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datasets.SplitGenerator(
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name=datasets.Split.TEST,
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gen_kwargs={
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"filepath": [downloaded_files["test_images"],
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downloaded_files["test_labels"]],
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"split": "test",
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},
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),
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]
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def _generate_examples(self, filepath, split):
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"""This function returns the examples in the raw form."""
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# Images
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with open(filepath[0], "rb") as f:
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# First 16 bytes contain some metadata
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_ = f.read(4)
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size = struct.unpack(">I", f.read(4))[0]
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_ = f.read(8)
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images = np.frombuffer(f.read(), dtype=np.uint8).reshape(size, 28, 28)
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# Labels
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with open(filepath[1], "rb") as f:
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# First 8 bytes contain some metadata
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_ = f.read(8)
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labels = np.frombuffer(f.read(), dtype=np.uint8)
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for idx in range(size):
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yield idx, {"image": images[idx], "label": str(labels[idx])}
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data/t10k-images-idx3-ubyte.gz
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version https://git-lfs.github.com/spec/v1
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oid sha256:8d422c7b0a1c1c79245a5bcf07fe86e33eeafee792b84584aec276f5a2dbc4e6
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size 1648877
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data/t10k-labels-idx1-ubyte.gz
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version https://git-lfs.github.com/spec/v1
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oid sha256:f7ae60f92e00ec6debd23a6088c31dbd2371eca3ffa0defaefb259924204aec6
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size 4542
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data/train-images-idx3-ubyte.gz
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version https://git-lfs.github.com/spec/v1
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oid sha256:440fcabf73cc546fa21475e81ea370265605f56be210a4024d2ca8f203523609
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size 9912422
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data/train-labels-idx1-ubyte.gz
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version https://git-lfs.github.com/spec/v1
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oid sha256:3552534a0a558bbed6aed32b30c495cca23d567ec52cac8be1a0730e8010255c
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size 28881
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