mirror of
https://github.com/wassname/pytorch-ts.git
synced 2026-07-05 05:05:17 +08:00
Kashif Rasul
908945b422
* initial uncond image gaussian diff TODO make it work for multivariate vector add conditioning * remove tqdm * initial unet TODO convert to 1d conv * initial time grad estimator * initial training * initial sampling * added huber loss * use SinusoidalPosEmb from wavegrad * use time diff network * fix reshaping * fix missing property * clip false * updated api * added padding * added circular padding * use linear schedule * added more schedules * added back cosine schedule * Delete Solar-time-grad.ipynb * updated estimator API * not tuple * renamed to EpsilonTheta * removed * added example notebook * removed some output * fix requirements * formatting * added more options to time-grad * added article
33 lines
927 B
Python
33 lines
927 B
Python
from setuptools import setup, find_packages
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setup(
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name="pytorchts",
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version="0.3.0",
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description="PyTorch Probabilistic Time Series Modeling framework",
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long_description=open("README.md").read(),
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long_description_content_type="text/markdown",
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author="Kashif Rasul",
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author_email="kashif.rasul@zalando.de",
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url="https://github.com/zalandoresearch/pytorch-ts",
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license="MIT",
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packages=find_packages(exclude=["tests"]),
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include_package_data=True,
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zip_safe=True,
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python_requires=">=3.6",
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install_requires=[
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"torch>=1.7.0",
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"gluonts",
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"holidays",
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"numpy~=1.16",
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"pandas~=1.1",
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"scipy",
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"tqdm",
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"matplotlib",
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"tensorboard",
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"wandb",
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],
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dependency_links=["git+https://github.com/awslabs/gluon-ts.git@master#egg=gluonts"],
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test_suite="tests",
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tests_require=["flake8", "pytest"],
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)
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