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py-clip-anytorch: new package (#47050)

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* py-clip-anytorch: new package

* py-clip-anytorch: ran black

py-langchain-core: ran black

py-pydantic: ran black

py-dalle2-pytorch: ran black

* [py-clip-anytorch] fixed license(checked_by)

* Apply suggestion from Wouter on fixing CI

Co-authored-by: Wouter Deconinck <wdconinc@gmail.com>

---------

Co-authored-by: Alex C Leute <acl2809@rit.edu>
Co-authored-by: Bernhard Kaindl <bernhardkaindl7@gmail.com>
Co-authored-by: Wouter Deconinck <wdconinc@gmail.com>
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Jen Herting 2024-10-18 14:55:27 -04:00 committed by GitHub
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commit 957c0cc9da
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# Copyright 2013-2024 Lawrence Livermore National Security, LLC and other
# Spack Project Developers. See the top-level COPYRIGHT file for details.
#
# SPDX-License-Identifier: (Apache-2.0 OR MIT)
from spack.package import *
class PyClipAnytorch(PythonPackage):
"""CLIP (Contrastive Language-Image Pre-Training) is a neural network
trained on a variety of (image, text) pairs. It can be instructed in
natural language to predict the most relevant text snippet, given an image,
without directly optimizing for the task, similarly to the zero-shot
capabilities of GPT-2 and 3. We found CLIP matches the performance of the
original ResNet50 on ImageNet "zero-shot" without using any of the original
1.28M labeled examples, overcoming several major challenges in computer
vision."""
homepage = "https://github.com/rom1504/CLIP"
# PyPI source is missing requirements.txt
url = "https://github.com/rom1504/CLIP/archive/refs/tags/2.6.0.tar.gz"
license("MIT", checked_by="qwertos")
version("2.6.0", sha256="1ac1f6ca47dfb5d4e55be8f45cc2f3bdf6415b91973a04b4529e812a8ae29bea")
depends_on("py-setuptools", type="build")
depends_on("py-ftfy", type=("build", "run"))
depends_on("py-regex", type=("build", "run"))
depends_on("py-tqdm", type=("build", "run"))
depends_on("py-torch", type=("build", "run"))
depends_on("py-torchvision", type=("build", "run"))