# This file created by conda-build 24.1.2
# meta.yaml template originally from:
# /feedstock/recipe, last modified Tue Jul  2 12:45:15 2024
# ------------------------------------------------

package:
  name: pytorch-lightning
  version: 2.3.0
source:
  sha256: 89caf90e3543b314508493f26e0eca8d5e10e43e3d9e6c143acd8ddceb584ce2
  url: https://pypi.io/packages/source/p/pytorch-lightning/pytorch-lightning-2.3.0.tar.gz
build:
  number: '0'
  script: /croot/pytorch-lightning_1719924323519/_h_env_placehold_placehold_placehold_placehold_placehold_placehold_placehold_placehold_placehold_placehold_placehold_placehold_placehold_placehold_placehold_placehold_placehold_placehold_placehold_placehold_placehold/bin/python
    -m pip install . -vv --no-deps --no-build-isolation
  string: py312h06a4308_0
requirements:
  host:
    - _libgcc_mutex 0.1 main
    - _openmp_mutex 5.1 1_gnu
    - bzip2 1.0.8 h5eee18b_6
    - ca-certificates 2024.3.11 h06a4308_0
    - expat 2.6.2 h6a678d5_0
    - ld_impl_linux-64 2.38 h1181459_1
    - libffi 3.4.4 h6a678d5_1
    - libgcc-ng 11.2.0 h1234567_1
    - libgomp 11.2.0 h1234567_1
    - libstdcxx-ng 11.2.0 h1234567_1
    - libuuid 1.41.5 h5eee18b_0
    - ncurses 6.4 h6a678d5_0
    - openssl 3.0.14 h5eee18b_0
    - pip 24.0 py312h06a4308_0
    - python 3.12.4 h5148396_1
    - readline 8.2 h5eee18b_0
    - setuptools 69.5.1 py312h06a4308_0
    - sqlite 3.45.3 h5eee18b_0
    - tk 8.6.14 h39e8969_0
    - tzdata 2024a h04d1e81_0
    - wheel 0.43.0 py312h06a4308_0
    - xz 5.4.6 h5eee18b_1
    - zlib 1.2.13 h5eee18b_1
  run:
    - fsspec >=2022.5.0
    - lightning-utilities >=0.8.0
    - numpy >=1.17.2
    - packaging >=20.0
    - python >=3.12,<3.13.0a0
    - pytorch >=2.0.0
    - pyyaml >=5.4
    - torchmetrics >=0.7.0
    - tqdm >=4.57.0
    - typing-extensions >=4.4.0
test:
  commands:
    - pip check
  imports:
    - pytorch_lightning
  requires:
    - pip
about:
  description: 'Lightning is a way to organize your PyTorch code to decouple the science
    code from the engineering.

    It''s more of a style-guide than a framework.


    In Lightning, you organize your code into 3 distinct categories:


    1. Research code (goes in the LightningModule).

    2. Engineering code (you delete, and is handled by the Trainer).

    3. Non-essential research code (logging, etc. this goes in Callbacks).


    Although your research/production project might start simple, once you add things
    like GPU AND TPU training,

    16-bit precision, etc, you end up spending more time engineering than researching.

    Lightning automates AND rigorously tests those parts for you.


    Overall, Lightning guarantees rigorously tested, correct, modern best practices
    for the automated parts.

    '
  dev_url: https://github.com/Lightning-AI/lightning
  doc_url: https://pytorch-lightning.readthedocs.io
  home: https://lightning.ai/
  license: Apache-2.0
  license_family: Apache
  license_file: LICENSE
  summary: PyTorch Lightning is the lightweight PyTorch wrapper for ML researchers.
    Scale your models. Write less boilerplate.
extra:
  copy_test_source_files: true
  final: true
  flow_run_id: 40cf5ac4-7023-400c-a763-8c9367a0e6b9
  recipe-maintainers:
    - borda
    - carmocca
    - williamFalcon
  remote_url: git@github.com:AnacondaRecipes/pytorch-lightning-feedstock.git
  sha: 2ee7786367f569ca0b9fcaa4cc68ecaca171c5d4
