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swh:1:snp:4e3e7077647a709f15b8c1b32ce7100175d0580b
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    • 0.5.1
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  • meta.yaml
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To reference or cite the objects present in the Software Heritage archive, permalinks based on SoftWare Hash IDentifiers (SWHIDs) must be used.
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(requires biblatex-software package)
Generating citation ...
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Generating citation ...
Tip revision: bfda61015d0817d259ec539d4fcf876e81a5ed1d authored by Jean Kossaifi on 14 April 2021, 11:14:29 UTC
Pypi Worflow: use correct token for test pypi
Tip revision: bfda610
meta.yaml
package:
  name: tensorly
  version: "0.5.1"

source:
  path: ../

build:
  number: 0
  noarch: python
  script: python -m pip install --no-deps --ignore-installed .

requirements:
  build:
    - python >=3.6
    - setuptools
    - pip

  run:
    - python
    - numpy
    - scipy

test:
  requires:
    - pytest
    # NumPy requires nosetests e.g. for assert_raises.....
    - nose

  commands:
    - TENSORLY_BACKEND='numpy' pytest -v $SP_DIR/tensorly

about:
  home: https://github.com/tensorly/tensorly/
  license: BSD
  summary: "Tensor learning in Python"
  description: |
    TensorLy is a Python library that aims at making tensor learning simple 
    and accessible. It allows to easily perform tensor decomposition, 
    tensor learning and tensor algebra. Its backend system allows to 
    seamlessly perform computation with NumPy, MXNet, PyTorch, TensorFlow,
    CuPy or JAX, and run methods at scale on CPU or GPU.

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