BigDL Orca helps to seamlessly scale out TensorFlow and PyTorch pipelines for distributed Big Data.

See here for more information.

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  • Released:
Latest release

1 maintainer

PyPI data
Data sourced directly from PyPI's database.
Avatar for kai_intel from gravatar.com kai_intel

Credits

Author: BigDL Authors

License

Apache Software License (Apache License, Version 2.0)

Classifiers

Report project as malware

Metadata

Project links

Key dates

PyPI data
Data sourced directly from PyPI's database.
  • Released:
Latest release

1 maintainer

PyPI data
Data sourced directly from PyPI's database.
Avatar for kai_intel from gravatar.com kai_intel

Credits

Author: BigDL Authors

License

Apache Software License (Apache License, Version 2.0)

Classifiers

Report project as malware

Release files for bigdl-orca-spark2 2.4.0

For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.

Built distributions (wheels)

Table of built distributions (wheels) for bigdl-orca-spark2 2.4.0
File Interpreter ABI Platform
bigdl_orca_spark2-2.4.0-py3-none-manylinux1_x86_64.whl 20.4 MB Python 3 none Linux glibc 2.5+ x86-64 Details
bigdl_orca_spark2-2.4.0-py3-none-macosx_10_11_x86_64.whl 24.5 MB Python 3 none macOS 10.11+ x86-64 Details

Total release size: 44.9 MB

Release files / bigdl_orca_spark2-2.4.0-py3-none-manylinux1_x86_64.whl

Download URL bigdl_orca_spark2-2.4.0-py3-none-manylinux1_x86_64.whl
Size 20.4 MB
Tags Linux glibc 2.5+ x86-64 Python 3
SHA-256 checksum
How to use checksums 		b6399c70075e5d35515755baca051cba31028800f057401326ce64f44f4838d9
BLAKE2b-256 checksum
How to use checksums 		0a4ef66e1562ff1e81276981525357d3cfd3c1f336363365a3dfbbc5674ad0d0
Upload date
Uploaded using Trusted Publishing?
What is trusted publishing? 		No
Uploaded via twine/4.0.2 CPython/3.7.15

Release files / bigdl_orca_spark2-2.4.0-py3-none-macosx_10_11_x86_64.whl

Download URL bigdl_orca_spark2-2.4.0-py3-none-macosx_10_11_x86_64.whl
Size 24.5 MB
Tags Python 3 macOS 10.11+ x86-64
SHA-256 checksum
How to use checksums 		f6a1796ae12034b7aad186d0560597e8ee19b50991dbe5858d54181ceac26a53
BLAKE2b-256 checksum
How to use checksums 		641745b03c90f6b4eb0d26bb3d417fdbfa8684abc2c69e569a02925246ebc104
Upload date
Uploaded using Trusted Publishing?
What is trusted publishing? 		No
Uploaded via twine/4.0.2 CPython/3.7.15

Release history Release notifications | RSS feed

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