Wheelodex » Projects » mead-layers

mead-layers

View on PyPI — Reverse Dependencies (1)

2.4.2 mead_layers-2.4.2-py3-none-any.whl
2.2.2 mead_layers-2.2.2-py3-none-any.whl

Wheel Details

Project: mead-layers
Version: 2.2.2
Filename: mead_layers-2.2.2-py3-none-any.whl
Download: [link]
Size: 134975
MD5: 156e97c036e4fb0946494b04bef6004c
SHA256: a9d42dea443308ffb9e2ec1fbc3704e8816572a19bf92533f2ddad108ba41ea7
Uploaded: 2020-10-19 12:50:55 +0000

dist-info

METADATA · WHEEL · RECORD · top_level.txt · entry_points.txt

METADATA

Metadata-Version: 2.1
Name: mead-layers
Version: 2.2.2
Summary: Reusable Deep-Learning layers for NLP
Author: mead-ml
Author-Email: mead.baseline[at]gmail.com
Home-Page: https://www.github.com/mead-ml/mead-layers
Download-Url: https://www.github.com/mead-ml/mead-layers/archive/2.2.2.tar.gz
License: Apache 2.0
Keywords: deep-learning,nlp,pytorch,tensorflow
Classifier: Topic :: Scientific/Engineering :: Artificial Intelligence
Classifier: Environment :: Console
Classifier: Programming Language :: Python :: 3.6
Classifier: Intended Audience :: Developers
Classifier: Natural Language :: English
Classifier: Development Status :: 3 - Alpha
Classifier: Programming Language :: Python :: 3.5
Classifier: Operating System :: OS Independent
Classifier: License :: OSI Approved :: Apache Software License
Classifier: Intended Audience :: Science/Research
Classifier: Programming Language :: Python :: 3.7
Requires-Dist: numpy
Requires-Dist: matplotlib; extra == "plot"
Requires-Dist: pytest; extra == "test"
Requires-Dist: mock; extra == "test"
Requires-Dist: contextdecorator; extra == "test"
Requires-Dist: pytest-forked; extra == "test"
Requires-Dist: tensorflow-addons; extra == "tf2"
Requires-Dist: pyyaml; extra == "yaml"
Provides-Extra: plot
Provides-Extra: test
Provides-Extra: tf2
Provides-Extra: yaml
Description-Content-Type: text/markdown
[Description omitted; length: 449 characters]

WHEEL

Wheel-Version: 1.0
Generator: bdist_wheel (0.35.1)
Root-Is-Purelib: true
Tag: py3-none-any

RECORD

Path Digest Size
eight_mile/__init__.py sha256=SPQs-_d0nlmbN0asydR8AjcsNCDCGlvwET8kMeXKiow 43
eight_mile/bleu.py sha256=mcrlcIXyUaeb24tOL89rgaQYoUveShHUq7C071FIt8U 12791
eight_mile/confusion.py sha256=Z9XAbLDpPDh__cCXEdiRD-DzmLBvRWswZq5w3PUIqTE 8623
eight_mile/conlleval.py sha256=MdJPlxHEDSBq5ytDVsUpwhFajVeq4PrRXMatQLrpnyU 4594
eight_mile/downloads.py sha256=XDoNdAcT3plHvU_cByaGFtFmAwkNC5u1LIpDCngyOpk 16349
eight_mile/embeddings.py sha256=I070X6EqlbqdX7ZBu3UAO10gpc_CbCpPR2CAWn1WSE4 15536
eight_mile/metrics.py sha256=VrTTNgPEDCMjENpvK5Z8jHZOYLucqYzRBGAaj8nyrPY 2582
eight_mile/optz.py sha256=45HdWwlAdEgGH1NXFrMzsgeG5Lyd1uxa9vWocXLaA7w 5299
eight_mile/progress.py sha256=8umBYOtWIoblK0vOiMuTkTCxZ26MiSQmSl3gEXNu7W8 3993
eight_mile/utils.py sha256=Px8vDYifl3xKgbYTUXGI980qgxwpM1z85FKW8kmDqiY 64325
eight_mile/version.py sha256=toAYzE_ok1SiBE0AqAVdW0O8YCXCwcx0w4JATYQuJOg 22
eight_mile/calibration/__init__.py sha256=YqHwhCwGPPuSpu6l4SIDDF9XtbwzclBKJRhvReYFR5k 174
eight_mile/calibration/calibration.py sha256=NGpYwl7xGxUxWhxC-sMRflrWsVkVRWYLsAweL0V_Fu0 3070
eight_mile/calibration/metrics/__init__.py sha256=NDvy-kjQdN4tRX8AXCoIcchp0ta8uTi-GKjuY6LXghY 115
eight_mile/calibration/metrics/calibration_error.py sha256=vfwXpMbo6L08hZqpqHSmcDAbV4FpItxEpIFStK6hKNE 1960
eight_mile/calibration/plot/__init__.py sha256=0uRukGlYxI7ECg6oN_aYJL1rZ36jzG9NkKD0soSs7Mg 181
eight_mile/calibration/plot/confidence_histogram.py sha256=rNRQjwpncgaF3fVsvPp_gqwsAe2kSI_mUzUUMK63kbU 4907
eight_mile/calibration/plot/reliability_diagram.py sha256=2TKQxbTQKoZ5nlX6oucVRXVwCnqnm5pQXmA9ntmBvbI 9855
eight_mile/pytorch/__init__.py sha256=47DEQpj8HBSa-_TImW-5JCeuQeRkm5NMpJWZG3hSuFU 0
eight_mile/pytorch/embeddings.py sha256=S_tQBR9eRy2Wy2wl19cf-S_971RXHxjoGmSJHsEoy4U 15211
eight_mile/pytorch/layers.py sha256=QERVfLM3jqRRf4qZROxkr_ygkQW7NCzsakMWGKE6QX4 159109
eight_mile/pytorch/optz.py sha256=1uSs74rV3r4Axr3HZkXPCD7xLAwi7bBlWUsofOsGkZM 8924
eight_mile/pytorch/serialize.py sha256=a2QzL4pACSuJgznOKbv-t0-1yPfOpmOKA_1nA8hWHoA 28420
eight_mile/tf/__init__.py sha256=47DEQpj8HBSa-_TImW-5JCeuQeRkm5NMpJWZG3hSuFU 0
eight_mile/tf/embeddings.py sha256=iorYs57zTKE3y-aHerHuKqX5_YnVu-STZVYVEuxbLG8 18009
eight_mile/tf/layers.py sha256=aZBX61OpILzhcHjnqqzw0SZ6uCdXH_bVjMtkqzwLjDU 151052
eight_mile/tf/optz.py sha256=irHTrTAPBO2CBroqyNNux8vW9hu46Ry7pDJJT8nhtBE 34475
eight_mile/tf/serialize.py sha256=N77t69Zn1l5IMKR4U7YK4jZbfAndT4rn4bZ9JNaVUgI 14456
mead_layers-2.2.2.dist-info/LICENSE sha256=tAkwu8-AdEyGxGoSvJ2gVmQdcicWw3j1ZZueVV74M-E 11357
mead_layers-2.2.2.dist-info/METADATA sha256=aRGYsBmNxDgG6vsNTYj83EHVzxyvCW1Vb9R2rq4S8AU 1820
mead_layers-2.2.2.dist-info/NOTICE sha256=tjEa-9rzpN96J1IK49OIxnjXIqeG4YQbITmOX2fNKO0 548
mead_layers-2.2.2.dist-info/WHEEL sha256=EVRjI69F5qVjm_YgqcTXPnTAv3BfSUr0WVAHuSP3Xoo 92
mead_layers-2.2.2.dist-info/entry_points.txt sha256=HeQFefCotKqQ3xfQAM1T30c0L8hhqiGJ4ZFICA-Rdl4 84
mead_layers-2.2.2.dist-info/top_level.txt sha256=13RZrAcAUCMLkG_jJ6stmyzBM9XQVIEOHOp1bke_L9Q 11
mead_layers-2.2.2.dist-info/RECORD — —

top_level.txt

eight_mile

entry_points.txt

[console_scripts]
bleu = eight_mile.bleu:mainconlleval = eight_mile.conlleval:main