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bio-embeddings-tape-proteins

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0.5 bio_embeddings_tape_proteins-0.5-py3-none-any.whl

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Project: bio-embeddings-tape-proteins
Version: 0.5
Filename: bio_embeddings_tape_proteins-0.5-py3-none-any.whl
Download: [link]
Size: 69166
MD5: 87c0afcba46e61150dc3a0df3918fa9b
SHA256: 12b3d3cf675f130bdc41bf7b746f9571a4381b06fca0a65f0d28d9f0bada9233
Uploaded: 2021-07-11 12:13:44 +0000

dist-info

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

METADATA

Metadata-Version: 2.1
Name: bio-embeddings-tape-proteins
Version: 0.5
Summary: Repostory of Protein Benchmarking and Modeling
Author: Roshan Rao, Nick Bhattacharya, Neil Thomas
Author-Email: roshan_rao[at]berkeley.edu, nickbhat[at]berkeley.edu, nthomas[at]berkeley.edu
Home-Page: https://github.com/songlab-cal/tape
License: BSD 3-Clause License Copyright (c) 2018, Regents of the University of California All rights reserved. Redistribution and use in source and binary forms, with or without modification, are permitted provided that the following conditions are met: * Redistributions of source code must retain the above copyright notice, this list of conditions and the following disclaimer. * Redistributions in binary form must reproduce the above copyright notice, this list of conditions and the following disclaimer in the documentation and/or other materials provided with the distribution. * Neither the name of the copyright holder nor the names of its contributors may be used to endorse or promote products derived from this software without specific prior written permission. THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS" AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT HOLDER OR CONTRIBUTORS BE LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.
Keywords: Proteins,Deep Learning,Pytorch,TAPE
Classifier: Programming Language :: Python :: 3.6
Classifier: Programming Language :: Python :: 3.7
Classifier: Programming Language :: Python :: 3.8
Classifier: Operating System :: POSIX :: Linux
Classifier: Intended Audience :: Developers
Classifier: Intended Audience :: Science/Research
Classifier: Topic :: Scientific/Engineering :: Artificial Intelligence
Classifier: Topic :: Scientific/Engineering :: Bio-Informatics
Requires-Dist: torch (<1.10,>=1.0)
Requires-Dist: tqdm
Requires-Dist: tensorboardX
Requires-Dist: scipy
Requires-Dist: lmdb
Requires-Dist: boto3
Requires-Dist: requests
Requires-Dist: biopython
Requires-Dist: filelock
License-File: LICENSE
[No description]

WHEEL

Wheel-Version: 1.0
Generator: bdist_wheel (0.36.2)
Root-Is-Purelib: true
Tag: py3-none-any

RECORD

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tape/metrics.py sha256=Kbs3NiDd492AQpjlTXfP9IHTiGARo6w23X26ihqvdn8 1726
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tape/registry.py sha256=rAkVxuZsA4DkJvGvt5SXWpaNxJLbiUwVydj7sCln1VY 9008
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tape/visualization.py sha256=_trilhK-TYQ2_0SbWquP44g29svB5jYPDU1dCSUTXBs 3946
tape/models/__init__.py sha256=bYbbp1iDoeJFldbyOM8ageEAKKwIKgO8aIHM57t8xr4 1712
tape/models/file_utils.py sha256=vm5Oguhv0zFvPogU1pHGcWESQIY7MPmzP2-oScXwyrQ 12228
tape/models/modeling_bert.py sha256=oBQKB-qlEfGQM0iDa2_P3d6PYnoGu6xdDsoWCsHY9x8 24199
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tape/models/modeling_onehot.py sha256=VG-rOTHSrntqDuBv9kxrzt8tWLRg5aqQvmI7CJW-_kM 5367
tape/models/modeling_resnet.py sha256=_Jfwg_BZ9bWH1WiqDDL3zKIn4kcWCn4i46ForvFGnr4 12858
tape/models/modeling_trrosetta.py sha256=vJasolV3yfsuMdyo-9f9n_x6QaeB0fGSk2K8R9LiEH0 12733
tape/models/modeling_unirep.py sha256=fLfrWajiy9OX-pyRYxW4-LEoYd4kNQu95D5GEsTv8B8 9137
tape/models/modeling_utils.py sha256=2DKzM0-XUy05stA1cT5Z0lm5S0qNkjttPTG1r96BwyI 38627
tape/utils/__init__.py sha256=SmCYbhcdyaB4qeWlO0GisepYyT6Uqkzik83tt5AnDeI 1124
tape/utils/_sampler.py sha256=jtBbMUX4F_iCwShySbinZSFB_kSY1dA0SWss2pp3ZjA 3906
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tape/utils/setup_utils.py sha256=ZW-JxpcE7qNVf4NA5lOqTfHJm7I6OKrn1_mcsue3igs 4424
tape/utils/utils.py sha256=3Pu4pFlJFzf78R1UMs37qKPjedCIrbWOOivvbVSnUDU 11325
bio_embeddings_tape_proteins-0.5.dist-info/LICENSE sha256=sDF39Wp9F8eC39hADKSinCcvRv0u1IVp2RlGgvJ-cAE 1539
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bio_embeddings_tape_proteins-0.5.dist-info/RECORD — —

top_level.txt

tape

entry_points.txt

[console_scripts]
tape-embed = tape.main:run_embed
tape-eval = tape.main:run_eval
tape-train = tape.main:run_train
tape-train-distributed = tape.main:run_train_distributed