Wheelodex » Projects » autotm

autotm

View on PyPI — Reverse Dependencies (0)

0.2.3.4 autotm-0.2.3.4-py3-none-any.whl

Wheel Details

Project: autotm
Version: 0.2.3.4
Filename: autotm-0.2.3.4-py3-none-any.whl
Download: [link]
Size: 78534
MD5: 1c2b24578dc459c891dfdd44ff18b910
SHA256: e30d4a64699cc8a4288e97bddaf18241b93a060c884d98734a78dc2782d7a75f
Uploaded: 2024-06-08 19:31:48 +0000

dist-info

METADATA · WHEEL · RECORD · entry_points.txt

METADATA

Metadata-Version: 2.1
Name: autotm
Version: 0.2.3.4
Summary: Automatic hyperparameters tuning for topic models (ARTM approach) using evolutionary algorithms
Author: Khodorchenko Maria
Author-Email: mariyaxod[at]yandex.ru
Home-Page: https://autotm.readthedocs.io/en/latest/
Project-Url: Repository, https://github.com/ngc436/AutoTM
License: Apache-2.0
Classifier: License :: OSI Approved :: Apache Software License
Classifier: Programming Language :: Python :: 3
Classifier: Programming Language :: Python :: 3.9
Classifier: Programming Language :: Python :: 3.10
Classifier: Programming Language :: Python :: 3.11
Requires-Python: >=3.9,<3.12
Requires-Dist: PyMySQL
Requires-Dist: PyYAML (==5.3.1)
Requires-Dist: bigartm (==0.9.2)
Requires-Dist: billiard
Requires-Dist: celery (>=4.4.7)
Requires-Dist: click (==8.0.1)
Requires-Dist: dataclasses-json
Requires-Dist: dill
Requires-Dist: gensim (<5.0.0,>=4.1.2)
Requires-Dist: hyperopt
Requires-Dist: jinja2 (==3.0)
Requires-Dist: mlflow
Requires-Dist: nltk
Requires-Dist: numpy
Requires-Dist: openai (<2.0.0,>=1.31.0)
Requires-Dist: pandas
Requires-Dist: plotly
Requires-Dist: protobuf (<=3.20.0)
Requires-Dist: psycopg2-binary
Requires-Dist: pydantic (==2.6.0)
Requires-Dist: pymongo (==3.11.3)
Requires-Dist: pymystem3
Requires-Dist: pytest
Requires-Dist: redis (==3.5.3)
Requires-Dist: scikit-learn (<2.0.0,>=1.1.1)
Requires-Dist: scipy (<=1.10.1)
Requires-Dist: seaborn (<0.14.0,>=0.13.2)
Requires-Dist: spacy (>=3.5)
Requires-Dist: spacy-langdetect
Requires-Dist: tqdm (==4.50.2)
Description-Content-Type: text/markdown
[Description omitted; length: 4855 characters]

WHEEL

Wheel-Version: 1.0
Generator: poetry-core 1.5.2
Root-Is-Purelib: true
Tag: py3-none-any

RECORD

Path Digest Size
autotm/__init__.py sha256=47DEQpj8HBSa-_TImW-5JCeuQeRkm5NMpJWZG3hSuFU 0
autotm/abstract_params.py sha256=Ay2udlIgjlEQ_XXBLncOBByvk-YYF0dpbMLNLaHC1FQ 856
autotm/algorithms_for_tuning/__init__.py sha256=47DEQpj8HBSa-_TImW-5JCeuQeRkm5NMpJWZG3hSuFU 0
autotm/algorithms_for_tuning/bayesian_optimization/__init__.py sha256=47DEQpj8HBSa-_TImW-5JCeuQeRkm5NMpJWZG3hSuFU 0
autotm/algorithms_for_tuning/bayesian_optimization/bayes_opt.py sha256=3Z75MdiP9dBfHsxtUrFKOSD0AevBmVGq1WwKMoI60-I 5562
autotm/algorithms_for_tuning/genetic_algorithm/__init__.py sha256=47DEQpj8HBSa-_TImW-5JCeuQeRkm5NMpJWZG3hSuFU 0
autotm/algorithms_for_tuning/genetic_algorithm/config.yaml sha256=Kn7PPMYQoAcr7hBSfWvQBU9P7K2rksDZ2XO9-jc4HF8 84
autotm/algorithms_for_tuning/genetic_algorithm/crossover.py sha256=_sSa8bqy5hA0NbRsTLhip2Wcu29-qzSFQ_PPs5q-uqg 3936
autotm/algorithms_for_tuning/genetic_algorithm/ga.py sha256=Bqbokd3z62T5RtvRcWzZt4jFaA8_98lBBs6bQq5Gtak 24826
autotm/algorithms_for_tuning/genetic_algorithm/genetic_algorithm.py sha256=6RNFPEHkRXM2PGlpMxdp35taRpSmHT3NQmkUz4p8gW0 8763
autotm/algorithms_for_tuning/genetic_algorithm/mutation.py sha256=pMNr406gTK2N6mwVljwI-uzXyr8wdJv7WqQzCAsyGN4 5047
autotm/algorithms_for_tuning/genetic_algorithm/selection.py sha256=ChtqKefNftZsFOwshmzi4pW3XXW41MvwhayrlvN0gBE 3108
autotm/algorithms_for_tuning/genetic_algorithm/statistics_collector.py sha256=2OvumLYn0dFe7cR9Y9LQXv_qyOI04vNAEwHw9eY0hJc 540
autotm/algorithms_for_tuning/genetic_algorithm/strategy.py sha256=-7zks2as33K0Ox1UvQWIGVRIntGNsyztirxEkyKHF3A 5203
autotm/algorithms_for_tuning/genetic_algorithm/surrogate.py sha256=CSN0pHVKH3m7cjUKuNMrYqY9d20ascRYa65No9U65Lw 5242
autotm/algorithms_for_tuning/individuals.py sha256=u6ms6snvGyjWYK57LXD2XuUwU67VUyzptgdOl7x5HkY 4910
autotm/algorithms_for_tuning/nelder_mead_optimization/__init__.py sha256=47DEQpj8HBSa-_TImW-5JCeuQeRkm5NMpJWZG3hSuFU 0
autotm/algorithms_for_tuning/nelder_mead_optimization/nelder_mead.py sha256=yH-JHH9-mvB94hdEkvWdk2TnSVcVl_8fPaCl3OODilE 3493
autotm/base.py sha256=0mR2lg4_hLaJf7sy6aex4Ob0neiXyOweXbPJageTyQE 12761
autotm/batch_vect_utils.py sha256=FTPxql6sg10tGRul_Avp4EfhqAkw9KZFB_3yNVETy_E 1506
autotm/clustering.py sha256=0xdz5sMncu-lM9DEH5_K8nsbThKy4OEHAuDZTbSb9oc 1003
autotm/content_splitter.py sha256=UrB8ODcQGbhYnIwpIakMVmTpuD0UECKBSHqRuIFB2uE 342
autotm/data_generator/synthetic_data_generation.ipynb sha256=uV_9ZZEQ9aFX6BSUf2TjvLFkuzy--9ZshLWbkNaL_fk 1322
autotm/fitness/__init__.py sha256=Ya6kQ1cgDsglek9uCMohDilr_Mcgdcq-Pv1FVCzeZ5I 260
autotm/fitness/base_score.py sha256=uKLMtyfo6xZ54LftlQ58-OOZWziSCKWaijIAZmDtuu4 7373
autotm/fitness/cluster_tasks.py sha256=0GfXx7bFZLDb0K8bvbSQz6GJkj6KFSDbZTIC8Q-eONw 8437
autotm/fitness/estimator.py sha256=jbJqHBkMT2tfNQpsq1ZlDiw3x4IisyHi4Rrg5CvSWoE 12419
autotm/fitness/external_scores.py sha256=sGJU4vFknA1qMr_pv5V3tNqKgVtYpYxjSYPMibGE8v0 1720
autotm/fitness/local_tasks.py sha256=Z19WQsCBb6upWzcug_qlb3p_VLux8jqOZn_NSHuDj2I 3179
autotm/fitness/tm.py sha256=lwkdBJhTr4aWZhzMRsZ9oBM4-zGeySp3Yk47C-ZBqTc 34588
autotm/graph_ga.py sha256=gLOQlKnNfhlP_06C2TcLLWMLZRBvpfaVWAVvvFzbWH4 10081
autotm/infer.py sha256=jJ099x4-7eYqz8YtXWhMfr8AIM7uP8Eg_1bthbDytc8 6251
autotm/main.py sha256=27GH_Q6TTrYa2hZVJoiR8N_3DTxMj0ADegKUvJ9P4Sg 5299
autotm/main_fitness_worker.py sha256=qJa0ZZv0HR2AxygXiD_foUHDs4niP9fXiy-37xONFl8 733
autotm/make-recovery-file.py sha256=tFztG7nqSSTeQse2g0T13NGpXWfWVU7mDWCPzr0K7MA 1241
autotm/params.py sha256=PuSkxuMzfZQuKDIe-QWoOoT0xo5c28h7lPs5YX5nCJc 12702
autotm/params_logging_utils.py sha256=Bi5WvbIW8-hBwJU1fktXQz6pEDVmHtw55VI_TtBMnRU 6848
autotm/pipeline.py sha256=a71_HTg8zfPMYBS6_H3sT2q-h5QpvZvufoij_KBUIEA 2632
autotm/preprocessing/__init__.py sha256=U6Kek5qUlq-wYmr1eidHE3ZoH5qfAyqBliM_ZW-Mwpk 126
autotm/preprocessing/cooc.py sha256=E-K6fYR-w4lxgp55yGKROAIVTX_sMn-y9AX7NukEzNU 5491
autotm/preprocessing/dictionaries_preparation.py sha256=WR9A8FrE6PkC7n-xFQLes_LuvkPvnvumfSvieoCUdts 13565
autotm/preprocessing/text_preprocessing.py sha256=EYYaLN8_6gPjzZ4uJGn_Z5m-Kcu2YHns0zmbxl4PnXw 5667
autotm/schemas.py sha256=xj2-F5IAsrPYWFakdrxTAk70UQzziWwupPmKiQs7wrY 817
autotm/utils.py sha256=ZnqjdpwLFRwpZn-iGGDy3IVMyFD5icJzvGVOWLE5RwQ 6049
autotm/visualization/__init__.py sha256=47DEQpj8HBSa-_TImW-5JCeuQeRkm5NMpJWZG3hSuFU 0
autotm/visualization/dynamic_tracker.py sha256=9XXUqCzPzOwefFRbXc0hKBwOfBGZHnxL0tbPZd7UYGQ 10251
autotm-0.2.3.4.dist-info/LICENSE sha256=do03GjPBpGjyNK8WgrCMxS7DZPUs3UGLBiR1WnJK0BU 1509
autotm-0.2.3.4.dist-info/METADATA sha256=BQSWfOhFG59UeHBz5knwLZcNNAwIC5DkoH57D1aTmd0 6428
autotm-0.2.3.4.dist-info/WHEEL sha256=7Z8_27uaHI_UZAc4Uox4PpBhQ9Y5_modZXWMxtUi4NU 88
autotm-0.2.3.4.dist-info/entry_points.txt sha256=JVjT_p03BWfSOarpIvm6VcrqMyteTrdzQCWXbNo9YQk 92
autotm-0.2.3.4.dist-info/RECORD — —

entry_points.txt

[console_scripts]
autotmctl = autotm.main:cli
fitness-worker = autotm.main_fitness_worker:main