| { |
| "format": "oscr-script-manifest/1", |
| "repository": "github.com/goekelab/m6anet", |
| "url": "https://github.com/GoekeLab/m6anet", |
| "host": "github.com", |
| "commit": "590ec277cb48d61774f0872395099e466022e810", |
| "license": "MIT", |
| "license_confirmed_by": "license file LICENSE", |
| "redistribution": "yes", |
| "files": [ |
| { |
| "path": "LICENSE", |
| "sha256": "ca50d26b9487cd839659e2a080ce69037edf6edd0cd5d48f95c71cb04c488646", |
| "language": "License", |
| "lines": 21, |
| "truncated": false, |
| "block": 10, |
| "row": 6043 |
| }, |
| { |
| "path": "README.md", |
| "sha256": "1fd0aac76b84e5c8c259bd2a81bae4d08bc39b99bae6ef7bc08f7309b2c5b1b5", |
| "language": "Text", |
| "lines": 304, |
| "truncated": false, |
| "block": 10, |
| "row": 20013 |
| }, |
| { |
| "path": "docs/source/conf.py", |
| "sha256": "7fa1c9c5f26bc5bfcc715a7e366ddd16bc9f8ddd6c8038576095689c6a754517", |
| "language": "Python", |
| "lines": 58, |
| "truncated": false, |
| "block": 10, |
| "row": 11844 |
| }, |
| { |
| "path": "m6anet/__init__.py", |
| "sha256": "7a247948904f38547171881615fac2faede8bc67d3ea5c9d65f0043545a71cc3", |
| "language": "Python", |
| "lines": 30, |
| "truncated": false, |
| "block": 10, |
| "row": 10738 |
| }, |
| { |
| "path": "m6anet/deprecated/compute_norm_factors.py", |
| "sha256": "278e292c0030ccb54b4f8b39af725d972e03021c36693bacf619af9abb07868d", |
| "language": "Python", |
| "lines": 51, |
| "truncated": false, |
| "block": 10, |
| "row": 11720 |
| }, |
| { |
| "path": "m6anet/deprecated/dataprep.py", |
| "sha256": "7fa9209ff3d4ddb5e4195a55de3c3f5f0d47dd21d1422240e5da63f9b9c182dc", |
| "language": "Python", |
| "lines": 72, |
| "truncated": false, |
| "block": 10, |
| "row": 12503 |
| }, |
| { |
| "path": "m6anet/deprecated/inference.py", |
| "sha256": "bb8002867ecaad16fe669a6916f582e37d4593af4f23875832f8aca98b028946", |
| "language": "Python", |
| "lines": 99, |
| "truncated": false, |
| "block": 10, |
| "row": 13367 |
| }, |
| { |
| "path": "m6anet/deprecated/train.py", |
| "sha256": "46d49c4accc29bef3dca00b5cd4855c3036d733bf3c30a97f4f79aee3e1d1225", |
| "language": "Python", |
| "lines": 139, |
| "truncated": false, |
| "block": 10, |
| "row": 14138 |
| }, |
| { |
| "path": "m6anet/model/model.py", |
| "sha256": "61ee774c1f55c6bead60f140446a29ab6b76e776c973d2571eae66e677b0fac4", |
| "language": "Python", |
| "lines": 164, |
| "truncated": false, |
| "block": 10, |
| "row": 14641 |
| }, |
| { |
| "path": "m6anet/model/model_blocks/__init__.py", |
| "sha256": "81393020933c33c63ff5a241555ee99c3e886c6c2c68b29381b6ec8932e78ab9", |
| "language": "Python", |
| "lines": 11, |
| "truncated": false, |
| "block": 10, |
| "row": 10581 |
| }, |
| { |
| "path": "m6anet/model/model_blocks/blocks.py", |
| "sha256": "a2f5e7da0c397edf16f58c6a451f254181ff5c6b35909afdbe5fa0e6edc39f53", |
| "language": "Python", |
| "lines": 266, |
| "truncated": false, |
| "block": 10, |
| "row": 15354 |
| }, |
| { |
| "path": "m6anet/model/model_blocks/pooling_blocks.py", |
| "sha256": "f2912b2d3127997eb8cf279f2ee32c7e67a81b1e2fc52e38507d4b741793ee6c", |
| "language": "Python", |
| "lines": 412, |
| "truncated": false, |
| "block": 10, |
| "row": 16302 |
| }, |
| { |
| "path": "m6anet/scripts/compute_norm_factors.py", |
| "sha256": "e7c8bf1578821e1a9aa7da7ed521e1f042fc86b6089735a6597f3e97e077cd3e", |
| "language": "Python", |
| "lines": 43, |
| "truncated": false, |
| "block": 10, |
| "row": 11445 |
| }, |
| { |
| "path": "m6anet/scripts/convert.py", |
| "sha256": "d145dc796b2906a2088bf63c2f633b548414ac57489e44f7f709d0752f576692", |
| "language": "Python", |
| "lines": 34, |
| "truncated": false, |
| "block": 10, |
| "row": 10874 |
| }, |
| { |
| "path": "m6anet/scripts/dataprep.py", |
| "sha256": "8df4a78cacba2d512106ebb75a44621ff845568019a343ab93c14162d78bd827", |
| "language": "Python", |
| "lines": 70, |
| "truncated": false, |
| "block": 10, |
| "row": 12470 |
| }, |
| { |
| "path": "m6anet/scripts/inference.py", |
| "sha256": "44cbe4c80bfce0b5207b30f6ff2788b87d94d6023b62573970b9ac6b4c769caa", |
| "language": "Python", |
| "lines": 106, |
| "truncated": false, |
| "block": 10, |
| "row": 13608 |
| }, |
| { |
| "path": "m6anet/scripts/train.py", |
| "sha256": "51fd1c2bc51f2412b2cea4d6a6725970782b0c410eef2c3ee450be27e1d350b1", |
| "language": "Python", |
| "lines": 131, |
| "truncated": false, |
| "block": 10, |
| "row": 14016 |
| }, |
| { |
| "path": "m6anet/tests/conftest.py", |
| "sha256": "62639ac9d1a7f075fdbfc5e35d0e5e6e2d44acc4f8e11a714e7dbb8c42085f26", |
| "language": "Python", |
| "lines": 121, |
| "truncated": false, |
| "block": 10, |
| "row": 13090 |
| }, |
| { |
| "path": "m6anet/tests/test_dataprep.py", |
| "sha256": "7d37646d969c2baaaeb5293ac2dac55499d95db13cb7c33246e40f239cb9ba12", |
| "language": "Python", |
| "lines": 58, |
| "truncated": false, |
| "block": 10, |
| "row": 12120 |
| }, |
| { |
| "path": "m6anet/tests/test_inference.py", |
| "sha256": "7a3a93a54af3877a343305c36f982a77c4f4bc250b0d636961271753b10a5a2e", |
| "language": "Python", |
| "lines": 82, |
| "truncated": false, |
| "block": 10, |
| "row": 13512 |
| }, |
| { |
| "path": "m6anet/utils/builder.py", |
| "sha256": "98c98b4c5bfa06598178d47e14ca2240db8123b3144155caadb19fe7fc91074b", |
| "language": "Python", |
| "lines": 110, |
| "truncated": false, |
| "block": 10, |
| "row": 13784 |
| }, |
| { |
| "path": "m6anet/utils/constants.py", |
| "sha256": "5c757472a254923aea151e22e962a3a333b16ab83107858d1fbe92a6f29688da", |
| "language": "Python", |
| "lines": 37, |
| "truncated": false, |
| "block": 10, |
| "row": 12116 |
| }, |
| { |
| "path": "m6anet/utils/data_utils.py", |
| "sha256": "b929f3b7cedb42820df6daba5f2a280f05d55e924742fb68ba4547704099efd3", |
| "language": "Python", |
| "lines": 511, |
| "truncated": false, |
| "block": 10, |
| "row": 17089 |
| }, |
| { |
| "path": "m6anet/utils/dataprep_utils.py", |
| "sha256": "e96f34681b1e3519cb6df5611041c1170d87809615004a5181e2770fc5ca0fb3", |
| "language": "Python", |
| "lines": 488, |
| "truncated": false, |
| "block": 10, |
| "row": 17041 |
| }, |
| { |
| "path": "m6anet/utils/helper.py", |
| "sha256": "c19c576a3ba5023985a245dc36c48e54c031ba9209144c48978a49e5e99b6c3e", |
| "language": "Python", |
| "lines": 104, |
| "truncated": false, |
| "block": 10, |
| "row": 12797 |
| }, |
| { |
| "path": "m6anet/utils/inference_utils.py", |
| "sha256": "44a3e3158788f2958c47aba232b5d16422d157711e1529c3d991477f82069ebc", |
| "language": "Python", |
| "lines": 140, |
| "truncated": false, |
| "block": 10, |
| "row": 14846 |
| }, |
| { |
| "path": "m6anet/utils/loss_functions/loss_functions.py", |
| "sha256": "06e0b807c00f9a8313cc71c37a8f0ee03ea9cca619c881fb2dac3a841f24cc05", |
| "language": "Python", |
| "lines": 39, |
| "truncated": false, |
| "block": 10, |
| "row": 11322 |
| }, |
| { |
| "path": "m6anet/utils/norm_utils.py", |
| "sha256": "a3027517c972ef60b3e0cd48c5a9c11c3f83268662942f1bef78132f1bdfc76d", |
| "language": "Python", |
| "lines": 180, |
| "truncated": false, |
| "block": 10, |
| "row": 15156 |
| }, |
| { |
| "path": "m6anet/utils/sampler_utils.py", |
| "sha256": "901fb2c0da32d8faa0dcb5876fb43f196b006623b401031a7391aadcb76474ad", |
| "language": "Python", |
| "lines": 261, |
| "truncated": false, |
| "block": 10, |
| "row": 15644 |
| }, |
| { |
| "path": "m6anet/utils/training_utils.py", |
| "sha256": "7367f5ba9492ff7dc165d69659a2a3880cd53e04b84dfc369bea0694698a7028", |
| "language": "Python", |
| "lines": 268, |
| "truncated": false, |
| "block": 10, |
| "row": 15779 |
| }, |
| { |
| "path": "setup.py", |
| "sha256": "3d15639897619d8c421795a29c6cb04c18cc7b601659a286ec58c0039a2a2571", |
| "language": "Python", |
| "lines": 66, |
| "truncated": false, |
| "block": 10, |
| "row": 12459 |
| } |
| ] |
| } |
