Download manifests/1e/github.com__mlds-nus__uidd-jax.json from OpenScientificCodeRegistry/Database: direct link, hf CLI and curl.
- Browser
- Download file 13.5 kB
-
https://huggingface.co/datasets/OpenScientificCodeRegistry/Database/resolve/main/manifests/1e/github.com__mlds-nus__uidd-jax.json
- Command line
-
hf download hf://datasets/OpenScientificCodeRegistry/Database/manifests/1e/github.com__mlds-nus__uidd-jax.json
-
curl -L -o github.com__mlds-nus__uidd-jax.json https://huggingface.co/datasets/OpenScientificCodeRegistry/Database/resolve/main/manifests/1e/github.com__mlds-nus__uidd-jax.json
13.5 kB
| { | |
| "format": "oscr-script-manifest/1", | |
| "repository": "github.com/mlds-nus/uidd-jax", | |
| "url": "https://github.com/MLDS-NUS/UIDD-jax", | |
| "host": "github.com", | |
| "commit": "dc50d42987a2164359ada6b155c6b99932504331", | |
| "license": "MIT", | |
| "license_confirmed_by": "license file LICENSE", | |
| "redistribution": "yes", | |
| "files": [ | |
| { | |
| "path": "LICENSE", | |
| "sha256": "1b9e7656476b07cd90234c235f0c6a497518cceb070d5ff1fe98e0eec126e3bc", | |
| "language": "License", | |
| "lines": 21, | |
| "truncated": false, | |
| "block": 2, | |
| "row": 1122 | |
| }, | |
| { | |
| "path": "README.md", | |
| "sha256": "0e56045503f6758b2f3b6872fd9a9e36665ce480e58a75b623a9c418e5b0cbad", | |
| "language": "Text", | |
| "lines": 159, | |
| "truncated": false, | |
| "block": 2, | |
| "row": 2642 | |
| }, | |
| { | |
| "path": "UIDD/__init__.py", | |
| "sha256": "39a7a7a0616170d7b84631e6a447cdb76c43ca2f47108b2a62736b9a54d7be5c", | |
| "language": "Python", | |
| "lines": 14, | |
| "truncated": false, | |
| "block": 2, | |
| "row": 1654 | |
| }, | |
| { | |
| "path": "UIDD/_activations.py", | |
| "sha256": "c383c568757b53004cdf318dd080d32dd0a11452ac92a38212e1fba928bc043d", | |
| "language": "Python", | |
| "lines": 119, | |
| "truncated": false, | |
| "block": 2, | |
| "row": 1834 | |
| }, | |
| { | |
| "path": "UIDD/_layers.py", | |
| "sha256": "040a87cead40aeafc683b491519de5de7fcfbf72affc148958eea7cb8dc5fe8f", | |
| "language": "Python", | |
| "lines": 69, | |
| "truncated": false, | |
| "block": 2, | |
| "row": 1773 | |
| }, | |
| { | |
| "path": "UIDD/_losses.py", | |
| "sha256": "6ad921fc13398df64220202195cf17cb36700af5f39665a6380b3983c99e660c", | |
| "language": "Python", | |
| "lines": 254, | |
| "truncated": false, | |
| "block": 2, | |
| "row": 2037 | |
| }, | |
| { | |
| "path": "UIDD/_utils.py", | |
| "sha256": "7045505e29d7abe2cd6f64608a5bee406419e23f4d99c69c539eb1a88a5435a0", | |
| "language": "Python", | |
| "lines": 22, | |
| "truncated": false, | |
| "block": 2, | |
| "row": 1642 | |
| }, | |
| { | |
| "path": "UIDD/dynamics.py", | |
| "sha256": "56704bc06ee39ae8011312f71b765173fa179b801498cc36f87ad6a3fe2b8279", | |
| "language": "Python", | |
| "lines": 584, | |
| "truncated": false, | |
| "block": 2, | |
| "row": 2168 | |
| }, | |
| { | |
| "path": "UIDD/models.py", | |
| "sha256": "d14e001da1de563308bfec2d28153edf2a03a1c83822ec3f605c4b45449eb72a", | |
| "language": "Python", | |
| "lines": 873, | |
| "truncated": false, | |
| "block": 2, | |
| "row": 2200 | |
| }, | |
| { | |
| "path": "UIDD/trainers.py", | |
| "sha256": "48cbc730bdfedd0e068b627c7fa20d76bf565e78e0fffcef2ea576a2a851d514", | |
| "language": "Python", | |
| "lines": 485, | |
| "truncated": false, | |
| "block": 2, | |
| "row": 2158 | |
| }, | |
| { | |
| "path": "UIDD/transformations.py", | |
| "sha256": "f496fba9ea63be02a3d6f0b5c969205e354942eb888c355cea45004aa07dbf2b", | |
| "language": "Python", | |
| "lines": 181, | |
| "truncated": false, | |
| "block": 2, | |
| "row": 1966 | |
| }, | |
| { | |
| "path": "examples/20Dnonlinear_case/evaluate_mmd.py", | |
| "sha256": "6aa251150e0abfec89a2a37b4201ee87238262b43c507ba0ca6d4c99b5aff993", | |
| "language": "Python", | |
| "lines": 556, | |
| "truncated": false, | |
| "block": 2, | |
| "row": 2185 | |
| }, | |
| { | |
| "path": "examples/20Dnonlinear_case/nonlinear_case.py", | |
| "sha256": "d244913be4b7babfc2224c923913d58d935621bd7d9b2406eac836b48e1fd856", | |
| "language": "Python", | |
| "lines": 421, | |
| "truncated": false, | |
| "block": 2, | |
| "row": 2117 | |
| }, | |
| { | |
| "path": "examples/20Dnonlinear_case/onsager_reg.py", | |
| "sha256": "620cde5cee462fd4316bea5a5c7707cac5556d70572be311a3edb1b64b34e224", | |
| "language": "Python", | |
| "lines": 136, | |
| "truncated": false, | |
| "block": 2, | |
| "row": 1933 | |
| }, | |
| { | |
| "path": "examples/20Dnonlinear_case/run_all_tests.sh", | |
| "sha256": "68081a290e1c331f4b59dac4b68221b67bec5f7e2aa8ca0c7ace3bd6bda616e9", | |
| "language": "Shell", | |
| "lines": 108, | |
| "truncated": false, | |
| "block": 2, | |
| "row": 2564 | |
| }, | |
| { | |
| "path": "examples/20Dnonlinear_case/run_reg.sh", | |
| "sha256": "74179344ffb97905df7a5a3f8763a13972706f4a0051626bd1e53c670131f52e", | |
| "language": "Shell", | |
| "lines": 123, | |
| "truncated": false, | |
| "block": 2, | |
| "row": 2573 | |
| }, | |
| { | |
| "path": "examples/20Dnonlinear_case/train.sh", | |
| "sha256": "d88c72ef8be16c6e8d6540e74893fbd9874c5eb9abd7646dd22913166194f906", | |
| "language": "Shell", | |
| "lines": 123, | |
| "truncated": false, | |
| "block": 2, | |
| "row": 2569 | |
| }, | |
| { | |
| "path": "examples/SGLD-1Kaczmarz/main_Kaczmarz_scale.py", | |
| "sha256": "a34597e9a9521fa6b127dd56dba4166d081d44ff9958f3932dd88bebc047e12c", | |
| "language": "Python", | |
| "lines": 81, | |
| "truncated": false, | |
| "block": 2, | |
| "row": 1818 | |
| }, | |
| { | |
| "path": "examples/SGLD-1Kaczmarz/results.ipynb", | |
| "sha256": "5e4fb64cce86e9c4962c04cdd81ee2739bc6037ff246e85ffc17bae2365cbde4", | |
| "language": "Jupyter", | |
| "lines": 360, | |
| "truncated": false, | |
| "block": 2, | |
| "row": 1084 | |
| }, | |
| { | |
| "path": "examples/SGLD-1Kaczmarz/train.sh", | |
| "sha256": "a714c7bdc18968970bd5fa1de5887771576d622331a56e2fb3da36bf047f15a2", | |
| "language": "Shell", | |
| "lines": 14, | |
| "truncated": false, | |
| "block": 2, | |
| "row": 2512 | |
| }, | |
| { | |
| "path": "examples/SGLD-1Kaczmarz/utils_Kaczmarz.py", | |
| "sha256": "85e1e274b917f1132c66a1724a4b99e449ad0078a18184b1c96baccd74f00b76", | |
| "language": "Python", | |
| "lines": 281, | |
| "truncated": false, | |
| "block": 2, | |
| "row": 2051 | |
| }, | |
| { | |
| "path": "examples/SGLD-2ICA/main_sgld.py", | |
| "sha256": "837e48fc88539e8c4565c81245a0607d614e906768464dc95916e0e670998c7a", | |
| "language": "Python", | |
| "lines": 79, | |
| "truncated": false, | |
| "block": 2, | |
| "row": 1810 | |
| }, | |
| { | |
| "path": "examples/SGLD-2ICA/results.ipynb", | |
| "sha256": "dcaeca1abd73c9ccdef70cfbce1e0a4b12295e3e896c69087b0a9cde323e55e1", | |
| "language": "Jupyter", | |
| "lines": 301, | |
| "truncated": false, | |
| "block": 2, | |
| "row": 1073 | |
| }, | |
| { | |
| "path": "examples/SGLD-2ICA/train.sh", | |
| "sha256": "d0eac509d92986b24d6d824e4c599e5c3309b26922322eb01073efe7bff10c9b", | |
| "language": "Shell", | |
| "lines": 9, | |
| "truncated": false, | |
| "block": 2, | |
| "row": 2501 | |
| }, | |
| { | |
| "path": "examples/SGLD-2ICA/utils_sgld.py", | |
| "sha256": "5f35de4faab0bf78e3a9f08d08334e92864f934ffd92e28598663b2c223ccb82", | |
| "language": "Python", | |
| "lines": 257, | |
| "truncated": false, | |
| "block": 2, | |
| "row": 2031 | |
| }, | |
| { | |
| "path": "examples/linear_case/linear_case.py", | |
| "sha256": "9c6214b94e09b902ce8103db6e09bab575b00a94667c03eea465a5a3f8c5a341", | |
| "language": "Python", | |
| "lines": 273, | |
| "truncated": false, | |
| "block": 2, | |
| "row": 2048 | |
| }, | |
| { | |
| "path": "examples/linear_case/linear_plot.ipynb", | |
| "sha256": "e9faf7a62bb7e687087c37824f7f8f1aab45c10e3e1cb7623ac43161f2d5d08a", | |
| "language": "Jupyter", | |
| "lines": 544, | |
| "truncated": false, | |
| "block": 2, | |
| "row": 1099 | |
| }, | |
| { | |
| "path": "examples/linear_case/train.sh", | |
| "sha256": "528d94acfd9561320b591b2617942335ff825f62e9b6e0ca3fef024e306d7391", | |
| "language": "Shell", | |
| "lines": 25, | |
| "truncated": false, | |
| "block": 2, | |
| "row": 2543 | |
| }, | |
| { | |
| "path": "examples/nonlinear_case/eval.sh", | |
| "sha256": "942bc1f5fad1b5d464900d92c6267f611039cc20de7936045948987d1a7faac2", | |
| "language": "Shell", | |
| "lines": 40, | |
| "truncated": false, | |
| "block": 2, | |
| "row": 2517 | |
| }, | |
| { | |
| "path": "examples/nonlinear_case/evaluate_mmd.py", | |
| "sha256": "af875406d65fc4027d8c24e1ce9e346138128b584f68bef5ebb1416464b853d8", | |
| "language": "Python", | |
| "lines": 554, | |
| "truncated": false, | |
| "block": 2, | |
| "row": 2184 | |
| }, | |
| { | |
| "path": "examples/nonlinear_case/nonlinear_case.py", | |
| "sha256": "33a42a35d17e0b7d62a39e9918c6bacef787c16a71b435a5286f54294a7c9070", | |
| "language": "Python", | |
| "lines": 396, | |
| "truncated": false, | |
| "block": 2, | |
| "row": 2108 | |
| }, | |
| { | |
| "path": "examples/nonlinear_case/nonlinear_plot.ipynb", | |
| "sha256": "e0639a97dc0622052f9beecccb6008fe8520f91e037fd97f31b88e669215d67d", | |
| "language": "Jupyter", | |
| "lines": 164, | |
| "truncated": false, | |
| "block": 2, | |
| "row": 1039 | |
| }, | |
| { | |
| "path": "examples/nonlinear_case/nonlinear_plot_reg.ipynb", | |
| "sha256": "6b8723a6fcf4060036779df67b7e68ba54e31038ba833af7a5bddcbf31f69dda", | |
| "language": "Jupyter", | |
| "lines": 218, | |
| "truncated": false, | |
| "block": 2, | |
| "row": 1057 | |
| }, | |
| { | |
| "path": "examples/nonlinear_case/npz_to_xlsx.py", | |
| "sha256": "01f1ac745c6abda1141d666ed3745db754efcc3f6982b2f1b244b3fe8627e3f9", | |
| "language": "Python", | |
| "lines": 300, | |
| "truncated": false, | |
| "block": 2, | |
| "row": 2069 | |
| }, | |
| { | |
| "path": "examples/nonlinear_case/onsager_reg.py", | |
| "sha256": "620cde5cee462fd4316bea5a5c7707cac5556d70572be311a3edb1b64b34e224", | |
| "language": "Python", | |
| "lines": 136, | |
| "truncated": false, | |
| "block": 2, | |
| "row": 1933 | |
| }, | |
| { | |
| "path": "examples/nonlinear_case/run_reg.sh", | |
| "sha256": "8e97e8d7864db91f24c6895b562d0a5d1312e268819f78301dd583a7435d655e", | |
| "language": "Shell", | |
| "lines": 109, | |
| "truncated": false, | |
| "block": 2, | |
| "row": 2571 | |
| }, | |
| { | |
| "path": "examples/nonlinear_case/run_uidd_sensitivity.sh", | |
| "sha256": "c1edb8066ac7b2edfdbf1faf9d1d219a853d2cfaa63f4c6e65b674ea37d7c7a5", | |
| "language": "Shell", | |
| "lines": 91, | |
| "truncated": false, | |
| "block": 2, | |
| "row": 2559 | |
| }, | |
| { | |
| "path": "examples/nonlinear_case/test.sh", | |
| "sha256": "cb6bc252dd4e6d2040d41236afb93c95032d3816ab9af9785c4acb6da5b27ff0", | |
| "language": "Shell", | |
| "lines": 4, | |
| "truncated": false, | |
| "block": 2, | |
| "row": 2498 | |
| }, | |
| { | |
| "path": "examples/nonlinear_case/train.sh", | |
| "sha256": "47e08474d4524844a264cd29739f7ce24e579284a27af88b4e33da2180df832e", | |
| "language": "Shell", | |
| "lines": 110, | |
| "truncated": false, | |
| "block": 2, | |
| "row": 2561 | |
| }, | |
| { | |
| "path": "examples/nonlinear_case/uidd_sensitivity.py", | |
| "sha256": "5768757dc6032a680bd1d088ccfb70cc9a27e9e5b0acc3cb31496f7be20e19f9", | |
| "language": "Python", | |
| "lines": 856, | |
| "truncated": false, | |
| "block": 2, | |
| "row": 2205 | |
| }, | |
| { | |
| "path": "examples/nonlinear_case/uidd_sensitivity_plot.ipynb", | |
| "sha256": "5495f0c514594bbf99d5913c760ee23d24f453db003f8c3ccecb311cf5a64054", | |
| "language": "Jupyter", | |
| "lines": 383, | |
| "truncated": false, | |
| "block": 2, | |
| "row": 1085 | |
| }, | |
| { | |
| "path": "examples/polymer_dynamics_HD/Download.ipynb", | |
| "sha256": "af1d29b9db59a9ae49b7031ddf414c3f5a24f9920648d731d8bf4bdf96069aee", | |
| "language": "Jupyter", | |
| "lines": 20, | |
| "truncated": false, | |
| "block": 2, | |
| "row": 1003 | |
| }, | |
| { | |
| "path": "examples/polymer_dynamics_HD/barrier_height.ipynb", | |
| "sha256": "8689e5ceeb3bff769aa1e0bb969d6a5e7a1cbfda3628b0485417d67a652417fb", | |
| "language": "Jupyter", | |
| "lines": 322, | |
| "truncated": false, | |
| "block": 2, | |
| "row": 1079 | |
| }, | |
| { | |
| "path": "examples/polymer_dynamics_HD/main_reduced_polymerF.py", | |
| "sha256": "43f3a813d75c1baf5b5aadf668dda916d9319c608db29cf94d6730ce734f9712", | |
| "language": "Python", | |
| "lines": 94, | |
| "truncated": false, | |
| "block": 2, | |
| "row": 1851 | |
| }, | |
| { | |
| "path": "examples/polymer_dynamics_HD/plot_localEPR.ipynb", | |
| "sha256": "d27730dfdc2d123f3061d299f63f0241a06b8ab775159f5f67646bc5622dd3ed", | |
| "language": "Jupyter", | |
| "lines": 385, | |
| "truncated": false, | |
| "block": 2, | |
| "row": 1094 | |
| }, | |
| { | |
| "path": "examples/polymer_dynamics_HD/plot_potential.ipynb", | |
| "sha256": "5451dc4dd3e7d8b1bb836d7ad1830c106112c5749ff84780fff74081eeb73018", | |
| "language": "Jupyter", | |
| "lines": 150, | |
| "truncated": false, | |
| "block": 2, | |
| "row": 1037 | |
| }, | |
| { | |
| "path": "examples/polymer_dynamics_HD/plot_var.ipynb", | |
| "sha256": "92f47bcff5cfd2072a11ef790e477d705ce7ba44cad62cd66056aa9cee36c122", | |
| "language": "Jupyter", | |
| "lines": 69, | |
| "truncated": false, | |
| "block": 2, | |
| "row": 1010 | |
| }, | |
| { | |
| "path": "examples/polymer_dynamics_HD/polt_traj.ipynb", | |
| "sha256": "cc1af8a2e5db7cf5c85351c972eae683e3e4d8c76dbc9eae81a8e8e929ecba34", | |
| "language": "Jupyter", | |
| "lines": 215, | |
| "truncated": false, | |
| "block": 2, | |
| "row": 1059 | |
| }, | |
| { | |
| "path": "examples/polymer_dynamics_HD/polymer_exp_val/EPR_30V.ipynb", | |
| "sha256": "e7d526e7a509e45e667ef0b677421d3a9b374b0dde43df6a84a004c46c2149e7", | |
| "language": "Jupyter", | |
| "lines": 330, | |
| "truncated": false, | |
| "block": 2, | |
| "row": 1080 | |
| }, | |
| { | |
| "path": "examples/polymer_dynamics_HD/polymer_exp_val/EPR_60V.ipynb", | |
| "sha256": "a092a8a2ec8ff31b7e0abc118b0474bbd5d653919e7e2cfa5589d432b89023f9", | |
| "language": "Jupyter", | |
| "lines": 338, | |
| "truncated": false, | |
| "block": 2, | |
| "row": 1083 | |
| }, | |
| { | |
| "path": "examples/polymer_dynamics_HD/polymer_exp_val/plot_polymer.ipynb", | |
| "sha256": "5d42e0a0a274a80df10d6660d7cfb28f4ae9773fa72500eacadba72a8641810a", | |
| "language": "Jupyter", | |
| "lines": 67, | |
| "truncated": false, | |
| "block": 2, | |
| "row": 1009 | |
| }, | |
| { | |
| "path": "examples/polymer_dynamics_HD/results.ipynb", | |
| "sha256": "6cef582967115a2785d2bc6dd1f6be86d83abbe87b8123bfc4f98e32dfb5c43b", | |
| "language": "Jupyter", | |
| "lines": 149, | |
| "truncated": false, | |
| "block": 2, | |
| "row": 1038 | |
| }, | |
| { | |
| "path": "examples/polymer_dynamics_HD/train.sh", | |
| "sha256": "e2045a36ccd06bddfc10a8c6123211e30e3302db89e75d39cd61713f1984e128", | |
| "language": "Shell", | |
| "lines": 9, | |
| "truncated": false, | |
| "block": 2, | |
| "row": 2504 | |
| }, | |
| { | |
| "path": "examples/polymer_dynamics_HD/utils_reduced_polymer.py", | |
| "sha256": "a187ea16ee8aaeb61a3fc44310bcf0b58c6e41af4556c17a88dbce1ce5d8730e", | |
| "language": "Python", | |
| "lines": 338, | |
| "truncated": false, | |
| "block": 2, | |
| "row": 2076 | |
| }, | |
| { | |
| "path": "examples/utils/data.py", | |
| "sha256": "9fa0ecd85108e927327f895f9f98443927b715c51101629f0476935f581cc6c1", | |
| "language": "Python", | |
| "lines": 68, | |
| "truncated": false, | |
| "block": 2, | |
| "row": 1788 | |
| }, | |
| { | |
| "path": "examples/utils/sde.py", | |
| "sha256": "f3c5b3237097eab9bb3f7b9d7a1906c9228e56b286e8f9efbf80cddb209be969", | |
| "language": "Python", | |
| "lines": 127, | |
| "truncated": false, | |
| "block": 2, | |
| "row": 1875 | |
| } | |
| ] | |
| } |