sha256 stringlengths 64 64 | language stringclasses 28
values | size int32 1 491k | lines int32 1 23.2k | content stringlengths 1 200k |
|---|---|---|---|---|
94826372028328980aadcf670649394bb7736936966af6e9c93022ec704d71e6 | Python | 23 | 1 | from .model import PAN
|
bd03fa9431a0c2256a5e5930b3189fffcd377d016411b717d315c3c8c43f6936 | Python | 23 | 1 | """Recipes for EMT."""
|
d0261172f6d25e7cfd4288ebf6ecacebb2b331a09aa6de62ba7b1a7fe9ea1ebb | Python | 23 | 1 | from .BP import detect
|
f3437cada05eaafc4be0cf432811184e2878c91560992ef6f8525ed82c223437 | Python | 23 | 1 | __version__ = "0.3.21"
|
05eb4e4a55eb9ccd17f6eb71084fef386db6f8d0cec8be620a792b221fca027d | Python | 24 | 1 | """Recipes for DFTB+"""
|
44a7e0d29bd660e61a69be3d00795646ef869bbeab50b8e05bb9504dede4d666 | Python | 24 | 1 | """Recipes for ORCA."""
|
509ea5fadf55172e53e1fbcdb19cfacc2f2abd5e567a839af1e4a249ac4a55f4 | Python | 24 | 1 | """Recipes for GULP."""
|
6807a03c42fadc0e6782fa5a5616b943e7b784b4868193f8a1d621a8d63d3bb9 | Python | 24 | 1 | __author__ = 'martinez'
|
9a189fd0f890141094012670fa34533f6874aac3cc0668ee4e572a04c28e4064 | Python | 24 | 1 | __all__ = ['IoU_score']
|
afc68320e131d19bf6cb17ff0063fb98ac304924450171bf7f200f417012517b | Python | 24 | 1 | """Example functions"""
|
b77317ee8b5f858f3b544fa57404e9dee8d70bed7994b42fd71c5a31965f82f7 | Python | 24 | 1 | """Common workflows."""
|
db8875259156982d458005cfbc3deff4e04b2f22e22e8ad688b66dd7c3ed5253 | Python | 24 | 1 | """Recipes for VASP."""
|
df0020acf7cb4035f89b4e5733d7cdd73cf305443ad97814d3eb271a0f628600 | Python | 24 | 1 | """Recipes for Psi4."""
|
f467ac8f63b7366689f6232ab20182f12b7a95b68c42e23124a47e2d9e1329b7 | Python | 24 | 1 | from .oc_wc import OcWc
|
fa470b411561aff3a946e5bdb8aa6581cd82481759f6bf2584dc2aa439d0cac3 | Python | 24 | 1 | """Recipes for MRCC."""
|
1187a5becbc5450194d48907fbaa34ac7d2142db46a86a5cbea42dfc2c4aeccd | Python | 25 | 1 | """Recipes for ONETEP"""
|
2a9f7ede5810332b758a39258dda87c751d568a610f9cbcd7c842a1994bdc0b5 | Python | 25 | 1 | from .model import MAnet
|
50be2913c0c5629e40c8c1f502317c44285b38d5aab3bc3d76a5f207b50551ea | Python | 25 | 1 | """deepsignal2 utils"""
|
5d44c8bcadc4aff32bd4aaa58131356a3dbe247bb27beec1537e4d6d5270859a | Python | 25 | 1 | from .proofread import *
|
7b335ded2229cadfbaf04d9ee2eb509a5d846d33754423a4683bb3bb186c0568 | Python | 25 | 1 | # NIfTI Creation module
|
a7609a9bbe8942eafc8b1f09dc9c4013767c7dd14cf1f7a3b91967ed344df42d | Python | 25 | 1 | from .benchmarks import * |
cfe7a3fe397744743c4276fd5e8831410ea1fb812fcf5344832dde2ec099c21d | Python | 25 | 1 | from .load import Loader
|
e7b6cbe9c9598430a5cd59377604d7fbfbdf074d97b8b043ff4665bb77aee990 | Python | 25 | 2 | import tensorflow as tf
|
f35aaea20802b88ca966366cddb6dfd53cbbd0a1ddbdae511842718b4a02e7b1 | Python | 25 | 1 | from .constants import *
|
03e4b3f2c376b688d187443e0ce86c6e6535bb07afd31ed0efb24d534a05d584 | Python | 26 | 1 | from .oc_fhn import OcFhn
|
267ae76979165a2c5e355b4e4e91092fc067c18daddf903b7dd248bfc5109cc3 | Python | 26 | 1 | __author__ = 'bguillouet'
|
2c0b95004ce6334e2e9391acc284e9e9b843aca5e064425a501757f9a6db4d35 | Python | 26 | 1 | ../catalogs_b/catalog_1.py |
46f6bc0374abf17420e9883051756a2c9846ba59c0f7a614d31abc65fc92a64a | Python | 26 | 1 | """Recipes for tblite."""
|
8ebcda00f104e68540f9f9ae68c9bda1cbfe852af1333f43015b99733190ef6b | Python | 26 | 1 | ../catalogs_b/catalog_2.py |
96d550234935754a493e7d6cc052c8efc884d60711f3aafc662e3fb0f3232eb4 | Python | 26 | 1 | ../catalogs_a/catalog_3.py |
c65810b2904e86b933b06897d0fb74c84569f1fe0e08d960837ef0c6d2abd35c | Python | 26 | 1 | from .internvideo import * |
d1755f10d85ced3806f5f91d3cceb70080a155f5236e2ae1832c2eecbdd3a60f | Python | 26 | 1 | from .model import PSPNet
|
ec463c14d22770b54bd4d9336b4911a7f60310bad82e19f7ab58a5b3e2856841 | Python | 26 | 1 | from .oc_aln import OcAln
|
590067db3154e10e2034789bebd9a9148441050bacc294d573903212e96f1bea | Python | 27 | 1 | """Utilities init file."""
|
9d59c24d8129a3df024ee0968ef11c39015095fa20d896f5d14214a1529cfa28 | Python | 27 | 1 | from .model import WCModel
|
e9add001404b4806957773fa94218add2b5aa85aa861cd8733d93bb858c6e2f2 | Python | 27 | 1 | from .model import WWModel
|
f857efb953d8e38310c7cba4a8353d3c449d85f67c5451608d6f4bd5f3cbfb4a | Python | 27 | 1 | from .connectivity import * |
00fcf72708a2135abd7bb99a7025f5995af61ebc2ada2c215e287c1ebec21cd2 | Python | 28 | 1 | from .model import ALNModel
|
19c6d8d66315e8e98ca7d9981caa7dfd1a4c02219c12a6a7f786f586ae278e22 | Python | 28 | 1 | supervised_learning = False
|
39b9ccc9c2ae7b8adf4f826d6919e654e1f49e1b4c39321039efc1f8dd10dc71 | Python | 28 | 1 | # Implement your code here.
|
5556231aa1491ad19bc259d6105a8ba96d5640d1c0958b5f49ec3ffe675830b6 | Python | 28 | 1 | from .acsunet import ACSUNet |
6909c7f18d4fec6a152fd7a5f467e66209428c01399ce10f29fed75fb9b9837a | Python | 28 | 1 | from .oc_hopf import OcHopf
|
69aeb196b39db3d2638b7173d84d9bbf8ae7d4676cc671e592f6b27fa1de77e4 | Python | 28 | 1 | from .tsu_benchmark import * |
9acf20e14b1998460260cedcd6b6a18976aa9928fb36ccac65fcecd758030082 | Python | 28 | 1 | catalogs_c_link/catalog_4.py |
b9d628519c6f0d5f89d9d53f61f547ed2e12206e33e39713b36c14fed5703508 | Python | 28 | 1 | """Recipes for Gaussian."""
|
ca38afe23e054d65f32b4a2f695b5a36159daaa35914f4e1cb3ca172d8e3e5cd | Python | 28 | 1 | from .pddl_file import open
|
e4cbe55a7960328f04faedc8c833529db8537a0b210e94c64f7246a79a97b1dc | Python | 28 | 1 | from .model import FHNModel
|
f8d3cefc4bbe8c5d3150f89d2ee6dfdc20e92f6794cdc1463d54333959801238 | Python | 28 | 1 | """Recipes for FHI-Aims."""
|
062cde341679cff8f51bfd56c28cb5c5a5685d17558f361362b5c83588b8664d | Python | 29 | 1 | from .model import HopfModel
|
1fc7dd4309b23a6e0ac60c36e0fbb1420d473db8aaf054a92ecdca5945be14cd | Python | 29 | 1 | """Recipes for NewtonNet."""
|
47f58e76e901b9e67432bf64d0ca8146bc04dca1bf3f1f3bf96e9813e3274991 | Python | 29 | 1 | from .model import get_model
|
4ae991c4eb8fdf4ab15713fb28e70d0509690b2bc3a8ef349627ef71d4308ad8 | Python | 29 | 1 | from .m3cv import M3CVDataset |
eea7ad29860e43d507e2bdb3b0010d613f3622f18df978110275322a9715432e | Python | 29 | 1 | from arrayexp import ArrayExp |
07a78d814ba7ed6382f1cfc56ee237e41d34cd8e94bb3c33f7a88671e251ee17 | Python | 30 | 1 | from .__main__ import Analysis |
3f5f2123ed1f29396ab645a0cc71b710f5542246f9ba7d95d1aa5d314038f069 | Python | 30 | 1 | from .build import build_model |
8cd90863ada932863833f58a4aced5dcac543828a11ac2136706baa2160b2ba3 | Python | 30 | 1 | from pinn.robustfill import *
|
00a0e5727764828ae4c25241d1c1c5246f0593ba1941ff54952cada2ca239dec | Python | 31 | 1 | from .hcnn_compressed import *
|
0e46a4f6134f80557b1dc37ea4a38b489796b62df25aa58ac5feab6f7f2ed78a | Python | 31 | 1 | from .tigre import TIGREDataset |
2c373230e253dff211ca80f99d620dc552714af4f66b7af4fd6b19953f8e53c7 | Python | 31 | 1 | from .relu import ReLU as ReLU
|
2f7a711cfaf33faa98905470069b9c00508a4096ccc0a987ff99206ee844c09b | Python | 31 | 1 | """Miscellaneous functions."""
|
44da03aa981e805a262e69be2b4cc46a61b8ec31cd47a27041a83e562a9600c0 | Python | 31 | 2 | LARGE_VAR = 5.0
NUM_ITEMS = 18
|
774e10dbff26278e534c0f666aef3e09294bdcf62a5e81c89b251f33c789b95b | Python | 31 | 1 | from audiobook.config import *
|
8d93653569e7b563845488c5f33303ae09a90cd07631316c7627ab4b779be0d7 | Python | 31 | 1 | from .to import ToG, ToDynamicG |
a6de7a5464fd48d86fa130243d4455eaaa19086ee842a400e5ee59b301e274df | Python | 31 | 1 | from .design import Rom as Rom
|
a8c2a493c1d8c02bc30cdb1e09253132b9f58454d0522c48197f36f02ec27d47 | Python | 31 | 3 | from .model_compare import *
|
fbaf00cbfd819a58e3af640d9ab10aca9bf71aba404210af1e8f7248b2fd4551 | Python | 31 | 1 | from .build import build_loader |
310ad869056a99731e9fb54ba759f507bf8fd0c7d2f95882fcae37a04f943495 | Python | 32 | 1 | from .layer import ReLU as ReLU
|
9659fc5865c5ad7e972b4be65af48f978844edd44a60797d8163a4709de2f9c0 | Python | 32 | 1 | from .model import UnetPlusPlus
|
0383303fb758ea1958dca75d23e26d8a5071e403fe02dc8f43ab2bda7ce6098d | Python | 33 | 1 | from .model import KuramotoModel
|
44f4407bbe6728eae783f468086f66c29c62bd22827c48895b3a086e8fcb215b | Python | 33 | 1 | """Calculator for using MRCC."""
|
9880ac1568bdde2003955b80b87ea8f2cbc31094bc05e65d939be12e7572be7a | Python | 33 | 1 | """Recipes for Lennard-Jones."""
|
a1cf6c0928b669fd85a07c47a28373dae0609a17593ce816acff367ebefb605e | Python | 33 | 1 | from .evolution import Evolution
|
c70a9a4be5c48035a0c36783ed8472001fde505c3a1863c08978ad33cc961803 | Python | 33 | 1 | from .hashgrid import HashEncoder |
f1f3c1ee25edf445cd049ddc9417d1ca1e8329b0d4ff80fc5b4eb2d4bdf5ce7c | Python | 33 | 1 | from .FaceBoxes import FaceBoxes
|
f9e0056442e7dbca7c53695ba9140e6267f89a593f14726c177aa2303ca3a7b5 | Python | 33 | 1 | from .tevo import UFromHOperator
|
0ca599a07443bcf351a8a104ac877f4cea8ec6712a541c1c7e2da8c12a425eec | Python | 34 | 1 | from .sim_clr import SimCLRTrainer |
7fd299ac26c6127d2509c78944468d0a084aa865ac862e9561ad7eb39e999291 | Python | 34 | 1 | __all__ = ["data_factory", "func"] |
c052af08d2245c5441e6e49df47e2bff75b19e37daf2ef0359bf5a8826fb46ba | Python | 34 | 1 | from .layer import PReLU as PReLU
|
d93edc2b9097dd403baa32903a0623a95e609da668dc9f3bec47737954ba95ce | Python | 34 | 1 | from .arg_parser import ArgParser
|
ed4bf9da7833cc3048a2e53904108aac00a051412ae522d1f5b99db8b0b8356d | Python | 34 | 1 | """ Tensorflow models go here """
|
033c62d3c387484558f5ba1519543963314fd59f4fb03ff9293cc1f60cff49d6 | Python | 35 | 1 | """Tests for cog-dataclass SDK."""
|
2683c717687002a6fecf042bd691013d374e18f4ac49dfd0b0f3c5c83a8e38b1 | Python | 35 | 1 | from.class_ecolocator import EcoLoc |
c8640fec1bd3b7b0fc25612be07895eab50462762c207efab9a84f23b8040019 | Python | 35 | 1 | from .exploration import BoxSearch
|
30ced62d99dfdc97fca7ef12952174cce1a6ecd258d29eeb2129acd9ac1f198b | Python | 36 | 1 | from .helpers import get_activations |
c5bfb42b321ddd532b92bdd2352f7518a41929c2ede1f817a0418b19614ccb2b | Python | 36 | 1 | collect_ignore = ["system_test.py"]
|
c6a748dd0ad5e2dcfb2c15c75c8d18a57db77bfdb53304fc0e844df1e98f8a64 | Python | 36 | 1 | from .layer import PReLU2 as PReLU2
|
cb82755a89248fb243feacb4e34f8ad2c5f3254e848401ff3db05db0e1ee420d | Python | 36 | 1 | """Recipes for Quantum Espresso."""
|
252f294e3f98ef7a69a5cbe83f272cbfa4bcaab1a52481b7c616c14b0b2b1a95 | Python | 37 | 1 | """SPCM control module init file."""
|
616e6b2a7515e4e9a285e6799bcd2096dbad35091513d5d2232590e947806e36 | Python | 37 | 3 | from .merlin import merlin
merlin()
|
b0b41046110dfb54c827f8abf09d8240553d41efff2d5bd82915e727dc5dcd05 | Python | 37 | 1 | from .classification_models import *
|
be8d56b69bfdd37625d4e50bc68bd947eb8cd4c71ccebf68fcee57d59b475597 | Python | 37 | 1 | from .linear import Linear as Linear
|
ca99667a935c2eafc032a739e5f4695d1e3ef23e8a31499de3f74814e3fbe557 | Python | 37 | 1 | from .conv1d import Conv1d as Conv1d
|
ef1a656be937a40c4ec9c09dc7237b516a8f29def46d427cdf1fd2f35da955af | Python | 37 | 1 | from .model import ThalamicMassModel
|
f4d7c989e56cc83705172ac2938867373ccc65cd43aef9acd400ea30a51263a2 | Python | 37 | 1 | from .lutron import lutron as lutron
|
e9c6daeca62e38a931c6f1662ccbe3f601b95dcaa8cce637c685de07dde4d205 | Python | 38 | 3 | # __init__.py
__version__ = '0.0.13'
|
2cdb8b5ffb1e4e1e73c8beefb4f0e42a70d9d430c32b075764d4be87cb20d4a6 | Python | 39 | 1 | """Miscellaneous utility functions."""
|
776d69a8b43362f45fb9ad7159d6172b2cda2e4774204cb3970f0a8bd7f135dd | Python | 39 | 1 | from topaz._version import __version__
|
d1c7bdadf5f8feb18aee7a58f25d96e984009d1a08256b02efdb8bb69c5ec181 | Python | 39 | 1 | """Presets for the Vasp calculator."""
|
fb7cce463f4a6b9198e9a9aa2f91364f820fea6af53cd691a5c747f6f99cd9dc | Python | 39 | 1 | """Calibration sequences init file."""
|
1b4825eef9a7395a82d579e8b758966f746dadfc49d6ff72a61839dffcdcb4fd | Python | 40 | 2 | from .bcgan import *
from .bgan import * |
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