sha256 stringlengths 64 64 | language stringclasses 28
values | size int32 1 491k | lines int32 1 23.2k | content stringlengths 1 200k |
|---|---|---|---|---|
efdebd1a883848d5fead99ba2a299fa60a823926b233051c6b2574d9c8b5c215 | Python | 173 | 7 | #!/usr/bin/env python3
# -*- coding: utf-8 -*-
def test_help_option(script_runner):
ret = script_runner.run(['scil_dwi_convert_FDF', '--help'])
assert ret.success
|
0bd7e4ce483806b5d10c5bdcffb39cd944fa068f90cfe6e771d4d4c320425532 | Python | 174 | 7 | #!/usr/bin/env python3
# -*- coding: utf-8 -*-
def test_help_option(script_runner):
ret = script_runner.run(['scil_freewater_priors', '--help'])
assert ret.success
|
92ceb121a1527de7d9dc6902ff66496ddb49a7c69d092727dd2f11372a09cc65 | Python | 174 | 2 | from .data_loader import load_nhefs, load_nhefs_survival, load_acic16
from ..simulation.CausalSimulator3 import CausalSimulator3 as CausalSimulator, generate_random_topology
|
cd6febf68f67087449c481aabf6837ea4784a0f13e3e2374a65fa89a5226c8fa | Python | 174 | 9 | #! /usr/bin/env python
import jellyfish
import sys
qf = jellyfish.QueryMerFile(sys.argv[1])
for str in sys.argv[2:]:
print("%s %d" % (str, qf[jellyfish.MerDNA(str)]))
|
2f101f37e2651c0059c19af5c5381a2c867e12a9837476280d4bd4f386c3967b | Python | 175 | 4 | from mako.abmil import AttentionMILModel
from mako.data import WSIBagDataset, InMemoryWSIBagDataset
__all__ = ["AttentionMILModel", "WSIBagDataset", "InMemoryWSIBagDataset"]
|
5d4c5a2e3c6754e5b397ff084af4cacaa4b68c7b215912e4c40d8283dc6a7f7b | Python | 175 | 7 | # Copyright (C) CVAT.ai Corporation
#
# SPDX-License-Identifier: MIT
import os
ORGANIZATIONS_MIN_ROLE_TO_CREATE = os.getenv("CVAT_ORGANIZATIONS_MIN_ROLE_TO_CREATE", "user")
|
18e5c7e9f09389bbed2c79cfdf05bcf0f6abfa56922730f155a8baf2edc50704 | Python | 176 | 4 | from brainscore_vision import benchmark_registry
from .benchmark import DicarloRajalingham2020ITPLS
benchmark_registry['Rajalingham2020.IT-pls'] = DicarloRajalingham2020ITPLS
|
f6bd6eee2bd5296e4397e3dcb062b9e66bf877086c63005ba2d9d43e9619fd26 | Python | 176 | 7 | #!/usr/bin/env python3
# -*- coding: utf-8 -*-
def test_help_option(script_runner):
ret = script_runner.run(['scil_viz_dti_screenshot', '--help'])
assert ret.success
|
6b4cfbe8c1c3bf0e68ea0346309dbddde33b9cbc9c10da7ed118e3958cc17a89 | Python | 177 | 5 | from .local_handler import SVILocalHandler
from .settings import DEFAULT, TEST
from .wrapper import FactorModel
__all__ = ["DEFAULT", "TEST", "SVILocalHandler", "FactorModel"]
|
c9bc62c584b8bd1f04f5a6528bc1ee840de57107a93e9668a6e1aa20e5aa918f | Python | 177 | 8 | # Copyright (C) CVAT.ai Corporation
#
# SPDX-License-Identifier: MIT
from django.dispatch import Signal
cache_item_created_signal = Signal()
cache_item_read_signal = Signal()
|
f726b3ccfc664b575ab72bd354a4acdeb7d2715ad5d1ba03feb4a3e0d030843c | Python | 177 | 8 | import pytest
from brainscore_vision import load_stimulus_set
@pytest.mark.private_access
def test_existence():
assert load_stimulus_set('ImageNetSlim15000') is not None
|
fcad13dbc637409fa3271537577a1a871d22241744c08e33ae245dab8c315708 | Python | 177 | 4 | from mmsdk.mmdatasdk.dataset.standard_datasets.POM import pom_std_folds as standard_folds
from mmsdk.mmdatasdk.dataset.standard_datasets.POM.pom import raw, highlevel, labels
|
3d1ec90c18230b76db7b412d36881b46312e8c54ef4da68bbe7d39dd69fcba78 | Python | 178 | 4 | from utils.utils import cvtColor, preprocess_input,get_lr
from utils.dataloader import DeeplabDataset
from utils.utils_metrics import f_score
from utils.utils import resize_image |
63446f185c41925697ca8f02c05e41dedc61706b0ad9e5283c8945d526f21817 | Python | 178 | 7 | name = "deep_events"
from . import database
# from . import csv_to_gaussian
# from . import gaussians_to_training
# from . import myfunctions
# from . import training_functions
|
8860f49ed58f2f293f257042e91306b08723d5c62613391ac3cdd70a14cd3820 | Python | 178 | 8 | import pytest
import brainscore_vision
@pytest.mark.travis_slow
def test_has_identifier():
model = brainscore_vision.load_model('kap')
assert model.identifier == 'kap'
|
a87d31325cc50ee31ef764ea9fc8fbc444cfd90697d367a1198f1058e16a8e89 | Python | 178 | 5 | from .base_positivity import BasePositivity
from .trimming import Trimming
from .matching import Matching
from .univariate_bbox import UnivariateBoundingBox
__version__ = "0.0.1" |
ead5c159c44f391c72d270ae2cdfb5a5f90e0f3a30ca25e75831418b1eb3fc52 | Python | 178 | 7 | #!/usr/bin/env python3
# -*- coding: utf-8 -*-
def test_help_option(script_runner):
ret = script_runner.run(['scil_viz_tractogram_seeds', '--help'])
assert ret.success
|
1b12991131d640cf6e0c118dbb8d6b2746ed948e6822b39a41001fdafb4a7cdd | Python | 179 | 11 | from .models import *
from .data import *
from .finemap import *
from .io import *
from .util import *
from .viz import *
__version__ = "0.7"
VERSION = __version__
LOG = "MAIN"
|
28800412c88434bf98fc76eeec92ce3df898e6f7b868e672015b9d8cc6ecaf45 | Python | 179 | 9 | from . import constants
from . import fit
from . import io
from . import misc
from . import models
from . import optimize
from . import preproc
from . import seq
from . import sim |
96913e25428085b83cff335fbb4c458c104cc8bd06584db6c32a8ed0e2b606bf | Python | 179 | 8 | """
ChemGraph UI Package
This package contains the user interface components for ChemGraph including
the Streamlit web app and command-line interface.
"""
__version__ = "0.1.0"
|
bb0aef09a0874176647716202df701427eb310c6e9c5b30ec1efa4e66da64f15 | Python | 179 | 8 | import pytest
import brainscore_vision
@pytest.mark.travis_slow
def test_has_identifier():
model = brainscore_vision.load_model('hmax')
assert model.identifier == 'hmax' |
cba96742411749437cf8ad9473d70e96a4f00d301bda2f4ec034f12c87d25b21 | Python | 179 | 9 | # import self-written scripts to get random positions and manage exp
import exp_utils
LOCATION='mockup'
if __name__ == '__main__':
exp_utils.run_exp(LOCATION,train=True)
|
de65225a8d577e5c74d49ee9d97881ec94a1644b4d877c8084b53e10908e65d8 | Python | 179 | 6 | #!/usr/bin/env python3
# -*- coding: utf-8 -*-
def test_help_option(script_runner):
ret = script_runner.run(['scil_json_harmonize_entries', '--help'])
assert ret.success
|
2c7e8d51c0a3201564c06f28a5a3472d4da18475680f850cc288a81cf4c9f4e7 | Python | 180 | 8 | import pytest
import brainscore_vision
@pytest.mark.travis_slow
def test_has_identifier():
model = brainscore_vision.load_model('kap1')
assert model.identifier == 'kap1'
|
4d76f5042b3c67b98db3041c01db005e8bad9f6260d358005ae65613a4861746 | Python | 180 | 6 | import pytest
import brainscore_vision
def test_has_identifier():
model = brainscore_vision.load_model('chresmax_v3_cl_01')
assert model.identifier == 'chresmax_v3_cl_01'
|
c124b3d4b11a8ee1efe18404d5e262446cc4f00f66081f34342bc0407e584d2e | Python | 180 | 11 | # -*- coding: utf-8 -*-
# @Author : LG
# 用于测试cpu
# import os
# os.environ["CUDA_VISIBLE_DEVICES"] = ""
from ISAT.main import main
if __name__ == "__main__":
main()
|
d2a7f00aa783ef20b7901b4729d86eafeaaf3f9a16e81c2257641f34f0855250 | Python | 180 | 8 | import pytest
import brainscore_vision
@pytest.mark.travis_slow
def test_has_identifier():
model = brainscore_vision.load_model('kap2')
assert model.identifier == 'kap2'
|
233ef91b4ef038bbab0ab50b63d787ffbf78b700e0828e8a4271395c46b528ef | Python | 181 | 3 |
# from protein_DIFF.model.egnn_pytorch.egnn_pytorch import EGNN, EGNN_Network
# from protein_DIFF.model.egnn_pytorch.egnn_pytorch_geometric import EGNN_Sparse, EGNN_Sparse_Network
|
32314a9d1107812638a59211cd0215b349d76d29173da027f451cf1c6c608166 | Python | 181 | 6 | # Ultralytics 🚀 AGPL-3.0 License - https://ultralytics.com/license
from .train import WorldTrainer
from .val import WorldValidator
__all__ = ["WorldTrainer", "WorldValidator"]
|
51ce92fb21bf749e8f9fe09ed87b07e16bde1358df2d98fcf34463acb4e40ff8 | Python | 181 | 9 | # import self-written scripts to get random positions and manage exp
import exp_utils
LOCATION='scanner'
if __name__ == '__main__':
exp_utils.run_exp(LOCATION,train=True)
|
80047b3c553d548a491f524ae0a37b53ea3650abb34c72d800af902e2a8ed7d2 | Python | 181 | 9 | import torch
import numpy as np
import random
def set_global_seed(seed):
random.seed(seed)
np.random.seed(seed)
torch.manual_seed(seed)
torch.cuda.manual_seed(seed) |
3fcdb50321ab5bd2b85e9dd54b2827bb0fc4f70185bd8234c0feb2f1411eec54 | Python | 182 | 7 | #!/usr/bin/env python3
# -*- coding: utf-8 -*-
def test_help_option(script_runner):
ret = script_runner.run(['scil_viz_gradients_screenshot', '--help'])
assert ret.success
|
4d36ad92504a29740749c3bea85f2eb93df3c108eae8806f786692d79eb958cb | Python | 182 | 9 | import brainscore_vision
import pytest
@pytest.mark.travis_slow
def test_has_identifier():
model = brainscore_vision.load_model('grcnn')
assert model.identifier == 'grcnn' |
63d486af008bea797cba9ceb003fccdb937a503772f68596298e9de4e676aa2d | Python | 182 | 8 | import pytest
import brainscore_vision
@pytest.mark.travis_slow
def test_has_identifier():
model = brainscore_vision.load_model('kapIT')
assert model.identifier == 'kapIT'
|
77e52728309f7a1524eaeeefd30d4d8c2d9860cb9dda748f20710d7a22d9a47d | Python | 182 | 7 | #!/usr/bin/env python3
# -*- coding: utf-8 -*-
def test_help_option(script_runner):
ret = script_runner.run(['scil_bundle_explore_bundleseg', '--help'])
assert ret.success
|
c0930f1fd92a6858491cb1a274bd2c5259cebedad2802d13ab0c6ec366bd3442 | Python | 182 | 8 | import pytest
import brainscore_vision
@pytest.mark.travis_slow
def test_has_identifier():
model = brainscore_vision.load_model('kapv1')
assert model.identifier == 'kapv1'
|
c9f9fbe7a1c7bb864175176a26bd39ec5d1e69ce52e82ff233b0442f5cafda25 | Python | 182 | 7 | #!/usr/bin/env python3
# -*- coding: utf-8 -*-
def test_help_option(script_runner):
ret = script_runner.run(['scil_dwi_prepare_eddy_command', '--help'])
assert ret.success
|
12de566145c8cb73454a5e5f6ee1d3bb0bdeb6be9a2281da23ff424fdb26eee0 | Python | 183 | 7 | #!/usr/bin/env python3
# -*- coding: utf-8 -*-
def test_help_option(script_runner):
ret = script_runner.run(['scil_dwi_prepare_topup_command', '--help'])
assert ret.success
|
52e1192db25f93df1ad4919c5ce8e2bf9fe2b0ac22d093e36b377b7d8139b565 | Python | 183 | 4 | from .trainer import ModelTrainer
from .distillation_trainer import ModelDistiller
from .finetune_trainer import ModelFinetuner
from .reinforcement_trainer import ReinforcementTrainer |
6793f9ab1639dfa4dcec9b90f9ba1905ac37c8c17e40b337e4c1c7ce4a6ffdd6 | Python | 183 | 7 | #!/usr/bin/env python3
# -*- coding: utf-8 -*-
def test_help_option(script_runner):
ret = script_runner.run(['scil_bundle_clean_qbx_clusters', '--help'])
assert ret.success
|
9cb4ac3854dca7bf866e6b23d4297091da1d884b450ec23588e734eaaf192354 | Python | 183 | 7 | #!/usr/bin/env python3
# -*- coding: utf-8 -*-
def test_help_option(script_runner):
ret = script_runner.run(['scil_viz_tractogram_collisions', '--help'])
assert ret.success
|
a9862c0c4e0aa2efa9739bb3f6814df6a228bcf3f2574240c252e9846d553d1c | Python | 183 | 7 | #!/usr/bin/env python3
# -*- coding: utf-8 -*-
def test_help_option(script_runner):
ret = script_runner.run(['scil_viz_bundle_screenshot_mni', '--help'])
assert ret.success
|
41088dd3b9a1180b039f01670a9a321532dd31737c484a26834b6ef6be6d8db7 | Python | 184 | 6 | # Copyright (C) CVAT.ai Corporation
#
# SPDX-License-Identifier: MIT
# Reexport symbols for public SDK API
from cvat_sdk.api_client.models import * # pylint: disable=wildcard-import
|
69bbd40636d91560d69425964c1eb1695ab6399ade3deb5bcb964e45f91ff7b1 | Python | 184 | 6 | """Dataset classes for loading MRI data."""
from .fastsurfer_dataset import FastSurferDataset
from .nifti_dataset import NiftiDataset
__all__ = ['FastSurferDataset', 'NiftiDataset']
|
9e733315e69274a2f0cef0fac63e248c21293f34a12b33f749f3416e36b59ad4 | Python | 184 | 4 | from mmsdk.mmdatasdk.dataset.standard_datasets.SocialIQ import socialiq_std_folds as standard_folds
from mmsdk.mmdatasdk.dataset.standard_datasets.SocialIQ.socialiq import highlevel
|
c6dd0d84ba1d02a687ee1fce417b3d3c4a60b63a29b9bcd73c41b035201035af | Python | 184 | 9 | # Copyright (C) CVAT.ai Corporation
#
# SPDX-License-Identifier: MIT
from django.apps import AppConfig
class DatasetManagerConfig(AppConfig):
name = "cvat.apps.dataset_manager"
|
32f6fb1fe271b8779545a7ddd69c292ac0b2134394ba3f3bc9783ffcca737d31 | Python | 185 | 8 | __all__ = ['check_attr']
def check_attr(c: type, p: type):
attr_c = set(dir(c))
attr_p = set(dir(p))
if attr_c != attr_p:
raise RuntimeError(f'{attr_c - attr_p}')
|
7e0230eec57e2f971e43b01f97d73ce41ad6b7f5ec5e84789c5f1084b18abf57 | Python | 185 | 7 | # Copyright (c) Meta Platforms, Inc. and affiliates. All Rights Reserved
from .model_builder import build_sam3_image_model
__version__ = "0.1.0"
__all__ = ["build_sam3_image_model"]
|
b0e2f4775ea96e80707da412593b3c089fed100681096612160961327a927d63 | Python | 186 | 3 | from diffxpy.testing.tests import _fit
from diffxpy.testing.utils import parse_gene_names, parse_sample_description, parse_size_factors, parse_grouping, \
constraint_system_from_star |
b73d2a7f18672eebefa6a4e53a798851aad8536b154da08390db6b9191b62580 | Python | 186 | 7 | from magicgui import use_app
from magicgui.application import APPLICATION_NAME
def test_app_name():
app = use_app("qt")
assert app.native.applicationName() == APPLICATION_NAME
|
f40c1a15ca6831831d2337cd8fb38502fbb2a669a84e5254c933354fc22f578b | Python | 186 | 6 | import pytest
import brainscore_vision
def test_has_identifier():
model = brainscore_vision.load_model('chresmax_v3_cl_01_v2')
assert model.identifier == 'chresmax_v3_cl_01_v2'
|
fa3dfbd73836ac5e801b569b85103a05049b519f6bd5196acbe48d235cafaf71 | Python | 186 | 3 | from .transfermatrix import PairwiseUnitary, Beamsplitter, PhaseShiftUpper, \
PhaseShiftLower, PhaseShiftCommonMode, PhaseShiftDifferentialMode
from .mzi import MZI, SMMZI, BlochMZI
|
00030884c735501b99db14b6540af865bd31e21aa7e82b7bfd2a0a0996ad1ca3 | Python | 187 | 8 | import pytest
import brainscore_vision
@pytest.mark.travis_slow
def test_has_identifier():
model = brainscore_vision.load_model('CORnet-S')
assert model.identifier == 'CORnet-S' |
4b9d248f1925671e1759fa9d0bb1a075e13cb5ba360a1b2f14b3dec0ac210aa5 | Python | 187 | 8 | # -*- coding: utf-8 -*-
# @Author : LG
import re
def has_chinese(text: str) -> bool:
"""判断字符串中是否包含汉字"""
return bool(re.search(r'[\u4e00-\u9fff]', text)) |
f776f74803d5eea3f33d24802d92263d5b8763449a02eac85ec2a18efee3c0e9 | Python | 187 | 8 | # from . import sumstats
# from . import herigc
# from . import voxelgwas
# from . import ldr
# from . import ldmatrix
# from . import utils
# from . import sumstats
# from . import ldsc
|
737569e0c9aa8584d719f26378499b00adda156cd4451c8bcecef6b159903962 | Python | 188 | 4 | import pytest, brainscore_vision
@pytest.mark.travis_slow
def test_has_identifier():
assert brainscore_vision.load_model('convnext_xxlarge_clip').identifier == 'convnext_xxlarge_clip'
|
7abb097cd4a7f95f7e5b5a72eea1f433c98e2b277d5f393a6a89f0931f9b5792 | Python | 188 | 12 | #!/usr/bin/env python3
# tifffile/__main__.py
"""Display image and metadata in TIFF file."""
from __future__ import annotations
import sys
from .tifffile import main
sys.exit(main())
|
da469fabbb56a0854fe4dc3bb5ce32061e679d29fa2c61de1ec3390aed5ec1e2 | Python | 188 | 13 | from importlib.metadata import version
__version__ = version("debcr")
from . import data
from . import model
from . import config
__all__ = [
"data",
"model",
"config"
] |
c7421ee1b9a601b982ac2866e2ada79d23ca5ddf8b3ba8ad6557cf246634c27a | Python | 189 | 4 | from brainscore_vision import metric_registry
from .ceiling import SplitHalfPredictorConsistency
metric_registry["predictor_consistency"] = lambda *a, **k: SplitHalfPredictorConsistency()
|
2ca64c518edfb77925efef489cfed8df40159c64822f5ca3de581c2f277df065 | Python | 190 | 7 | """Configuration files for FLYNC pipeline.
This module contains default configuration files:
- bwq_config.yaml: Default BigWig/BigBed track queries for feature extraction
"""
__all__ = []
|
dc421f051c3a28311d14f324df3de981c9f3366141d96d0a947629b70f345cd0 | Python | 190 | 9 | import brainscore_vision
import pytest
@pytest.mark.travis_slow
def test_has_identifier():
model = brainscore_vision.load_model('grcnn_109')
assert model.identifier == 'grcnn_109' |
2032a1491546dee1bb8e6d95a2e9e2e6ce64ef2d87569bf80d3ea98df3a52c1f | Python | 191 | 8 | from .metrics import fair_odds_auc
from .fairness import equalized_odds_gap, generalized_equalized_odds
__all__ = [
"fair_odds_auc",
"equalized_odds_gap",
"generalized_equalized_odds",
]
|
83f5b510b5ac09068dc7008e058c357524bb58c76956989bb8d72b6f7936b43e | Python | 191 | 9 | import json
import sys
with open(sys.argv[1], "r") as rf:
data = json.load(rf)
for item in data:
if "ERROR" in data[item]["manual_workflow"]["result"]['value']:
print(item)
|
caf08d45f025a000a45f9058858c19d4fda3556d788795ac2061d15b9929721c | Python | 191 | 7 | from .model import get_layers
def test_layers():
layers = get_layers("deepeisnn_ei_cifar10_vgg19")
assert len(layers) > 0
assert all(isinstance(layer, str) for layer in layers)
|
f8de1ee39355d1311d47ce6220314d5289d0a0b2d3ce8389f3e6a1bac07a25a9 | Python | 191 | 9 | # Copyright (C) 2018-2022 Intel Corporation
#
# SPDX-License-Identifier: MIT
from cvat.utils.version import get_version
VERSION = (2, 77, 1, "alpha", 0)
__version__ = get_version(VERSION)
|
0e8fe3613ce92483a8c867c9275057e417334c70cb42701f8b88fc81bff10359 | Python | 192 | 5 | """Background search helpers for iterative 2D background fitting.
Holds the full-image search routines (``background_search``) and
their low-level utilities (``background_search_utils``).
""" |
18afa4b5a7fce8f2d939494efe83a1bdcfb9e525f56052dca6372981fedaf3b7 | Python | 192 | 6 | """ Real-world/mock datasets and missingness corruptors to experiment with. """
from .base import randu
from .base import randn
from .base import mnist
__all__ = ["randu", "randn", "mnist"]
|
841c8af937be0aa14a88a0ee99150f168d525121f590e75989c3809b2372e5b0 | Python | 192 | 7 | from .model import get_layers
def test_layers():
layers = get_layers("deepeisnn_cifar10_vgg19_lif")
assert len(layers) > 0
assert all(isinstance(layer, str) for layer in layers)
|
8cec14da0f26fb6f040c98e7674c700dd6b01828ac82b2d2715487591bfc2218 | Python | 193 | 7 | from .model import get_layers
def test_layers():
layers = get_layers("deepeisnn_cifar10_vgg19_full")
assert len(layers) > 0
assert all(isinstance(layer, str) for layer in layers)
|
9c6f8979e7a638fd13c8dd058af70b0572fb82457b96ea9a28ef77101a7001e0 | Python | 193 | 8 | import brainscore_vision
import pytest
@pytest.mark.travis_slow
def test_has_identifier():
model = brainscore_vision.load_model('BiT-S-R50x3')
assert model.identifier == 'BiT-S-R50x3' |
ea5684182f6c561e975601e0a776da0433bc679b3e0144a22ecadb7419b46e0c | Python | 193 | 8 | import brainscore_vision
import pytest
@pytest.mark.travis_slow
def test_has_identifier():
model = brainscore_vision.load_model('BiT-S-R50x1')
assert model.identifier == 'BiT-S-R50x1' |
fa985d1872c52930c2a2fae2a51c252ba228c6a87f255914b6178a249eba35ce | Python | 193 | 6 | from analognas.search_spaces.sample import random_sample
dataset = "VWW"
number_of_architectures = 30
architectures = random_sample(dataset, number_of_architectures)
print(architectures[0]) |
9c762c9ded4e51b10a3eb4b1cf4e766a8d89e1b4e870d9a417e7440b6750d08b | Python | 194 | 7 | from .model import get_layers
def test_layers():
layers = get_layers("deepeisnn_ei_cifar10_resnet18")
assert len(layers) > 0
assert all(isinstance(layer, str) for layer in layers)
|
ac5f88b0d0b45bc73e831b2010e5b3957bf80b6e542ecb8a1c31503ace00357e | Python | 194 | 5 | """A Python library for generating quantum molecular graphs of organic molecules from electronic structure theory calculations."""
from graphpancake import *
from ._version import __version__
|
118a7ee15b216d40e4803583d9ee615b6a27b39e864fca62256e40b0837856d5 | Python | 195 | 8 | import pytest
import brainscore_vision
@pytest.mark.travis_slow
def test_has_identifier():
model = brainscore_vision.load_model('inception_v3')
assert model.identifier == 'inception_v3' |
301f050aacbd87b2f4f05fb1bc8ad6042d8a875f88d80466e96853217fe45bfc | Python | 195 | 8 | import pytest
import brainscore_vision
@pytest.mark.travis_slow
def test_has_identifier():
model = brainscore_vision.load_model('inception_v4')
assert model.identifier == 'inception_v4' |
3c051a9b27d7415c9540d3fd05237d964d90414f8c4196c77d738262c2e17565 | Python | 195 | 7 | from .model import get_layers
def test_layers():
layers = get_layers("deepeisnn_ei_imagenet_resnet18")
assert len(layers) > 0
assert all(isinstance(layer, str) for layer in layers)
|
6236e5b76c211f4e5fefea84b7644bc3dc927f0f53bad1d085497bd8812525e4 | Python | 195 | 8 | import brainscore_vision
import pytest
@pytest.mark.travis_slow
def test_has_identifier():
model = brainscore_vision.load_model('BiT-S-R101x1')
assert model.identifier == 'BiT-S-R101x1' |
634573f0ec63abb555c8a31e53a76411b933f49d9c6c9f3343d9f0a6d5c0cc2e | Python | 195 | 7 | from .model import get_layers
def test_layers():
layers = get_layers("deepeisnn_cifar10_resnet18_lif")
assert len(layers) > 0
assert all(isinstance(layer, str) for layer in layers)
|
65ccfa724b57047fb3756292d9ceb383bb2056b354909bb7a08b7d0ebef76dde | Python | 195 | 4 | from mmsdk.mmdatasdk.dataset.standard_datasets.CMU_MOSI import cmu_mosi_std_folds as standard_folds
from mmsdk.mmdatasdk.dataset.standard_datasets.CMU_MOSI.cmu_mosi import raw,highlevel,labels
|
6c2fc7a3d8926778f624d63c02d1a8e17108aec361c6ae5b6dc918c819174f3d | Python | 195 | 8 | import brainscore_vision
import pytest
@pytest.mark.travis_slow
def test_has_identifier():
model = brainscore_vision.load_model('densenet-121')
assert model.identifier == 'densenet-121' |
99b0a37bc26303c80ae3cdf173f6486f21c8214efbcccf0b0271de94bdd8528e | Python | 195 | 8 | import brainscore_vision
import pytest
@pytest.mark.travis_slow
def test_has_identifier():
model = brainscore_vision.load_model('BiT-S-R152x4')
assert model.identifier == 'BiT-S-R152x4' |
a24c180e682fe799ba470cd25e74dab8689dc720780525ccb2ff3bb6195d9f2a | Python | 195 | 8 | import brainscore_vision
import pytest
@pytest.mark.travis_slow
def test_has_identifier():
model = brainscore_vision.load_model('BiT-S-R152x2')
assert model.identifier == 'BiT-S-R152x2' |
a903ccb99493aa12d4deacf69bce5d85cc27ef9ca063a4facb890e7f91876021 | Python | 195 | 8 | import brainscore_vision
import pytest
@pytest.mark.travis_slow
def test_has_identifier():
model = brainscore_vision.load_model('BiT-S-R101x3')
assert model.identifier == 'BiT-S-R101x3' |
b1ac1963b065c8faad9256c62f975bc15ba38c0886f1a058cfda00e997b8b7c1 | Python | 195 | 8 | from PyInstaller.utils.hooks import logger
def pre_safe_import_module(psim_api):
import PyMca5.PyMcaGui as PyMcaGui
for p in PyMcaGui.__path__:
psim_api.append_package_path(p)
|
db87283c8040ac5363854f1d74e87277b18c799f2d7a50097878f14f58597186 | Python | 195 | 7 | from configparser import ConfigParser
import PUMI
import os
cfg_parser = ConfigParser()
cfg_parser.optionxform = str
cfg_parser.read(os.path.join(os.path.dirname(PUMI.__file__), 'settings.ini')) |
fc5382b92eb153a87a3e56e1b9b414bf4fad690f509010ae7d76eb402708fc25 | Python | 195 | 9 | # Module initialization
from .helpers import set_seed, create_directory, format_y_values, get_device
__all__ = [
'set_seed',
'create_directory',
'format_y_values',
'get_device'
] |
0023bdeaa4ba4fe40b0b0fbfbc7a0f11471b2f9920e819e2f750cda6d99d68e6 | Python | 196 | 8 | import brainscore_vision
import pytest
@pytest.mark.travis_slow
def test_has_identifier():
model = brainscore_vision.load_model('inception_v1')
assert model.identifier == 'inception_v1'
|
3dc312cbd5b88af28ddeccdbe7f7e4bb1b1c303c92a8242248104f8c72a3e6f8 | Python | 196 | 8 | import pytest
import brainscore_vision
@pytest.mark.travis_slow
def test_has_identifier():
model = brainscore_vision.load_model('VOneCORnet-S')
assert model.identifier == 'VOneCORnet-S'
|
4665e0d23f720750b1d4bf31f2b8935b7cf35072c1f44dcf1464a4dc591efc7b | Python | 196 | 8 | #!/usr/bin/env python3
# -*- coding: utf-8 -*-
def test_help_option(script_runner):
ret = script_runner.run([
'scil_bundle_mean_fixel_mrds_metric', '--help'])
assert ret.success
|
610adad678b11e018cae528d0c3bc2c4152c1589b22d4743ab8884bdf815496d | Python | 196 | 7 | from .model import get_layers
def test_layers():
layers = get_layers("deepeisnn_imagenet_resnet18_lif")
assert len(layers) > 0
assert all(isinstance(layer, str) for layer in layers)
|
7981afdea898f8ee6234140e22f6ad97c0c112afa7469d1573ecc0d5949d2d2d | Python | 196 | 4 | # Copyright (c) Meta Platforms, Inc. and affiliates. All Rights Reserved
from .mask_decoder import MaskDecoder
from .prompt_encoder import PromptEncoder
from .transformer import TwoWayTransformer
|
99a3cffb60e819e08aa58e84554e85c362c17a2f8964d76d03efe8e6b9c99040 | Python | 196 | 8 | import pytest
import brainscore_vision
@pytest.mark.travis_slow
def test_has_identifier():
model = brainscore_vision.load_model('densenet-201')
assert model.identifier == 'densenet-201'
|
a28eec350cba8dfea49a0b554c2df973162325a553f96cf59baae7dad0f02d28 | Python | 196 | 4 | from kinescope.processing.smoothing import interpolate_df, smooth
from kinescope.processing.normalization import normalise_skeletons
__all__ = ["interpolate_df", "smooth", "normalise_skeletons"]
|
a5b59a9254d76760eaff906150f968a614721a7fafc5cf166451bb32b1319b3f | Python | 196 | 9 | import brainscore_vision
import pytest
@pytest.mark.travis_slow
def test_has_identifier():
model = brainscore_vision.load_model('densenet-169')
assert model.identifier == 'densenet-169' |
aa96ad0c3e0f4b65d94cb3b7198c0aac8884ab38e54b55cbb02273b59d84f767 | Python | 196 | 7 | import pytest
import brainscore_vision
def test_has_identifier():
model = brainscore_vision.load_model('aughost_fair_resnet18')
assert model.identifier == 'aughost_fair_resnet18'
|
be46113cbc7b23975ef038ce18d59a7832d1bf8ae89d004988851ead654f1d64 | Python | 196 | 8 | """Runs the web interface version of ADMET-AI using Flask."""
from flask import Flask
app = Flask(__name__)
app.config.from_object("admet_ai.web.app.config")
from admet_ai.web.app import views
|
bf115c38dec9f4eb5a25845e7ed92be32296ae02654ce2e2dde26f1e8e169cc7 | Python | 196 | 6 | # Copyright (c) Facebook, Inc. and its affiliates.
#
# This source code is licensed under the MIT license found in the
# LICENSE file in the root directory of this source tree.
version = "0.3.1"
|
fa620a35323c3978c2aa6c035b15e8ab3dfcf8ec2246a102a498520aa13d991c | Python | 196 | 7 | from .model import get_layers
def test_layers():
layers = get_layers("deepeisnn_cifar10_resnet18_full")
assert len(layers) > 0
assert all(isinstance(layer, str) for layer in layers)
|
1fc7bae390c198d26f739759ad3e91e15d942cc9f4b09e26c0d26963b86f5714 | Python | 197 | 8 | import pytest
import brainscore_vision
@pytest.mark.travis_slow
def test_has_identifier():
model = brainscore_vision.load_model('evresnet_50_8')
assert model.identifier == 'evresnet_50_8' |
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