sha256 stringlengths 64 64 | language stringclasses 28
values | size int32 1 491k | lines int32 1 23.2k | content stringlengths 1 200k |
|---|---|---|---|---|
5efa02ab9dadcd7c016c7de60161b08288ae64d3375ed6f287c1501b2635f3d9 | Python | 435 | 9 | # Copyright (c) 2021, NVIDIA CORPORATION. All rights reserved.
#
# NVIDIA CORPORATION and its licensors retain all intellectual property
# and proprietary rights in and to this software, related documentation
# and any modifications thereto. Any use, reproduction, disclosure or
# distribution of this software and rel... |
607aae51c4f2175eaaeccd60c0532e4554effb7c9d11352ac627d14549e6eb58 | Python | 435 | 12 | from database import ImageModel
def generate_thumbnails():
PREFIX = "[Thumbnails]"
print(f'{PREFIX} Sending request for regenerating images with non actual thumbnails', flush=True)
[generate_thumbnail(image) for image in ImageModel.objects(regenerate_thumbnail=True).all()]
def generate_thumbnail(image):... |
7c5a80d0582f82861d980c3d75c50f110b917f3a6de84d86f5963db6c3961a87 | Python | 435 | 25 | from neuron import h, gui
def test_function():
s = h.Section()
s.insert("threading_effects")
h.finitialize()
assert s(0.5).threading_effects.sum_arr() == 30.3
def test_procedure():
s = h.Section()
s.insert("threading_effects")
h.finitialize()
s(0.5).threading_effects.set_g_w(44.4... |
e704551e5f7498958edbfc7eff2caa61e0241c7e31252263b8feb171a4a23fa9 | Python | 435 | 15 | """Tests for the xcp_d.utils.qcmetrics module."""
import numpy as np
from xcp_d.utils import qcmetrics
def test_compute_dvars():
"""Run a smoke test for xcp_d.utils.qcmetrics.compute_dvars."""
n_volumes, n_vertices = 100, 10000
data = np.random.random((n_vertices, n_volumes))
dvars, std_dvars = qcm... |
45b7da90f255ce0d43ef2dea2c5e809f9c4e3edffdd0d1060ee3435b3ea985ed | Python | 436 | 14 | from PIL import Image
from lightly.transforms.pirl_transform import PIRLTransform
from .. import helpers
def test_multi_view_on_pil_image() -> None:
multi_view_transform = PIRLTransform(input_size=32)
sample = Image.new("RGB", (100, 100))
output = helpers.assert_list_tensor(multi_view_transform(sample))... |
4d938b50d2b515f8e7d4ae21cfcdfe5d2a157fe5fb3c726b3db0aca121ac2e57 | Python | 436 | 16 | from sys import argv
from msp import MSP
msp = MSP()
msp.file = __file__
msp.seed = int(argv[1])
msp.architecture["num_motifs"] = 146
msp.architecture["motif_model_spec"] = dict(
type="PSAMMotifModel",
motif_spec=dict(type="rbrc"),
exclude_names=("3P", "5P"),
)
msp.architecture["sparse_spec"] = dict(type="... |
2a7be762751b537ee8e7356b9de3261f4f42b615b8f613b4132a5b3c8dba3161 | Python | 437 | 18 | # Generated by Django 2.2.6 on 2020-05-28 10:02
from django.db import migrations, models
class Migration(migrations.Migration):
dependencies = [
('biomedisa_app', '0076_auto_20200504_1256'),
]
operations = [
migrations.AlterField(
model_name='upload',
name='ignor... |
47980dde8647b863de23741c914bffe6a5114bdccf6527fdb26cf2f2a6a43f9a | Python | 437 | 18 | # Generated by Django 3.1.2 on 2020-11-30 16:18
from django.db import migrations, models
class Migration(migrations.Migration):
dependencies = [
('biomedisa_app', '0084_auto_20201123_2306'),
]
operations = [
migrations.AlterField(
model_name='upload',
name='valid... |
d7a8ed76cfbfe5609a6eefe1a60ef6e795ed37cef82af5b0c1dc351641d7e7b6 | Python | 437 | 19 | """
The Carbon Tracker module. The following objects/decorators belong to the Public API
"""
from ._version import __version__ # noqa
from .emissions_tracker import (
EmissionsTracker,
OfflineEmissionsTracker,
track_emissions,
)
from .output_methods.base_output import OutputMethod
__all__ = [
"Emissi... |
e2a62918502eb3c0b1ad199a3505e59d320060704e1657467969ea9c1932ecb3 | Python | 437 | 18 | # Generated by Django 3.2.6 on 2023-10-18 03:33
from django.db import migrations, models
class Migration(migrations.Migration):
dependencies = [
('biomedisa_app', '0102_alter_upload_pic'),
]
operations = [
migrations.AddField(
model_name='upload',
name='validatio... |
f3de7b7e5d07fa760caca8162584dc3624dfe9da0701fdd462256b04db18bfb4 | Python | 437 | 30 | import numpy as np
from neuron import h, gui
from neuron.units import ms
def test_calls():
nseg = 1
soma = h.Section()
soma.nseg = nseg
syn = h.NetReceiveCalls(soma(0.5))
stim = h.NetStim()
stim.interval = 0.2
stim.number = 3
stim.start = 0.1
netcon = h.NetCon(stim, syn)
... |
43cae2a201d26b2384e44f14d21f4d9470b51222f567981b9a78d87b0a3698a5 | Python | 438 | 19 | import numpy as np
def fun_h(x):
# the function h(x)
# h(x) = exp(-1/t^2) for x>0 and 0 otherwise.
#
# xiayq @ 8/14/2019
#
# xiayq@zju.edu.cn
# refered to Yao, Z and Xia, Y. (2019). Manifold Fitting under Unbounded Noise, arXiv:1909.10228
x = np.array(x)
... |
6a6f1c6a1ebb01e6c373824d67d275283834127331c9130dd9e699cfd688a029 | Python | 438 | 20 | import numpy as np
from wormbrain.match import pairwise_distance
def test_pairwise_distance():
"""
A test for computing pairwise distances between two sets of points.
"""
A = np.array([[0.0, 0.0, 0.0], [4.0, 0.0, 0.0]])
B = np.array([[0.0, 4.0, 0.0], [0.0, 0.0, 0.0]])
D = pairwise_distance(... |
9b5d85efa90bb1661c8f387e73ca16588bc1133f8865c3a4c40915afb5786de0 | Python | 438 | 30 | from ._tools import (
encode_domains,
decode_domains,
TLSplitter
)
from ._estimators import (
TLDummy,
TLCenter,
TLStretch,
TLRotate,
TLEstimator,
TLClassifier,
TLRegressor,
MDWM,
)
__all__ = [
"encode_domains",
"decode_domains",
"TLDummy",
"TLSplitter",
... |
ae0c707a9cefa58c55f65ff141dd7e1f224b7a898cdc9077ebfddf12e49f82e0 | Python | 438 | 10 | import pytest
import tensorflow as tf
from psychrnn.tasks.perceptual_discrimination import PerceptualDiscrimination
from psychrnn.backend.curriculum import Curriculum
def test_get_generator_function_deprecation(capfd):
pds = [PerceptualDiscrimination(dt = 10, tau = 100, T = 2000, N_batch = 50, coherence = .7 - i/5) f... |
b7f0346de2346f40e4433d15fa8e0475bcd88f0dcdbfc921446f47b0a416c11e | Python | 438 | 14 | #!/usr/bin/env python
from __future__ import print_function
import json, sys
try:
json.load( open( sys.argv[1], "r" ))
except ValueError as e:
print( "ValueError: {0}".format( e ) )
print( "{0}:0:0: error: validating json file.".format( sys.argv[1] ) )
sys.exit(1)
except TypeError as e:
print( "Typ... |
168026ec96edc60d07623a120558e4b2463cfced11653676505f49469a24d4ed | Python | 439 | 18 | from sys import argv
from msp import MSP
msp = MSP()
msp.batch_size = 2 * msp.batch_size // 3
msp.lr = float(msp.lr) * 2 / 3
msp.file = __file__
msp.seed = int(argv[1])
msp.architecture["motif_model_spec"]["motif_width"] = 9
msp.architecture["motif_model_spec"]["motif_feature_extractor_spec"] = dict(
type="FCMot... |
1b161b1003295faed72ebc670e082376790c0b7eb83bf3f78be391546915595e | Python | 439 | 18 | # Generated by Django 3.2.6 on 2024-07-12 08:26
from django.db import migrations, models
class Migration(migrations.Migration):
dependencies = [
('biomedisa_app', '0110_repository_users'),
]
operations = [
migrations.AddField(
model_name='upload',
name='scaling',... |
51a70ac1fed550003d1838100e6ef0809a969a1e59388ca2526e4b32b12fc9f1 | Python | 439 | 18 | from Configurations import CNN
import numpy as np
import tensorflow as tf
import random as random
'''
NOTE:
Get numpy, TensorFlow and random packages here and initialize random seeds.
See also create_xoroshiro128p_states in ufunc.py.
'''
seed = CNN.GLOBALSEED
# Initialize seeds
np.random.seed(seed)
tf.compat.v1.set... |
762cff0a4b828c99e311c1eed6ca57c865f030aae127e1619d82101a32e683ed | Python | 439 | 18 | from sys import argv
from msp import MSP
msp = MSP()
msp.batch_size = 2 * msp.batch_size // 3
msp.lr = float(msp.lr) * 2 / 3
msp.file = __file__
msp.seed = int(argv[1])
msp.architecture["motif_model_spec"]["motif_width"] = 9
msp.architecture["motif_model_spec"]["motif_feature_extractor_spec"] = dict(
type="FCMot... |
a21a72976f1c3389d490a3e0413ec8cf45f1298078fcc5d773439dd9b1d9948a | Python | 439 | 18 | # Generated by Django 2.2.2 on 2019-08-19 13:59
from django.db import migrations, models
class Migration(migrations.Migration):
dependencies = [
('biomedisa_app', '0047_remove_upload_stride_size_refining'),
]
operations = [
migrations.AddField(
model_name='upload',
... |
a45c5764fe0a584d9bd869832e04a64c7716aef97347f039e67b73a36b2ca31b | Python | 439 | 16 | from ethoscope.hardware.interfaces.odour_delivery_device import OdourDelivererInterface
import time
class ZeroEr(OdourDelivererInterface):
def _warm_up(self):
for i in range(self._n_channels):
self._move_to_pos(i+1,1)
time.sleep(.5)
self._move_to_pos(i + 1, 2)
... |
ab586aebf5add9b76893979da053456170cd6d27e1e1d3031534c039a5c08d70 | Python | 439 | 18 | from sys import argv
from msp import MSP
msp = MSP()
msp.batch_size = 2 * msp.batch_size // 3
msp.lr = float(msp.lr) * 2 / 3
msp.file = __file__
msp.seed = int(argv[1])
msp.architecture["motif_model_spec"]["motif_width"] = 9
msp.architecture["motif_model_spec"]["motif_feature_extractor_spec"] = dict(
type="FCMot... |
34e914c299dc8c1bbc9f26f21c93216a0c849fa10b4f30038dea6ad907b093a0 | Python | 440 | 10 | import pandas as pd
df_train = pd.read_csv("data/datasets/CLEAN_dataset/split100.csv",sep="\t")
print(df_train)
df_train.to_json("data/datasets/CLEAN_dataset/CLEAN_dataset_train.json")
df_test_valid = pd.read_csv("data/datasets/CLEAN_dataset/price.csv",sep="\t")
print(df_test_valid)
df_test_valid.to_json("data/datase... |
380039108c4eb51a22fb41178ae21245d8c6041335365dc219c84ec1dbbbcc34 | Python | 440 | 18 | # Generated by Django 3.2.6 on 2022-05-30 13:13
from django.db import migrations, models
class Migration(migrations.Migration):
dependencies = [
('biomedisa_app', '0089_auto_20220527_1425'),
]
operations = [
migrations.AddField(
model_name='upload',
name='validat... |
509f7c32a14691b685b3af1d717e0fa7b75595aa89f71e0d286af011f30fb669 | Python | 440 | 19 | from Configurations import CNN
import numpy as np
import tensorflow as tf
import random as random
'''
NOTE:
Get numpy, TensorFlow and random packages here and initialize random seeds.
See also create_xoroshiro128p_states in ufunc.py.
'''
seed = CNN.GLOBALSEED
# Initialize seeds
np.random.seed(seed)
tf.compat.v1.set... |
76860a6dacace32a69c51f35c62c2e3149094af3db5926d75cc9b9501e2c384f | Python | 440 | 18 | # Generated by Django 2.1.5 on 2019-03-13 08:54
from django.db import migrations, models
class Migration(migrations.Migration):
dependencies = [
('biomedisa_app', '0036_auto_20190312_1945'),
]
operations = [
migrations.AlterField(
model_name='upload',
name='only'... |
94efc2c761b25724e01d6f62de7070d2307a7340b77648e7f88594716b7b4a27 | Python | 440 | 15 | from OscopeBootstrap.SyntheticDataset import GetSimISyntheticData
def test_data_generation_single_group():
data, _, _ = GetSimISyntheticData(NG=2, G=10, N=100, noiseLevel=3, ngroups=1)
G, N = data.shape
assert G == 10
assert N == 100
def test_data_generation_three_groups():
data, _, _ = GetSimIS... |
a49172b94b74bc152f89709a0c307c4849a226a23cd6ffef2e9e492d4fdf9fd2 | Python | 440 | 13 | """
This module sets up and stores configuration parameter sets for diverse elements of the platform
including experiments, environments, larva models and tracker-specific data formats
used to import experimental datasets from different labs.
"""
from __future__ import annotations
__displayname__ = "Available confi... |
f90b25b9ef977946f1c150f2a1beb79445a56c3d915530584ffe62f2bd9de954 | Python | 440 | 13 | import tqdm
from modular_splicing.motif_names import get_motif_names
from modular_splicing.fit_rbns.train import train_21x2_model
from modular_splicing.fit_rbns.rbns_data import RBNSData
psam_names = get_motif_names("rbns")
motifs = RBNSData("../data/500k_binary_rbns_dataset/").names
for seed in range(5):
for mot... |
05d06d3adfe45d00f0ce4523211ac7b9cacb71a908697cd2ea0c7b463ef2860e | Python | 441 | 17 | from Configurations import config as cfg
###############################################################################
# SIMULATION PARAMETERS
# number of simulation parameters
idxSimTypes = len(cfg.EnumSimParams)
# base values of simulation parameters
sim = [0] * idxSimTypes
# acf parameters
correlatorP = 16
co... |
44cf6a4bc15fa924c0fc7df278766d2a6b6766bfc881c9c8f9ffcb3844e98ade | Python | 441 | 23 | from sys import argv
from msp import MSP
from msp_donorlike import setup_as_adjusted_donor
msp = MSP()
msp.file = __file__
msp.seed = int(argv[1])
setup_as_adjusted_donor(msp)
msp.architecture["sparse_spec"] = dict(
type="ParallelSpatiallySparse",
sparse_specs=[
dict(type="NoSparsity"),
msp.... |
e115fbebeae4fc15254dbc59ebaceea2cb59827e4a31b92404c232ff2a4f525d | Python | 441 | 20 | # -*- coding: utf-8 -*-
# Generated by Django 1.11 on 2018-03-09 12:49
from __future__ import unicode_literals
from django.db import migrations
class Migration(migrations.Migration):
dependencies = [
('biomedisa_app', '0015_auto_20180220_1616'),
]
operations = [
migrations.RenameField(
... |
3789a3bdea6ead1ed5e9408584773645c58471c5ab2c0194fc8cc291d9d78dc7 | Python | 442 | 7 | from BatmanNet.data.molfeaturegenerator import get_available_features_generators, get_features_generator
from BatmanNet.data.molgraph import BatchMolGraph, get_atom_fdim, get_bond_fdim, mol2graph
from BatmanNet.data.molgraph import MolGraph, BatchMolGraph, MolCollator
from BatmanNet.data.moldataset import MoleculeDatas... |
247cef3d65ef611bf9be37ce4c96bb6479e49db115cd08207291d8c954180201 | Python | 443 | 15 | # pylint: disable=wildcard-import
"""Video action recognition."""
from __future__ import absolute_import
from .actionrec_vgg16 import *
from .actionrec_inceptionv1 import *
from .actionrec_inceptionv3 import *
from .actionrec_resnetv1b import *
from .c3d import *
from .p3d import *
from .r2plus1d import *
from .i3d_res... |
39122701587f71621fc706855926e5491c704fe8c6d395cf4676134c01d22b2e | Python | 443 | 19 | #!/usr/bin/env python3
# -*- coding: utf-8 -*-
"""
Created in December 2019
@author: Quentin Lutz <qlutz@enst.fr>
"""
class Log:
"""Log class for verbosity features"""
def __init__(self, verbose: bool = False):
self.verbose = verbose
self.log = ''
def print_log(self, *args):
"""Fi... |
bac438a25bf48aa80663ce8e5608868d7fd31d5aae3f4b88d8906c762261e50f | Python | 443 | 18 | import abc
from typing import List
from carbonserver.api.schemas import User, UserAutoCreate
class Users(abc.ABC):
@abc.abstractmethod
def create_user(self, user: UserAutoCreate) -> User:
raise NotImplementedError
@abc.abstractmethod
def get_user_by_id(self, user_id: int) -> User:
ra... |
c2daa5844fae8bf32d86053241593bb8ec0a0d72be76e49571bb002b1456276f | Python | 443 | 18 | # Generated by Django 3.2.6 on 2024-03-15 06:59
from django.db import migrations, models
class Migration(migrations.Migration):
dependencies = [
('biomedisa_app', '0104_alter_profile_storage_size'),
]
operations = [
migrations.AddField(
model_name='upload',
name=... |
1210814944095a82ff85c87d51cefd21aa0c958f8da8dfb40d2132ac7d68e152 | Python | 444 | 24 | from nitorch import io
import torch
root = '.'
marker = 'calb'
root += '/warp2oct'
neun = root + f'/{marker}.nii.gz'
infrasupra = root + '/infrasupra.nii.gz'
neun = io.map(neun)
infrasupra = io.map(infrasupra)
dat = neun.fdata().squeeze()
mask = infrasupra.data().squeeze() >= 2
norm = (dat*mask).sum([0, 1]).clamp... |
35cbfabf60fea2e1ea251c7b7b6c0995440077e9e8cd8909c4a6bda7b2f59d80 | Python | 444 | 14 | # ruff: noqa F401
"""
Matplotlib Renderers
====================
This submodule contains renderer objects which define renderer behavior used
within the Exporter class. The base renderer class is :class:`Renderer`, an
abstract base class
"""
from .base import Renderer
from .vega_renderer import VegaRenderer, fig_to_v... |
add35fffb18533aaedffac7bea00673bf003b12e67ab89499072478c17340850 | Python | 444 | 11 | from scipy.stats import ttest_rel
def whitebox_mem_score(output_1, output_2, label, labels):
# constrastive output, unique feature output, canary label, all labels
indxs = (labels == label).nonzero()[0]
output_1_f = output_1[indxs, label]
output_2_f = output_2[indxs, label]
m = (output_2_f - outpu... |
d786227ae56d0a665eeae03ba68d9a52e73491ba3c04119707364d8f79f40593 | Python | 444 | 16 | import sys
from typing import TYPE_CHECKING
if TYPE_CHECKING:
from ._colorscale import Colorscale
from ._hoverlabel import Hoverlabel
from ._line import Line
from . import hoverlabel
else:
from _plotly_utils.importers import relative_import
__all__, __getattr__, __dir__ = relative_import(
... |
eb45b04a968389b97f0cb8be93f41bd585c69f0638addb261d9e1053f015a8ef | Python | 444 | 26 | """Module proxies :mod:`galaxy.util.checkers` for backward compatibility.
External datatypes may make use of these functions.
"""
from galaxy.util.checkers import (
check_binary,
check_bz2,
check_gzip,
check_html,
check_image,
check_zip,
is_bz2,
is_gzip,
)
__all__ = (
"check_binar... |
028054cfcf06d196aa175ef8729f61c6c69ff7a48c209172c75b2a25e142e03b | Python | 445 | 20 | # -*- coding: utf-8 -*-
# Generated by Django 1.11 on 2018-05-18 07:55
from __future__ import unicode_literals
from django.db import migrations, models
class Migration(migrations.Migration):
dependencies = [
('biomedisa_app', '0018_upload_cnn'),
]
operations = [
migrations.AddField(
... |
0b207bc505aac314e83749f1e8a97544336fb03b1c2675d35f3eaca5204dfcdd | Python | 445 | 16 | from pl_bolts.models.self_supervised.swav.swav_module_cifar import SwAV
from pl_bolts.models.self_supervised.swav.swav_resnet import resnet18, resnet50
from pl_bolts.models.self_supervised.swav.transforms import (
SwAVEvalDataTransform,
SwAVFinetuneTransform,
SwAVTrainDataTransform,
)
__all__ = [
"SwAV... |
1c74b9ec21c6531081a22fa7e5d2425092a066a131119bccb27f5412884f7297 | Python | 445 | 22 | import numpy as np
from neuron import gui
from neuron import h
def nernst(ca):
return h.nernst(ca.cai, ca.cao, h.ion_charge("ca_ion"))
def simulate(mech_name, compute_eca=nernst):
s = h.Section()
s.insert(mech_name)
s.nseg = 1
h.stdinit()
ca = s(0.5).ca_ion
eca_expected = compute_eca(c... |
4ef00fae4c3cf980bef6bbe6ab52820bf788cae85cc8f884be0291a692804eb6 | Python | 445 | 18 | # Generated by Django 3.1.2 on 2020-11-10 11:39
from django.db import migrations, models
class Migration(migrations.Migration):
dependencies = [
('biomedisa_app', '0082_auto_20201103_1606'),
]
operations = [
migrations.AddField(
model_name='upload',
name='automat... |
5d61f6b03400c37502a8eff2df531e57cad9f54f7ab077c219c46db67ea3e9ed | Python | 445 | 17 | #!/usr/bin/env python3
# Copyright (c) Facebook, Inc. and its affiliates. All Rights Reserved.
"""Set up Environment."""
from iopath.common.file_io import PathManagerFactory
_ENV_SETUP_DONE = False
pathmgr = PathManagerFactory.get(key="pyslowfast")
checkpoint_pathmgr = PathManagerFactory.get(key="pyslowfast_checkpoi... |
5faf6c7a9113587d69a3d61716e6e9a6f6652de19d7e5ab1a0d1018a78a1a770 | Python | 445 | 18 | #!/usr/bin/env python3
# -*- coding: utf-8 -*-
"""Tests for tfidf.py"""
import unittest
import numpy as np
from scipy import sparse
from sknetwork.utils.tfidf import get_tfidf
class TestTFIDF(unittest.TestCase):
def test_tfidf(self):
count = sparse.csr_matrix(np.array([[0, 1, 2], [0, 2, 1], [0, 0, 1]])... |
82dae54007e4c1fca9d14dd206caca6be33151f652dce72b269bb7bb44bc74cb | Python | 445 | 18 | """Custom Exceptions"""
# ENVIRONMENT HANDLING
class UninterpretableObservationSpace(Exception):
"""The environment has an n_steps space that can currently not be handled by our implementation."""
pass
class IncompatibleModelException(Exception):
"""The model applied to the given environment cannot han... |
e07882641c66e41b526e4a2381e6c7073428429d629a9cb54008eb7a65cdd58a | Python | 445 | 18 | # Generated by Django 3.2.6 on 2023-01-11 12:21
from django.db import migrations, models
class Migration(migrations.Migration):
dependencies = [
('biomedisa_app', '0096_alter_upload_resnet'),
]
operations = [
migrations.AlterField(
model_name='upload',
name='resn... |
e3b86f303cd953cbab9ec9364841b8bb6c2e68455f3a428a1dd4057f60fb1843 | Python | 445 | 22 | import sys
def get_distance(sites_file):
chr_id = ''
with open(sites_file) as n:
while True:
try:
x = next(n)
y = next(n)
x = x.strip().split('\t')
y = y.strip().split('\t')
if x[0] == y[0] and int(y[1])-int(x[1]) < 1000:
print(str(int(y[1])-int(x[1]))+"\t"+sites_file)
... |
f6aa62dce60ec60ca3076808219ab279adc89be9636d6e00da946e75c98e6be9 | Python | 445 | 12 | import paramiko
import os
def agx_update(best_model_path):
ssh=paramiko.SSHClient()
ssh.load_host_keys(os.path.expanduser(os.path.join("~",".ssh","known_hosts")))
ssh.set_missing_host_key_policy(paramiko.AutoAddPolicy())
ssh.connect("## IP of edge device", username=" ", password=" ", look_for_keys=Fals... |
03edd6c18df94a7bb245ea6935770ec02faa8a59acc10574c95091c01c2f7864 | Python | 446 | 15 | dependencies = ['torch', 'numpy', 'resampy', 'soundfile']
from torchvggish.vggish import VGGish
model_urls = {
'vggish': 'https://github.com/harritaylor/torchvggish/'
'releases/download/v0.1/vggish-10086976.pth',
'pca': 'https://github.com/harritaylor/torchvggish/'
'releases/download/... |
50c2ae0c2ed8490feb430df598e4a521fcb73084085ee51b5af3338d3b769658 | Python | 446 | 22 | from sys import argv
from msp import MSP
from msp_donorlike import setup_as_adjusted_acceptor
msp = MSP()
msp.file = __file__
msp.seed = int(argv[1])
setup_as_adjusted_acceptor(msp)
msp.architecture["sparse_spec"] = dict(
type="ParallelSpatiallySparse",
sparse_specs=[
dict(type="NoSparsity"),
... |
87ae12a86818056058366bfb57ff586b1b9682d5c7a2015b2f842421bdc44a63 | Python | 446 | 16 | import sys
from typing import TYPE_CHECKING
if TYPE_CHECKING:
from ._tickfont import Tickfont
from ._tickformatstop import Tickformatstop
from ._title import Title
from . import title
else:
from _plotly_utils.importers import relative_import
__all__, __getattr__, __dir__ = relative_import(
... |
f1e297866c09fb119e706830dcb052123a55d761d99ea5790beaee465c2d5007 | Python | 446 | 16 | import torch
from strategies.basic import MultiSiteLearningStrategy
class Baseline(MultiSiteLearningStrategy):
name: str = 'baseline'
def training_step(self, batch, batch_idx, **kwargs) -> torch.Tensor:
inputs, labels = batch
outputs = self.forward(inputs)
standard_loss = self.crite... |
67ac557890f9b10743ec8b2c7a1e3b011083bce0a75024ecc315f340e5d5647f | Python | 447 | 18 | import os
import numpy as np
import cv2
os.chdir('..\\DATA_extend')
target_dir = os.getcwd()
folder = next(os.walk('.'))[1]
for x in folder:
#for ext in range(50,250): # medi
for ext in range(50, 350): # bright
#for ext in range(50, 300): # black
directory = str(ext)
path = os.path.join(... |
98355d37ce1e90c486db6b69808812ce310d050fac1cbd54c94b73f47c79145e | Python | 447 | 17 | """
See what happens if you print(abf) for every ABF in the data folder
"""
import os
import sys
PATH_HERE = os.path.abspath(os.path.dirname(__file__))
PATH_DATA = os.path.abspath(PATH_HERE+"../../../data/abfs/")
PATH_SRC = os.path.abspath(PATH_HERE+"../../../src/")
sys.path.insert(0, PATH_SRC)
import pyabf
import glo... |
b349d39a448a82d0a0ec719b010862d3e672ee2015bc2d5b7ce8dac9e0f01ca9 | Python | 447 | 17 | import sys
from typing import TYPE_CHECKING
if TYPE_CHECKING:
from ._circle import Circle
from ._fill import Fill
from ._line import Line
from ._symbol import Symbol
from . import symbol
else:
from _plotly_utils.importers import relative_import
__all__, __getattr__, __dir__ = relative_impo... |
ef4d62eaeda8acada4bdfe7d64e084939f2acc1534138dc91c1bff1ef9bc26e8 | Python | 447 | 12 | from . import _utils
from . import behavior
from . import fiber
from . import analysis
from .behavior import Behavior, MultiBehavior
from .fiber import Fiber
from .analysis import Session, MultiSession, Analysis, MultiAnalysis
#__all__ = behavior.__all__ + fiber.__all__ + analysis.__all__ #+ _utils.__all__ +
# FDG :... |
f3164cbd45ce46339f1b954017189158aaec9daa02bd1b92ac74859b576e9465 | Python | 447 | 18 | import importlib
from .data import preprocess
from .run_scbig import run_scbig
from .utils import setup_seed, sample, read_data
try:
from importlib.metadata import version
except ModuleNotFoundError:
from pkg_resources import get_distribution
version = lambda name: get_distribution(name).version
__name_... |
03df495b146e01bfbe3af6a7862fd8291566cfe88126e17ce7a4345906203fec | Python | 448 | 19 | """Here are a VAE and GAN."""
from pl_bolts.models.autoencoders.basic_ae.basic_ae_module import AE
from pl_bolts.models.autoencoders.basic_vae.basic_vae_module import VAE
from pl_bolts.models.autoencoders.components import (
resnet18_decoder,
resnet18_encoder,
resnet50_decoder,
resnet50_encoder,
)
__a... |
11dc5dcf36f10d33d9733002d39da93c4d36672b41d95be7071d577510a4972f | Python | 448 | 14 | from setuptools import setup, find_packages
setup(
name='mord',
version="0.6",
description='Ordinal regression models',
long_description=open('README.rst').read(),
author='Fabian Pedregosa',
author_email='f@bianp.net',
url='https://pypi.python.org/pypi/mord',
packages=find_packages(excl... |
4ade2057614b2c60c65d0fa47d5ecb156b23f88105063e6715b65b9b4aa32556 | Python | 448 | 16 | """
test to see if the same pyABF can be imported in Python 2.7 and 3.6
"""
import sys
import os
PATH_HERE = os.path.abspath(os.path.dirname(__file__))
PATH_DATA = os.path.abspath(PATH_HERE+"../../../data/abfs/")
PATH_SRC = os.path.abspath(PATH_HERE+"../../../src/")
sys.path.insert(0, PATH_SRC)
print("PYTHON %d.%d"%... |
7a671d0a371fb852a1da9dad6ae4ea70d8e5d8007d172aee51ed1319e804516f | Python | 448 | 14 | """Test functions for specparam.params.aperiodic."""
from specparam.params.aperiodic import *
###################################################################################################
###################################################################################################
def test_compute_knee_f... |
855071bca8b769a26ea6c2d72371017d6c7e91586cc044f7812d5c9dcafd3d57 | Python | 448 | 14 | from torch.nn import Module
from pl_bolts.models.self_supervised import resnets
from pl_bolts.utils.semi_supervised import Identity
def torchvision_ssl_encoder(
name: str,
pretrained: bool = False,
return_all_feature_maps: bool = False,
) -> Module:
pretrained_model = getattr(resnets, name)(pretraine... |
88f7c8035c118b3675a39ac18191e6511fa0787e1647cbff1ee21bbe378d7560 | Python | 448 | 13 | import shutil
import os
def transfer_mechanisms(source, destination):
"""
:param source: path to the model directory (BluePyOpt output), see examples for how
this directory should be structured
:param destination: path to BasalGanglia/data/your_brain_area/neuron_type/model_name
:r... |
9d8ccaf705c83bc2604065d8673ea9422a65575d249a312a05b53134ef250255 | Python | 448 | 18 | # Generated by Django 3.2.6 on 2023-01-11 11:03
from django.db import migrations, models
class Migration(migrations.Migration):
dependencies = [
('biomedisa_app', '0095_auto_20230111_1156'),
]
operations = [
migrations.AlterField(
model_name='upload',
name='resne... |
fa7efef986680e4626dcc6ac19fbdefb633c4d9cfbcef06649207de12cb53ab0 | Python | 448 | 19 | """
Add a top level method to the ABF class to simplify access to the headers
"""
import sys
import os
PATH_HERE = os.path.abspath(os.path.dirname(__file__))
PATH_DATA = os.path.abspath(PATH_HERE+"../../../data/abfs/")
PATH_SRC = os.path.abspath(PATH_HERE+"../../../src/")
sys.path.insert(0, PATH_SRC)
import pyabf
ab... |
2415471c141cac5d80daee3e76854e226e186de76394b41608ddc4ac591c0a51 | Python | 449 | 16 | from sys import argv
from msp import MSP, amm_mean40v1
msp = MSP()
msp.file = __file__
msp.seed = int(argv[1])
msp.architecture["num_motifs"] = 82
msp.architecture["motif_model_spec"] = dict(
type="PSAMMotifModel",
motif_spec=dict(type="rbns"),
include_names=amm_mean40v1,
)
msp.architecture["sparse_spec"] ... |
5240d712f52a3e364dbfd61b0cbe8653b25ed4a84d8badeb0fb4a857b944da28 | Python | 449 | 18 | # Generated by Django 3.2.6 on 2024-03-15 07:23
from django.db import migrations, models
class Migration(migrations.Migration):
dependencies = [
('biomedisa_app', '0105_upload_header_file'),
]
operations = [
migrations.AlterField(
model_name='upload',
name='heade... |
ee305b258212e174d7a1b1a18d6cf2039cdc857748b467a5ed0349092b8cd2e8 | Python | 449 | 21 | from contextlib import contextmanager
@contextmanager
def obj_in_module(module, name, obj):
backup_obj = getattr(module, name, None)
setattr(module, name, obj)
try:
yield
finally:
if backup_obj:
setattr(module, name, backup_obj)
def assert_equal_sequence(x, y):
assert ... |
648c158c9dab770a177cf5849a56ec94789dfd1a642809942d23395b9dc1e1d1 | Python | 450 | 20 | # -*- coding: utf-8 -*-
# Generated by Django 1.11 on 2018-01-03 13:07
from __future__ import unicode_literals
from django.db import migrations, models
class Migration(migrations.Migration):
dependencies = [
('biomedisa_app', '0010_upload_friendac'),
]
operations = [
migrations.AddField... |
8b0355da3b24fb40581ffd4d97effcec8b2b04ee10de0f4b0b1fe9ec199753ff | Python | 450 | 16 | import pathlib
import tempfile
import zipfile
def retrieve_data(zip_file):
"""Extract contents of data zip file and return sorted list of files"""
zpath = pathlib.Path(__file__).resolve().parent / "data" / zip_file
# unpack
arc = zipfile.ZipFile(str(zpath))
# extract all files to a temporary dire... |
631b937348ec31d8745ca24af62b5331cd123362764ff9a9990df70a23a7beee | Python | 451 | 18 | import sys
from pyoperant.interfaces import base_
class ConsoleInterface(base_.BaseInterface):
"""docstring for ComediInterface"""
def __init__(self,*args,**kwargs):
super(ConsoleInterface, self).__init__(*args,**kwargs)
pass
def _read(self,prompt=''):
""" read from keyboard input
... |
68790ae013257e85f3e13f004e21c9a5daa703b9338419c9dee487b65f697f88 | Python | 451 | 16 | import os
import pickle
def pickle_dump(file, var):
with open('../../data/preprocessed_data/' + file +
'.pickle', 'wb') as handle:
pickle.dump(var, handle, protocol=pickle.HIGHEST_PROTOCOL)
def pickle_load(file):
return pickle.load(open('../../data/preprocessed_data/' + file +
... |
1a78807c97544c24c7e9461673b09fbf9252873b94577863c1f7885c78374bb0 | Python | 452 | 20 | # -*- coding: utf-8 -*-
# Generated by Django 1.11.15 on 2018-09-28 16:53
from __future__ import unicode_literals
from django.db import migrations, models
class Migration(migrations.Migration):
dependencies = [
('biomedisa_app', '0021_auto_20180522_1523'),
]
operations = [
migrations.Ad... |
808e702d3150a44502cb7c637e0bb71153d5ee3b3ede6a85e2e8ec1a61f29bbd | Python | 452 | 26 | import numpy as np
from neuron import h, gui
from neuron.units import ms
nseg = 1
s = h.Section()
s.insert("ionic")
s.nseg = nseg
ena_hoc = h.Vector().record(s(0.5)._ref_ena)
t_hoc = h.Vector().record(h._ref_t)
h.stdinit()
h.tstop = 5.0 * ms
h.run()
ena = np.array(ena_hoc.as_numpy())
t = np.array(t_hoc.as_numpy()... |
a5ad5afd368b7a5c6f64930f5794fbd52029db94c6e229872907b20e36d7a6d9 | Python | 452 | 20 | # -*- coding: utf-8 -*-
# Generated by Django 1.11.15 on 2018-10-01 14:03
from __future__ import unicode_literals
from django.db import migrations, models
class Migration(migrations.Migration):
dependencies = [
('biomedisa_app', '0022_upload_pid'),
]
operations = [
migrations.AddField(
... |
df061f593134feb3b75ea99ad5e746c23cfa998c5c0121af688f0e459054dfaa | Python | 452 | 20 | # -*- coding: utf-8 -*-
# Generated by Django 1.11 on 2017-05-17 09:56
from __future__ import unicode_literals
from django.db import migrations, models
class Migration(migrations.Migration):
dependencies = [
('biomedisa_app', '0001_initial'),
]
operations = [
migrations.AlterField(
... |
fa76c92046bc7d965c8b3876f323f7d44ee9a6ab80b97c3589377aec4ed2a1e3 | Python | 453 | 19 | import pytest
from hobj.learning_models.random_guesser import RandomGuesser
@pytest.fixture
def dummy_learner() -> RandomGuesser:
return RandomGuesser(seed=0)
def test_dummy_learner_deterministic(dummy_learner):
ntests = 10
actions = []
expected_actions = [1, 1, 1, 0, 0, 0, 0, 0, 0, 1]
for i in... |
2ee0ab4e4d14ce6317509980b9b58bfea4a8dd97da8c92fff9ae1c8ed036381e | Python | 454 | 22 | #!/usr/bin/env python
'''
Output the parameters that makemodel supports with their ranges
'''
import makemodel
import json, sys
from collections import OrderedDict
#extract from arguments to makemodel
opts = makemodel.getoptions()
create = 'CREATE TABLE params (rmse DOUBLE, top DOUBLE, R DOUBLE, auc DOUBLE'
#every... |
470077edcbdbf016e5e223ca68ae9e856ca5de71f72c56e9de191f70ef368f53 | Python | 454 | 27 | import numpy as np
from neuron import h, gui
from neuron.units import ms
def test_net_receive_initial():
nseg = 1
soma = h.Section()
soma.nseg = nseg
syn = h.InitSyn(soma(0.5))
syn.a0 = 329.012
stim = h.NetStim()
nc = h.NetCon(stim, syn, 0, 0.0, 0.1)
h.stdinit()
assert nc.wcn... |
4734016dfee9a8d615d1c764f9fbe520dd01cbf67eb4a92865f2103a7cc30c5d | Python | 454 | 20 | from sys import argv
from msp import MSP
msp = MSP()
msp.batch_size = 2 * msp.batch_size // 3
msp.lr = float(msp.lr) * 2 / 3
msp.lr *= 0.5
msp.file = __file__
msp.seed = int(argv[1])
msp.architecture["motif_model_spec"]["motif_width"] = 9
msp.architecture["motif_model_spec"]["motif_feature_extractor_spec"] = dict(
... |
68317371ba8f937ce59d2f034b73c61ad4e668343459417f849588734bc40f3b | Python | 454 | 26 | import numpy as np
from neuron import h, gui
from neuron.units import ms
nseg = 1
s = h.Section()
s.insert("read_only")
s.nseg = nseg
x_hoc = h.Vector().record(s(0.5)._ref_x_read_only)
t_hoc = h.Vector().record(h._ref_t)
h.stdinit()
h.tstop = 1.0 * ms
h.run()
x = np.array(x_hoc.as_numpy())
t = np.array(t_hoc.as_n... |
a6becbf02f3a52296eaf5cce67183e25ae3111fdf4de6080d4e5a8c4779cf27a | Python | 454 | 20 | from sys import argv
from msp import MSP
msp = MSP()
msp.batch_size = 2 * msp.batch_size // 3
msp.lr = float(msp.lr) * 2 / 3
msp.lr *= 0.1
msp.file = __file__
msp.seed = int(argv[1])
msp.architecture["motif_model_spec"]["motif_width"] = 9
msp.architecture["motif_model_spec"]["motif_feature_extractor_spec"] = dict(
... |
ace3f049d2e8a95338ba8286c80e35df04c9f013b32f2122b8dd60a38c79ccd1 | Python | 454 | 20 | from sys import argv
from msp import MSP
msp = MSP()
msp.batch_size = 2 * msp.batch_size // 3
msp.lr = float(msp.lr) * 2 / 3
msp.lr *= 0.1
msp.file = __file__
msp.seed = int(argv[1])
msp.architecture["motif_model_spec"]["motif_width"] = 9
msp.architecture["motif_model_spec"]["motif_feature_extractor_spec"] = dict(
... |
b26af89142495543726c13defd4913c43476accd46eb13f99375c96c9eb5e28c | Python | 454 | 16 | from pkgutil import extend_path
# look for every subdir with flash_attn base name such that fa2 and fa4 can be co-installed
__path__ = extend_path(__path__, __name__)
__version__ = "2.8.4"
from flash_attn.flash_attn_interface import (
flash_attn_func,
flash_attn_kvpacked_func,
flash_attn_qkvpacked_func,
... |
c37c4899aaf7f7787ea52d2e9eca486757fde6f5375bd27aa16f9cf981037840 | Python | 455 | 14 | import unittest
from svim.SVIM_inter import is_similar
class TestSVIMInter(unittest.TestCase):
def test_is_similar(self):
self.assertFalse(is_similar("chrI", 0, 100, "chrII", 0, 100))
self.assertTrue(is_similar("chrI", 0, 100, "chrI", 0, 100))
self.assertTrue(is_similar("chrI", 0, 100, "c... |
1d9d28387d4e7a9e2e0fd41bac07b4d2910d14dad31909b76638b992259677a5 | Python | 456 | 18 | from sys import argv
from msp import MSP
msp = MSP()
msp.file = __file__
msp.seed = int(argv[1])
msp.architecture["motif_model_spec"]["motif_width"] = 9
msp.architecture["motif_model_spec"]["motif_feature_extractor_spec"] = dict(
type="FCMotifFeatureExtractor",
extra_compute=10,
num_compute_layers=1
)
ass... |
2b97ba9e925cb39cf4029df3096e8f27a12031186f05f6265c1bb1552e188788 | Python | 456 | 20 | # -*- coding: utf-8 -*-
# Generated by Django 1.11 on 2018-02-20 15:16
from __future__ import unicode_literals
from django.db import migrations, models
class Migration(migrations.Migration):
dependencies = [
('biomedisa_app', '0014_auto_20180220_1525'),
]
operations = [
migrations.Alter... |
3e848727aa7ebb28b6ace8ca78b6772b41db11f796cbc3402afe0899f9a3d822 | Python | 456 | 26 | from sys import argv
from msp import MSP
msp = MSP()
msp.file = __file__
msp.seed = int(argv[1])
msp.decay_per_epoch = 0.9 ** (5509 / 162706)
msp.lr = 1e-3
msp.window = 40
msp.batch_size = 32
msp.architecture = dict(
type="SplicePointIdentifier",
cl=40,
asymmetric_cl=(20, 2),
hidden_size=100,
n_l... |
78cde4c53875de45e7fbfd8da8beabd96e97f3807ff3fe303f63f554dfb980f8 | Python | 456 | 21 | from .sampling import sample_gaussian_spd, generate_random_spd_matrix
from .simulated import (
make_covariances,
make_matrices,
make_masks,
make_gaussian_blobs,
make_outliers,
make_classification_transfer,
)
__all__ = [
"sample_gaussian_spd",
"generate_random_spd_matrix",
"make_cov... |
cc94cfc826c40d8795f71237974a0435fc34ceee057f47daff9795703ca034a1 | Python | 456 | 27 |
from celery import shared_task
from database import TaskModel
from ..socket import create_socket
@shared_task
def long_task(n, task_id):
task = TaskModel.objects.get(id=task_id)
task.update(status="PROGRESS")
socketio = create_socket()
print(f"This task will take {n} seconds")
import time
... |
4f43439b6a8b2c6e72600eecb09961b8be23664f886aeefe4ee6d4aabbed70b8 | Python | 457 | 17 | import sys
from typing import TYPE_CHECKING
if TYPE_CHECKING:
from ._bounds import Bounds
from ._center import Center
from ._domain import Domain
from ._layer import Layer
from . import layer
else:
from _plotly_utils.importers import relative_import
__all__, __getattr__, __dir__ = relative... |
69ea21e70df60dc15cf56d21cfc66a8157c2cc4a80d32345eda34437355183f4 | Python | 457 | 18 | from nitorch import io
import torch
import os
root = '.'
root += '/lsfm/slide_center_oct'
device='cuda'
factor = 1
for i in range(8, 24):
fname = root + f'/vessels.{i:02d}.distance.nii.gz'
if not os.path.exists(fname):
continue
print(i)
f = io.map(fname)
d = f.fdata(device=device)
d = ... |
a0f5aaa131f53bdf1efa4fd4fb98597046a185b05d5f4195cf223327c95ef9a1 | Python | 457 | 20 | # -*- coding: utf-8 -*-
# Generated by Django 1.11 on 2017-06-05 23:02
from __future__ import unicode_literals
from django.db import migrations, models
class Migration(migrations.Migration):
dependencies = [
('biomedisa_app', '0008_upload_friend'),
]
operations = [
migrations.AddField(
... |
de1f81788c14a41810a37230ca6d6735dae73e56301c1624a7dc3feae16851af | Python | 457 | 19 | from sys import argv
from msp import MSP
msp = MSP()
msp.batch_size = 2 * msp.batch_size // 3
msp.lr = float(msp.lr) * 2 / 3
msp.file = __file__
msp.seed = int(argv[1])
msp.architecture["motif_model_spec"]["motif_width"] = 9
msp.architecture["motif_model_spec"]["motif_feature_extractor_spec"] = dict(
type="FCMot... |
52475a1db9a36556dc6ee9fe540a76d2a903bee27fee7df08ae6b7072656ad28 | Python | 458 | 26 | import pytest
from pyrosm import get_data
@pytest.fixture
def test_pbf():
pbf_path = get_data("test_pbf")
return pbf_path
@pytest.fixture
def helsinki_pbf():
pbf_path = get_data("helsinki_pbf")
return pbf_path
def test_invalid_filter_type(test_pbf):
from pyrosm import OSM
osm = OSM(filepa... |
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