content stringlengths 35 762k | sha1 stringlengths 40 40 | id int64 0 3.66M |
|---|---|---|
def make_user_role_table(table_name='user', id_column_name='id'):
"""
Create the user-role association table so that
it correctly references your own UserMixin subclass.
"""
return db.Table('fp_user_role',
db.Column(
'user_id', db.Integer, ... | 8e7570590686e78d2bf7f91ba3b16f14f4c42620 | 3,638,572 |
import re
def _remove_comments_inline(text):
"""Removes the comments from the string 'text'."""
if 'auto-ignore' in text:
return text
if text.lstrip(' ').lstrip('\t').startswith('%'):
return ''
match = re.search(r'(?<!\\)%', text)
if match:
return text[:match.end()] + '\n'
else:
return tex... | 463e29e1237a88e91c13a58ffea1b2ccdafd4a1d | 3,638,573 |
def wide_to_tall(df: pd.DataFrame) -> pd.DataFrame:
"""Convert a wide table to a tall table
Args:
df (pd.DataFrame): wide table
Returns:
pd.DataFrame: tall table
"""
return df.unstack().dropna().reset_index() | 50ab71d18f5fb1e4dba9207b71030c7f8ffdbcde | 3,638,574 |
def is_pj_player_plus(value):
"""
:param value: The value to be checked
:type value: Any
:return: whether or not the value is a PJ Player+
:rtype: bool
"""
return isinstance(value, list) and len(value) == 4 or len(value) == 3 | 1c4e7a7513d746d25f6b3d7964455b0735c988fc | 3,638,575 |
def pd_fuzz_partial_token_sort_ratio(col1, col2):
""" Calculate "partial token sort" ratio (`fuzz.partial_token_sort_ratio`) between two text columns.
Args:
col1 (Spark Column): 1st text column
col2 (Spark Column): 2nd text column
Returns:
Spark Column (IntegerType): result of `fuz... | d650d37d5936751f961260d98210e2d219200fe6 | 3,638,576 |
def looterCanReinforce(mine: Game) -> bool:
"""
Return True if, in the given game, the looter (the attack) can
reinforce at this moment, regardless of whether its the first or the
second time
"""
return getLooterReinforcementStatus(mine) != 0 | e73fb193cc1c621766900c1f484db90e4e21decb | 3,638,577 |
def _get_normed_sym_np(X_, _eps=DEFAULT_EPS):
"""
Compute the normalized and symmetrized probability matrix from
relative probabilities X_, where X_ is a numpy array
Parameters
----------
X_ : 2-d array_like (N, N)
asymmetric probabilities. For instance, X_(i, j) = P(i|j)
Returns
... | a6f5762a5bf41c83bd017d0661cc069f17bee618 | 3,638,578 |
def load_encoding_model():
"""Model to encode image as vector of length 4096 using 2nd to last layer of
VGG16"""
base_model = VGG16(weights='imagenet', include_top=True)
encoding_model = Model(inputs=base_model.input,
outputs=base_model.get_layer('fc2').output)
return enc... | b15f9d9b6d360a71db0fcb7fc0fa83c031f34047 | 3,638,579 |
import math
def get_geohash_radius_approximation(latitude, longitude, radius, precision, georaptor_flag=False, minlevel=1, maxlevel=12):
"""
Get the list of geohashed that approximate a circle
:param latitude: Float the longitude to get the radius approximation for
:param longitude: Float the latitud... | cf8bbc4a8323b796c4f325f4f3ab9f8e3a169fa8 | 3,638,580 |
def manage_products(request, category_id, template_name="manage/category/products.html"):
"""
"""
category = Category.objects.get(pk=category_id)
inline = products_inline(request, category_id, True)
# amount options
amount_options = []
for value in (10, 25, 50, 100):
amount_options.... | 4ece15c50e00198c422dbb452622dde938f2a9e6 | 3,638,581 |
def random_indices(X, size=None, p=None, sort_indices=True, **kwargs):
""" Get indices for a random subset of the data.
Parameters
----------
size: int
* integer size to sample (required if p=None)
p: float
* threshold percentage to keep (required if size=None)
Returns
-... | 680be93345ab5e3065a43fda5216a4ca8b986121 | 3,638,582 |
def get_facts(F5, uri):
"""
Issue a GET of the URI specified to the F5 appliance and return the result as facts.
If the URI must have a slash as the first character, add it if missing
In Ansible 2.2 found name clashing
http://stackoverflow.com/questions/40281706/cant-read-custom-fa... | 554cc7b9bf35d631c8742614142f5aa2ecaba9b4 | 3,638,583 |
from typing import Optional
from typing import Sequence
def parse_args(args: Optional[Sequence[str]] = None) -> Namespace:
"""
Parses args and validates the consistency of origin/target using the
generator
"""
parser = ArgumentParser(
prog="python -m luh3417.transfer",
description... | 475318fc9999b7b259a073e53b3b24d5ea46911a | 3,638,584 |
def parse_papers_plus_json(data):
""" Function which parses the papers_plus json and returns a pandas dataframe of the results.
Solr Field definition shown below:
<!-- Citing paper fields: papers, metadata, arxiv_metadata -->
<!-- Papers -->
<field name="sentencenum" type="pint" indexed="true" ... | 44c7a27701e265a841e07f49741f03e4b49d4b95 | 3,638,585 |
from pathlib import Path
from typing import Optional
def get_credential(config_file: Path, credential_key: str = 'api_key') -> Optional[str]:
"""
Get a single credential from yaml file. Usual case is 'api_key'
:param config_file:
:param credential_key:
:return:
"""
config = load_credential... | a3e5182c4b2e3fed777f6bd52e144a6d49e4f48f | 3,638,586 |
import functools
def authenticate_secondarily(endpoint):
"""Proper authentication for function views."""
@functools.wraps(endpoint)
def wrapper(request: HttpRequest):
if not request.user.is_authenticated:
try:
auth_result = PersonalAPIKeyAuthentication.authenticate(req... | ac7a5b63c2b556e1bb42986db8110a922485b96d | 3,638,587 |
def gather_emails_GUIDs(mailbox, search, folder):
""" Download GUID of messages passing search requirements
"""
mailbox.folder.set(folder)
return (email for email in mailbox.uids(search)) | d75ecdeaa4f95f9108276f2be236e33934d7de01 | 3,638,588 |
def pyrolite_meltsutil_datafolder(subfolder=None):
"""
Returns the path of the pyrolite-meltsutil data folder.
Parameters
-----------
subfolder : :class:`str`
Subfolder within the pyrolite data folder.
Returns
-------
:class:`pathlib.Path`
"""
return get_module_datafold... | e1ae16fff0b2fcd247c57a40e4713eb0ee13f3e7 | 3,638,589 |
from typing import List
def get_resource_record_set_cloud_formation_dict_list(hosted_zone: ResourceRecordSetList,
with_soa: str,
client: botocore.client.BaseClient, zone_id: str,
... | c7775a45763f733e2dc2392b5073f1bf18b7177c | 3,638,590 |
def _prepare_line(edges, nodes):
"""prepare a plotly scatter3d line plot so that a set of disconnected edges
can be drawn as a single line.
`edges` are values associated with each edge (that get mapped to colors
through a colorscale). `nodes` are pairs of (source, target) node indices
for each edge... | be95f58a3938b628c89639d3311799eb359c19d2 | 3,638,592 |
import getpass
def validate_password( password:str ) -> bool:
""" Validates the password again a password policy.
Args:
password ( str, required ):
password to verify.
Returns:
valid ( bool ):
True if the password meets validity requirements.... | eec09ad86d89184c4f87a8c0710e3af28f874429 | 3,638,593 |
from typing import Iterable
from typing import List
from typing import Dict
from typing import Any
def build_webhooks(
handlers_: Iterable[handlers.WebhookHandler],
*,
resources: Iterable[references.Resource],
name_suffix: str,
client_config: reviews.WebhookClientConfig,
... | fc5ca5de1f09c40e08ea8918319b07186af2fe94 | 3,638,594 |
def ndo_real(data, n):
"""mimic of gmx_fio_ndo_real in gromacs"""
return [data.unpack_real() for i in range(n)] | 875edd4c78e591fcee1b3de30f0ed62a4d0b074d | 3,638,595 |
from typing import Union
from typing import Optional
def get_field_type(field: Union[syntax.Field, syntax.Command], idl_file: syntax.IDLParsedSpec,
idl_file_path: str) -> Optional[Union[syntax.Enum, syntax.Struct, syntax.Type]]:
"""Resolve and get field type of a field from the IDL file."""
... | 19445d7a142b940ff3cd0c445e716c070eeac489 | 3,638,596 |
def get_status():
"""get the node status and return data"""
return data({}) | 0314331d249cebfeb63941961793fe9a72e0c329 | 3,638,598 |
import tokenize
def read_orc(path, columns=None, storage_options=None, **kwargs):
"""Read cudf dataframe from ORC file(s).
Note that this function is mostly borrowed from upstream Dask.
Parameters
----------
path: str or list(str)
Location of file(s), which can be a full URL with protoco... | 2f26a088cd849fc21c171767a0db276844341b11 | 3,638,599 |
import torch
def get_bernoulli_sample(probs):
"""Conduct Bernoulli sampling according to a specific probability distribution.
Args:
prob: (torch.Tensor) A tensor in which each element denotes a probability of 1 in a Bernoulli distribution.
Returns:
A Tensor of binary samp... | 14c45741d47f5eaff24893471425ddd4de7e2e4b | 3,638,601 |
def angle_load(root, ext='.angle'):
"""
Load information from the :ref:`Output_angle` file previously created by :func:`.angle_save`.
Args:
root (str): root name for the file to be loaded
ext (str, optional): default ".angle" - extension for the file to be loaded: name = root + ext
Ret... | f1218dc2dc1a6c5ef1c56689111086137b04a786 | 3,638,602 |
import pickle
def load_newsdata_and_labels():
"""
Read newsdata, return list of documents, each line in list is one document as string.
And list of labels, each line in list is one-hot-encoded class
"""
# read newsdata which is pickled
def read_pickle_one_by_one(pickle_file):
with ope... | 3838cbd42e5bab898fc969ebe9b4f326c736c773 | 3,638,605 |
def CollectUniqueByOrderOfAppearance(dataset:list):
"""
This method collect all unique in order of appearance and return it as list.
:param dataset:list: dataset list
"""
try:
seen = set()
seen_add = seen.add
return [x for x in dataset if not (x in seen or seen_add(x))]
... | e252d064bf0c525ec1c1781ca6dc915dbc9d46f0 | 3,638,606 |
async def list_slot_set_actions(current_user: User = Depends(Authentication.get_current_user_and_bot)):
"""
Returns list of slot set actions for bot.
"""
actions = mongo_processor.list_slot_set_actions(current_user.get_bot())
return Response(data=actions) | f52f1e996b2be38a0e175ca6bfcbfd694dc79240 | 3,638,607 |
from PyQt5 import QtGui, QtWidgets, QtCore
def openfile_dialog(file_types="All files (*)", multiple_files=False,
file_path='.', caption="Select a file..."):
"""
Opens a File dialog which is used in open_file() function
This function uses pyQt5.
Parameters
----------
file_t... | b96112c5af25350b49bc086820bcea32c228d3c8 | 3,638,608 |
def getBlocks(bal: "BKAlignedLayout"):
"""
Finds all blocks of a given layout.
:param bal The layout of which the blocks shall be found
:return: The blocks of the given layout
"""
blocks = defaultdict(list)
for layer in bal.layeredGraph.layers:
for node in layer:
root =... | 6f40dc209b72747f6960d474d54e1ffedd2fa9a1 | 3,638,609 |
def read_mcmc(path_to_file):
"""
Reads mcmc chain from file
Parameters
----------
path_to_file: string
Path to mcmc chain file
Returns
---------
emcee_table: pandas dataframe
Dataframe of mcmc chain values with NANs removed
"""
colnames = ['mhalo_c','mstellar_c'... | f8d0cdd5ea5a7274e81992722db4df29d7664e43 | 3,638,610 |
def rotzV(x, theta):
"""Roate a coordinate in the local z frame"""
M = [[np.cos(theta), -np.sin(theta), 0], \
[np.sin(theta), np.cos(theta), 0], [0, 0, 1]]
return np.dot(M, x) | 43e4f7a8f93fb2b237da1f6ac3f699bf41e38e0a | 3,638,611 |
import fcntl
def has_flock(fd):
"""
Checks if fd has flock over it
True if it is, False otherwise
:param fd:
:return:
:rtype: bool
"""
try:
fcntl.flock(fd, fcntl.LOCK_EX | fcntl.LOCK_NB)
except BlockingIOError:
return True
else:
return False | 9ae997d06a12d73a659958bc2f0467ebdf0142b7 | 3,638,612 |
def ExtractCodeBySystem(
codable_concept,
system):
"""Extract code in codable_concept."""
for coding in codable_concept.coding:
if (coding.HasField('system') and coding.HasField('code') and
coding.system.value == system):
return coding.code.value
return None | e672cb3d2c1d8d65e49d00539cdecf6ee03d1143 | 3,638,613 |
def add_item(data, type):
""" Add an item to the data in ranked order
This function handles the process of adding an item to the list. It
first requests the item from the console. Items are nothing more than a
line of text typed in. Next, this kicks off a type of binary search to
find the proper l... | 0662fb19725e0985043d7ea75bad4c5fa55d921f | 3,638,614 |
def get_full_test_names(testargs, machine, compiler):
###############################################################################
"""
Return full test names in the form:
TESTCASE.GRID.COMPSET.MACHINE_COMPILER.TESTMODS
Testmods are optional
Testargs can be categories or test names and support th... | 05fd19a412172195c2365b0c002c442ceabf7946 | 3,638,617 |
def record_or_not(record_mode, line, start_block, end_block):
""" """
if not record_mode:
if start_block in line:
record_mode = True
elif end_block in line:
record_mode = False
return record_mode | 2b3952ab7fa3aa23ccbd712dee0aa06083b7b5f5 | 3,638,618 |
def compute_angle_stats(vec_mat, unit='deg'):
""" Get mean of angles the successif vectors used in the reconstruction.
return mean an variance of the angles.
"""
angles = []
for i in range(vec_mat.shape[1] - 1):
aux = 0
dot_prod = np.dot(vec_mat[i] / np.linalg.norm(vec_mat[i]... | d1701a3eca12e41b05a38433a7561f811aceb02c | 3,638,619 |
def id_test_data(value):
"""generate id"""
return f"action={value.action_name} return={value.return_code}" | 47649b7302ef2f3ad046fc1c7b3fc18da2687921 | 3,638,620 |
def kneeJointCenter(frame, hip_JC, delta, vsk=None):
"""Calculate the knee joint center and axis.
Takes in a dictionary of marker names to x, y, z positions, the hip axis
and pelvis axis. Calculates the knee joint axis and returns the knee origin
and axis.
Markers used: RTHI, LTHI, RKNE, LKNE, hip... | 1f4ab38ef90c79c964587551e05ce32ccf482e53 | 3,638,621 |
def uniform(low: float = 0.0,
high: float = 1.0,
size: tp.Optional[SIZE_TYPE] = None):
"""
Draw samples from a uniform distribution.
"""
if high < low:
raise ValueError("high must not be less than low")
u = _draw_and_reshape(size, rand)
return u * (high - low) +... | da79a086a9c129a88e45c11407ca0d3993104f1a | 3,638,622 |
import math
def toInt():
"""This built-in function casts the current value to Int and returns the result.
"""
def transform_function(current_value: object, record: dict, complete_transform_schema: dict,
custom_variables: dict):
value_to_return = None
if current... | 0f58cb6c85ca4015696c7fef2d9378c0466c2422 | 3,638,623 |
import json
def public_upload(request):
"""Public form to upload missing images
:param request: current user request
:type request: django.http.request
:return: rendered response
:rtype: HttpResponse
"""
upload_success = False
if request.method == "POST":
document = Document.o... | 857b558566a52dc2b192efc3b1441a0da11a649c | 3,638,624 |
import pathlib
import re
def load_classes(fstem):
"""Load all classes from a python file."""
all_classes = []
header = []
forward_refs = []
class_text = None
done_header = False
fname = pathlib.Path('trestle/oscal/tmp') / (fstem + '.py')
with open(fname, 'r', encoding='utf8') as inf... | da4baaed8d849b90c51200b778bdde9a47d58cc4 | 3,638,625 |
def build_optimizer(name, lr=0.001, **kwargs):
"""Get an optimizer for TensorFlow high-level API Estimator.
Args:
name (str): Optimizer name. Note, to use 'Momentum', should specify
lr (float): Learning rate.
kwargs (dictionary): Optimizer arguments.
Returns:
tf.train.Optim... | c04c9348f26fdf25951f362a693cb70765133756 | 3,638,627 |
import yaml
def generate_pruning_config(model_name,
sparsity,
begin_step=0,
end_step=-1,
schedule='ConstantSparsity',
granularity='BlockSparsity',
res... | 42f566ce574b53d6effafcec18984c201fba7f92 | 3,638,628 |
def collect_FR_dev(stim_array,stim_dt,sim_dt,spikemon,n,return_spikes=False):
"""
get all firing rates for a given spikemon
stim_array: array of stimulation time/strengths, e.g., [0,0,0,0,1,0,0,0,1,0,0]
stim_dt: time interval of stimulation
sim_dt: time interval of simulation
spikemon_t: ti... | 05914a68085112e0b1b4353dbd6434fb3e59c7c8 | 3,638,629 |
import json
def assertDict(s):
""" Assert that the input is a dictionary. """
if isinstance(s,str):
try:
s = json.loads(s)
except:
raise AssertionError('String "{}" cannot be json-decoded.'.format(s))
if not isinstance(s,dict): raise AssertionError('Variable "{}" is not a dictionary.'.forma... | 302defb4e1eecc9a6171cda0401947e3251be585 | 3,638,630 |
import math
def _consolidate_subdivide_geometry(geometry, max_query_area_size):
"""
Consolidate and subdivide some geometry.
Consolidate a geometry into a convex hull, then subdivide it into smaller
sub-polygons if its area exceeds max size (in geometry's units).
Parameters
----------
ge... | 32fbafcf3066cc73c022fc1482030d35387107c2 | 3,638,631 |
import ast
from typing import Tuple
from typing import List
from typing import Any
def get_function_args(node: ast.FunctionDef) -> Tuple[List[Any], List[Any]]:
"""
This functon will process function definition and will extract all
arguments used by a given function and return all optional and non-optional... | a4fe9dccedd5684050a7d5e7949e384dd4021035 | 3,638,633 |
def svn_client_copy3(*args):
"""
svn_client_copy3(svn_commit_info_t commit_info_p, char src_path, svn_opt_revision_t src_revision,
char dst_path,
svn_client_ctx_t ctx, apr_pool_t pool) -> svn_error_t
"""
return apply(_client.svn_client_copy3, args) | 336aaec7d6c2a44f22d6b1164316f16b4fd5f53f | 3,638,634 |
import json
import copy
def delete(server = None, keys = None):
"""
Marks an entity or entities as deleted on the server. Until an entity
is permanently deleted (an administrative operation, not available
through the RESTful API), it can still be accessed, but will not turn
up in search results.
... | b3662ba85b1aacfca6034da5d5e198a5ffada2fa | 3,638,635 |
import collections
import csv
def ParseMemCsv(f):
"""Compute summary stats for memory.
vm5_peak_kib -> max(vm_peak_kib) # over 5 second intervals. Since it uses
the kernel, it's accurate except for takes that spike in their last 4
seconds.
vm5_mean_kib -> mean(vm_size_kib) # over 5 second intervals
"... | 5d10a0d0ac5ab3d3e99ff5fd4c9ca6cd0b74656b | 3,638,636 |
def index_containing_substring(list_str, substring):
"""For a given list of strings finds the index of the element that contains the
substring.
Parameters
----------
list_str: list of strings
substring: substring
Returns
-------
index: containing the substring or -1
"""
... | 2816899bc56f6b2c305192b23685d3e803b420df | 3,638,637 |
import pycountry
import gettext
import six
def _localized_country_list_inner(locale):
"""
Inner function supporting :func:`localized_country_list`.
"""
if locale == 'en':
countries = [(country.name, country.alpha_2) for country in pycountry.countries]
else:
pycountry_locale = gette... | c67b107d10b8bc2426de39f11c30e886b5fc2894 | 3,638,638 |
def ingest_questions(questions: dict, assignment: Assignment):
"""
questions: [
{
sequence: int
questions: [
{
q: str // what is 2*2
a: str // 4
},
]
},
...
]
response = {
rejected: [ ... ]
ignored: [ ... ... | d72370bcaa5cf1f5017eda827cca6dd011ac36d0 | 3,638,639 |
from datetime import datetime
def render_book_template(book_id):
"""
Find a specific book in the database.
Locate the associated reviews (sorted by score and date).
Create the purchase url.
Check whether the user has saved the book to their wishlist.
"""
# Find the book document in the dat... | d30b30b79b102b1c08404bc00c69b1f22ccebc6a | 3,638,640 |
def iatan2(y,x):
"""One coordinate must be zero"""
if x == 0:
return 90 if y > 0 else -90
else:
return 0 if x > 0 else 180 | a0b18b61d7ffadf864a94299bc4a3a0aacd7c65a | 3,638,641 |
import torch
def fuse_bn_sequential(model):
"""
This function takes a sequential block and fuses the batch normalization with convolution
:param model: nn.Sequential. Source resnet model
:return: nn.Sequential. Converted block
"""
if not isinstance(model, torch.nn.Sequential):
return m... | 6d31cd2cd73e8dc91098b7f9cc7f70ce3b81a3b9 | 3,638,642 |
def get_baseconf_settings( baseconf_settings_filename = None ):
"""
Returns the basic configuration settings as a parameter structure.
:param baseconf_settings_filename: loads the settings from the specified filename, otherwise from the default filename or in the absence of such a file creates default sett... | 0b0b829f4923072431b8e73c7fd70e732f17dc30 | 3,638,643 |
def subtract_background(image, background_image):
"""Subtracts background image from a specified image.
Returns
-------
bs_image : np.ndarray of type np.int | shape = [image.shape]
Background-subtracted image.
"""
image = image.copy().astype(np.int)
background = background_image.cop... | c136f78c1f355c2031ef60ca17fb0bd6fc63c94e | 3,638,645 |
import math
def batch_genomes(genomes, num_batches, order):
"""
Populates 2D numpy array with len(rows)==num_batches in {order} major order.
Using col is for when you know you are using X number of nodes, and want-
to evenly distribute genomes across each node
Use row when you want to fill each no... | 00fea150ea20ae886fd72f099a1c0bd4216ba987 | 3,638,646 |
def single_gate_params(gate, params=None):
"""Apply a single qubit gate to the qubit.
Args:
gate(str): the single qubit gate name
params(list): the operation parameters op['params']
Returns:
a tuple of U gate parameters (theta, phi, lam)
"""
if gate == 'U' or gate == 'u3':
... | 153459403639103cdfa9502a26797e9c536ba112 | 3,638,647 |
import time
def runTests(data, targets, pipeline, parameters):
""" Perform grid search with specified pipeline and parameters
on data training set with targets as labels
Evaluate performance based on precision and print parameters
for best estimator
grid search o... | 122d1330444dd72aa064cd263cb7f405bf2bf9ba | 3,638,650 |
def isMultipleTagsInput(item):
"""
Returns True if the argument datatype is not a column or a table, and if it allows lists and if it has no permitted value.
This function is used to check whether the argument values have to be delimited by the null character (returns True) or not.
:param item: Tab... | f7710902e27962fc8df55bc75be2d5d404144aeb | 3,638,651 |
def remove_url(url: str = Form(...)):
"""
Remove url from the url json file
:param url: api url in the format: http://ip:port/
:return: ApiResponse
"""
try:
payload = helpers.parse_json(url_config_path)
except Exception as e:
return ApiResponse(success=False, ... | c7c218926c2992df19b3988987fca8cf2bbff3d1 | 3,638,653 |
def load_CSVdata(messages_filepath, categories_filepath):
"""
Load and merge datasets messages and categories
Inputs:
Path to the CSV file containing messages
Path to the CSV file containing categories
Output:
dataframe with merged data containing messages and categories
... | e216c09ca403545fbc1152a25e966efeb4baeefc | 3,638,654 |
def accept_invite(payload, user):
"""
Accepts an invite
args: payload, user
ret: response
"""
try:
invite = Invites.get(payload['invite'])[0]
except:
return Message(
Codes.NOT_FOUND,
{ 'message': 'There isn\'t any active invite with the given id.' }
... | bff423eeec7f7f527771934de0f32ede0f528948 | 3,638,655 |
from typing import Tuple
from typing import Dict
from typing import List
import re
def clean_status_output(
input: str,
) -> Tuple[bool, Dict[str, str], List[Dict[str, str]]]:
# example input
"""
# Health check:
# - dns: rename /etc/resolv.conf /etc/resolv.pre-tailscale-backup.conf: device or ... | bbf100514373595948b0691dff857deb5772f019 | 3,638,656 |
def test_tensor_method_mul():
"""test_tensor_method_mul"""
class Net(Cell):
def __init__(self):
super(Net, self).__init__()
self.sub = P.Sub()
def construct(self, x, y):
out = x * (-y)
return out.transpose()
net = Net()
x = ms.Tensor(np... | 89866ebd9311e0bac0e3324b01545507b986751f | 3,638,657 |
def _get_top_artists(session: Session, limit=100):
"""Gets the top artists by follows of all of Audius"""
top_artists = (
session.query(User)
.select_from(AggregateUser)
.join(User, User.user_id == AggregateUser.user_id)
.filter(AggregateUser.track_count > 0, User.is_current)
... | ae6a45e7190995fc35daf62236e73c4bd5c6235f | 3,638,658 |
def _get_other_locations():
"""Returns all locations except convention venues."""
if 'all' not in location_cache.keys():
conv_venue = LocationType.objects.get(name='Convention venue')
location_cache['all'] = Location.objects.exclude(loc_type=conv_venue)
return location_cache['all'] | a34bf432529a31bc013988c394230e55b01ac21b | 3,638,660 |
import torch
def _check_cuda_version():
"""
Make sure that CUDA versions match between the pytorch install and torchvision install
"""
if not _HAS_OPS:
return -1
_version = torch.ops.torchvision._cuda_version()
if _version != -1 and torch.version.cuda is not None:
tv_version = ... | d86e209d10514060f0c15bff9ea28df6b2054480 | 3,638,661 |
def largest(layer,field):
"""largest(layer,field)
Returns the largest area significant class in the study area.
"""
theitems = []
rows = arcpy.SearchCursor(layer)
for row in rows:
theitems.append(row.getValue(field))
del rows
theitems.sort()
max1= theitems[-1]
return ma... | ff6433a5fef48550e902317384dec746136063dc | 3,638,662 |
import asyncio
import random
async def double_up(ctx):
"""
「ダブルアップチャンス！」を開始します。
"""
depth = 1 # 現在の階層
HOLE = "\N{HOLE}\N{VARIATION SELECTOR-16}"
LEFT_ARROW = "\N{LEFTWARDS BLACK ARROW}\N{VARIATION SELECTOR-16}"
RIGHT_ARROW = "\N{BLACK RIGHTWARDS ARROW}\N{VARIATION SELECTOR-16}"
TOP_AR... | 3ec1394d681fcb0e626e98b11bd815dddbe64254 | 3,638,663 |
def read_version(file_contents):
"""Read the project setting from pyproject.toml."""
data = tomlkit.loads(file_contents)
details = data["tool"]["poetry"]
return details["version"] | 7255c199463437765d21658f792a54049bbb45ee | 3,638,664 |
from datetime import datetime
def schedule_time(check_start_time, check_end_time, time_duaration=7) -> dict:
""" Returns dictionary of earliest available time within the next week """
all_busy_events = get_busy_events()
for d in range(1,time_duaration):
# Increment by one day throughout the week
... | 858387e8d07634df7a143b3ee500e648ed54abd6 | 3,638,665 |
import array
def _to_array(value):
"""When `value` is a plain Python sequence, return it as a NumPy array."""
if not hasattr(value, 'shape') and hasattr(value, '__len__'):
return array(value)
else:
return value | 3bf185f34c51dc2042bdb05138b0febd9e89b421 | 3,638,666 |
def dict_pix_to_deg(input_dict, changeN):
"""Convert pix to deg for a given dictionary format,
changeN is 1 or 2, to let the function works for the first
or both elements of the tuple"""
dict_deg = {}
for key, values in input_dict.items():
new_display = []
for display in values:
... | 03c49e113c8805c4d675899f3c61e3ae00bd7681 | 3,638,667 |
def remove_container_name_from_blob_path(blob_path, container_name):
"""
Get the bit of the filepath after the container name.
"""
# container name will often be part of filepath - we want
# the blob name to be the bit after that
if not container_name in blob_path:
return blob_path
b... | e02807abebdf3a193efcabee1dda3f733a780dd5 | 3,638,668 |
from typing import Dict
from typing import List
def _complex_ar_from_dict(dic: Dict[str, List]) -> np.ndarray:
"""Construct complex array from dictionary of real and imaginary parts"""
out = np.array(dic["real"], dtype=complex)
out.imag = np.array(dic["imag"], dtype=float)
return out | a3938619f84c2dcbec5c9ac90c0064ea380346c4 | 3,638,669 |
def endpoint(url_pattern, method="GET"):
"""
:param url_pattern:
:param method:
:param item:
:return:
"""
def wrapped_func(f):
@wraps(f)
def inner_func(self, *args, **kwargs):
"""
:param self:
:param args:
:param kwargs:
... | 23b68a1440e96eac27926f2a37d96cb74a568734 | 3,638,670 |
def elastic_transform(
image,
alpha,
sigma,
alpha_affine,
interpolation=cv2.INTER_LINEAR,
border_mode=cv2.BORDER_REFLECT_101,
random_state=None,
approximate=False,
):
"""Elastic deformation of images as described in [Simard2003]_ (with modifications).
Based on https://gist.github... | e60754cc898d83051164180b1d07ac0e4c688946 | 3,638,671 |
import re
from orangecontrib.xoppy.util.xoppy_xraylib_util import f0_xop
def crystal_atnum(list_AtomicName, unique_AtomicName, unique_Zatom,list_fraction, f0coeffs):
"""
To get the atom and fractional factor in diffierent sites
list_AtomicName: list of all atoms in the crystal
unique_AtomicName: lis... | f9805890971e1c2e6696084fad5f8b9071999046 | 3,638,672 |
def integrate(name, var):
""" given filename and var, generate profile """
d = vtk.vtkExodusIIReader()
d.SetFileName(name)
d.UpdateInformation()
d.SetPointResultArrayStatus(var,1)
d.Update()
blocks = d.GetOutput().GetNumberOfBlocks()
data = d.GetOutput()
# range... | 116993d18c4430f6ce0e7dacba8b73ef3a03f689 | 3,638,673 |
def mediate(timer: TimerBase, decimals: int | None) -> int:
"""If the start function doesn't have decimals defined, then use the decimals value defined when the Timer() was initiated."""
return timer.decimals if decimals is None else validate_and_normalise(decimals) | 030ec62071bc4c2bc41ae30c5eb8212b36e0359a | 3,638,674 |
def calculate_n_inputs(inputs, config_dict):
"""
Calculate the number of inputs for a particular model.
"""
input_size = 0
for input_name in inputs:
if input_name == 'action':
input_size += config_dict['prior_args']['n_variables']
elif input_name == 'state':
i... | 78d750ff4744d872d696dcb454933c868b0ba41e | 3,638,675 |
def coords(lat: float, lon: float, alt: float = None ) -> str:
"""Turn longitude, latitude into a printable string."""
txt = "%2.4f%s" % (abs(lat), "N" if lat>0 else "S")
txt += " %2.4f%s" % (abs(lon), "E" if lon>0 else "W")
if alt:
txt += " %2.0fm" % alt
return txt | c5768e03c55d5f567695056d78108812014b9ef4 | 3,638,678 |
def chromosome_to_smiles():
"""Wrapper function for simplicity."""
def sc2smi(chromosome):
"""Generate a SMILES string from a list of SMILES characters. To be customized."""
silyl = "([Si]([C])([C])([C]))"
core = chromosome[0]
phosphine_1 = (
"(P(" + chromosome[1] + ... | 793995484c46295977f1d312c4fa11f69bca6c84 | 3,638,679 |
def softmax_edges(graph, feat):
"""Apply batch-wise graph-level softmax over all the values of edge field
:attr:`feat` in :attr:`graph`.
Parameters
----------
graph : DGLGraph
The graph.
feat : str
The feature field.
Returns
-------
tensor
The tensor obtaine... | f5dafccca3c487756deeb37f534ef178cf1de75f | 3,638,680 |
def command_result_processor_parameter_required(command_line_parameter):
"""
Command result message processor if a parameter stays unsatisfied.
Parameters
----------
command_line_parameter : ``CommandLineParameter``
Respective command parameter.
Returns
-------
message ... | fed1b7af60018cb5638e021365ae754477b7a241 | 3,638,681 |
def randdirichlet(a):
""" Python implementation of randdirichlet.m using randomgamma fucnction
:param a: vector of weights (shape parameters to the gamma distribution)
"""
try:
x = rand.randomgamma(a)
except ValueError:
a[a == 0] += 1e-16
x = rand.randomgamma(a)
x /= x... | c825fb81c07337231f49437a2bea7ddd5a40234f | 3,638,682 |
def home(request):
"""
This is the home page request
"""
return render(request, 'generator/home.html') | ad8b69871d484c16583752d029fec2970084e698 | 3,638,683 |
def print_insn_mnem(ea):
"""
Get instruction mnemonics
@param ea: linear address of instruction
@return: "" - no instruction at the specified location
@note: this function may not return exactly the same mnemonics
as you see on the screen.
"""
res = ida_ua.ua_mnem(ea)
if not res:... | 4c60e853356217c2fbfdd21047429c729b57f10f | 3,638,684 |
def setdim(P, dim=None):
"""
Adjust the dimensions of a polynomial.
Output the results into Poly object
Args:
P (Poly) : Input polynomial
dim (int) : The dimensions of the output polynomial. If omitted,
increase polynomial with one dimension. If the new dim is
... | 610138c1d1a13112d35583d758cac43c1e296d18 | 3,638,685 |
def extract_file_from_zip(zipfile, filename):
"""
Returns the compressed file `filename` from `zipfile`.
"""
raise NotImplementedError()
return None | dc7b1e5a196a019d1fd2274155e0404b03b09702 | 3,638,686 |
import torch
def multi_classes_nms(cls_scores, box_preds, nms_config, score_thresh=None):
"""
Args:
cls_scores: (N, num_class)
box_preds: (N, 7 + C)
nms_config:
score_thresh:
Returns:
"""
pred_scores, pred_labels, pred_boxes = [], [], []
for k in range(cls_sco... | a0451c3769b4415e7e7d184d43f6b8f121b651b1 | 3,638,688 |
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