content stringlengths 35 762k | sha1 stringlengths 40 40 | id int64 0 3.66M |
|---|---|---|
import os
def get_exploration_components_from_dir(dir_path):
"""Gets the (yaml, assets) from the contents of an exploration data dir.
Args:
dir_path: str. a full path to the exploration root directory.
Returns:
*. A 2-tuple, the first element of which is a yaml string, and the
se... | 945690e496846e9cf6c0443ff8cc57ff18d5d056 | 11,700 |
import time
def time_this_function(func):
"""
Time the function.
use as a decorator.
Examples
---------
::
@time_this_function
def func(x):
return x
a= func(1)
Parameters
----------
func: Callable
function
Returns
-------
... | 6ee2d12dc2301e1c3efe2ca02548297aa83d316f | 11,701 |
def power_plot(data, sfreq, toffset, log_scale, zscale, title):
"""Plot the computed power of the iq data."""
print("power")
t_axis = np.arange(0, len(data)) / sfreq + toffset
if log_scale:
lrxpwr = 10 * np.log10(data + 1e-12)
else:
lrxpwr = data
zscale_low, zscale_high = zsca... | 06d7fab09c027ec2dbf7a11fa78f3b6fcd97e2d7 | 11,702 |
import torchvision
import torch
def load_dataset(dataset):
"""
Loads a dataset and returns train, val and test partitions.
"""
dataset_to_class = {
'mnist': torchvision.datasets.MNIST,
'cifar10': torchvision.datasets.CIFAR10,
'fa-mnist': torchvision.datasets.FashionMNIST
}
assert dataset in dataset_to_cla... | e17dcec84603a742cb6eec0fa18ad40af2454461 | 11,703 |
def compareTo(s1, s2):
"""Compares two strings to check if they are the same length and whether one is longer
than the other"""
move_slice1 = 0
move_slice2 = 1
if s1[move_slice1:move_slice2] == '' and s2[move_slice1:move_slice2] == '':
return 0 # return 0 if same length
elif s1[move_... | 4700360d10561227a6d4995c66953993dce1cea3 | 11,704 |
def is_unique(x):
# A set cannot contain any duplicate, so we just check that the length of the list is the same as the length of the corresponding set
"""Check that the given list x has no duplicate
Returns:
boolean: tells if there are only unique values or not
Args:
x (list): elemen... | 12b4513a71fc1b423366de3f48dd9e21db79e73a | 11,705 |
def str2format(fmt, ignore_types=None):
"""Convert a string to a list of formats."""
ignore_types = ignore_types if ignore_types else ()
token_to_format = {
"s": "",
"S": "",
"d": "g",
"f": "f",
"e": "e",
}
base_fmt = "{{:{}}}"
out = []
for i, token ... | 9cbe719abe6b37a0adcd52af250dfe768f850ffa | 11,706 |
from pathlib import Path
def _read_concordance(filename: Path, Sample_IDs: pd.Index) -> pd.DataFrame:
"""Create a flag of known replicates that show low concordance.
Given a set of samples that are known to be from the same Subject. Flag
samples that show low concordance with one or more replicates.
... | 2c7049ff5b521927ffbf863471fc23e073bce531 | 11,707 |
def load_image(name):
""" Get and cache an enaml Image for the given icon name.
"""
path = icon_path(name)
global _IMAGE_CACHE
if path not in _IMAGE_CACHE:
with open(path, 'rb') as f:
data = f.read()
_IMAGE_CACHE[path] = Image(data=data)
return _IMAGE_CACHE[path] | 6ce56c1a9d4d9e80d25a19aca239f43ebd119840 | 11,708 |
def add_shipment_comment(
tracking_id: str,
body: CreateComment = Body(...),
client: VBR_Api = Depends(vbr_admin_client),
):
"""Add a Comment to a Shipment.
Requires: **VBR_WRITE_PUBLIC**"""
tracking_id = sanitize_identifier_string(tracking_id)
shipment = client.get_shipment_by_tracking_id(... | d115d230bbf47a8f1cf625f0ab66e855f382244c | 11,709 |
import os
def train_faster_rcnn_alternating(base_model_file_name, debug_output=False):
"""
4-Step Alternating Training scheme from the Faster R-CNN paper:
# Create initial network, only rpn, without detection network
# --> train only the rpn (and conv3_1 and up for VGG16)
# buffer region prop... | cb0b255198f60da9415282f047396c8b501a43aa | 11,710 |
def _mp2_energy(output_str):
""" Reads the MP2 energy from the output file string.
Returns the energy in Hartrees.
:param output_str: string of the program's output file
:type output_str: str
:rtype: float
"""
ene = ar.energy.read(
output_str,
app.one_of_the... | febd9f4c5759cb6150ff16bda2e9050199c48c5f | 11,711 |
def fastlcs(a,b,Dmax=None):
"""
return the length of the longest common substring or 0 if the maximum number of difference Dmax cannot be respected
Implementation: see the excellent paper "An O(ND) Difference Algorithm and Its Variations" by EUGENE W. MYERS, 1986
NOTE:
let D be the minim... | d8a88c7ffaae892e48a292b7a045da9f5dc58173 | 11,712 |
from typing import Optional
from typing import Mapping
def FeaturesExtractor( # pylint: disable=invalid-name
eval_config: config_pb2.EvalConfig,
tensor_representations: Optional[Mapping[
Text, schema_pb2.TensorRepresentation]] = None) -> extractor.Extractor:
"""Creates an extractor for extracting f... | 86e58783fca3ebb23de1e6b7ac9cdd4030e99c38 | 11,713 |
def assert__(engine, obj, condition, message=u'Assertion failed'):
""":yaql:assert
Evaluates condition against object. If it evaluates to true returns the
object, otherwise throws an exception with provided message.
:signature: obj.assert(condition, message => "Assertion failed")
:arg obj: object ... | c29e073bf6673ce0c89ed339c27f2287d6952991 | 11,714 |
def create_review(request, item_id,
template_name="reviewclone/create_review.html"):
"""
Current user can create a new review.
Find the item with `item_id` then make sure the current user
does not already have a review. If a review is found
`review_exist` will be True. If the cur... | fe1806017cbce5e95be183be48c9e35a63a10e26 | 11,715 |
from typing import Iterable
from typing import List
def build_level_codes(incoming_column_name: str, levels: Iterable) -> List[str]:
"""
Pick level names for a set of levels.
:param incoming_column_name:
:param levels:
:return:
"""
levels = [str(lev) for lev in levels]
levels = [incom... | 994ccc0673bd27dcce30709a97372c29d75a8e67 | 11,716 |
def get_all(isamAppliance, check_mode=False, force=False):
"""
Get all rsyslog objects
"""
return isamAppliance.invoke_get("Get all rsyslog objects",
"/core/rsp_rsyslog_objs") | 55ff144577a9ef25b555ca3a37db65bfdb0f0af4 | 11,717 |
def genomic_dup1_37_loc():
"""Create test fixture GRCh37 duplication subject"""
return {
"_id": "ga4gh:VSL.CXcLL6RUPkro3dLXN0miGEzlzPYiqw2q",
"sequence_id": "ga4gh:SQ.VNBualIltAyi2AI_uXcKU7M9XUOuA7MS",
"interval": {
"type": "SequenceInterval",
"start": {"value": 4... | 470af80795c649bc0f4dd29393d1093c45c9f0da | 11,718 |
def parse(f, _bytes):
"""
Parse function will take a parser combinator and parse some set of bytes
"""
if type(_bytes) == Parser:
return f(_bytes)
else:
s = Parser(_bytes, 0)
return f(s) | 7f824c46477a384ce97f66806813f4b42412d6d8 | 11,719 |
def spiral_tm(wg_width=0.5, length=2):
""" sample of component cutback """
c = spiral_inner_io_euler(wg_width=wg_width, length=length, dx=10, dy=10, N=5)
cc = add_gratings_and_loop_back(
component=c,
grating_coupler=pp.c.grating_coupler_elliptical_tm,
bend_factory=pp.c.bend_circular,... | e7fcec9e61984d8f89558d7479cc942db389ba3a | 11,720 |
import time
import sys
def get_url_until_success(url):
"""Continuously tries to open a url until it succeeds or times out."""
time_spent = 0
while (time_spent < RECEIVE_TIMEOUT):
try:
helps = urllib2.urlopen(url)
break
except:
time.sleep(RETRY_INTERVAL)
time_spent += RETRY_INTERV... | 04c47d158393c1f8b809240b84d2aecc6fcbf8de | 11,721 |
from typing import List
from typing import Tuple
def _chunk(fst: pynini.Fst) -> List[Tuple[str, str]]:
"""Chunks a string transducer into tuples.
This function is given a string transducer of the form:
il1 il2 il3 il4 il5 il6
ol1 eps eps ol2 eps ol3
And returns the list:
[(il1 ... | fa50e13062267e8929df5f538ab9a924822bc265 | 11,722 |
def auth_token_required(func):
"""Your auth here"""
return func | e65b94d40c914c57ff8d894409b664cf97aa790d | 11,723 |
def base_convert_money(amount, currency_from, currency_to):
"""
Convert 'amount' from 'currency_from' to 'currency_to'
"""
source = get_rate_source()
# Get rate for currency_from.
if source.base_currency != currency_from:
rate_from = get_rate(currency_from)
else:
# If curren... | 5417ba7a9d757bafc835df8f55a1d4e6de72cb2f | 11,724 |
import confluent_kafka as ck
from elasticsearch import Elasticsearch
import sys
def init_dask_workers(worker, config, obj_dict=None):
"""
Initalize for all dask workers
:param worker: Dask worker
:type worker: object
:param config: Configuration which contains source and sink details
:type con... | 34fb468e5a5f2acf3ea4c18065c7c0efde750a04 | 11,725 |
async def contestant() -> dict:
"""Create a mock contestant object."""
return {
"id": "290e70d5-0933-4af0-bb53-1d705ba7eb95",
"first_name": "Cont E.",
"last_name": "Stant",
"birth_date": date(1970, 1, 1).isoformat(),
"gender": "M",
"ageclass": "G 12 år",
"... | 261fd560107489b58c645efb1bb9c19a396e0dce | 11,726 |
import requests
import http
def GetApitoolsTransport(timeout='unset',
enable_resource_quota=True,
response_encoding=None,
ca_certs=None,
allow_account_impersonation=True,
use_google_auth=None,
... | 21fc8d521703580a51c753811b7f0d401f68bba5 | 11,727 |
def user_requested_anomaly7():
""" Checks if the user requested an anomaly, and returns True/False accordingly. """
digit = 0
res = False
if is_nonzero_file7(summon_filename):
lines = []
with open(get_full_path(summon_filename)) as f:
lines = f.readlines()
if len(line... | bed54831c00deb6c11ce81c731fe37f35ef070b7 | 11,728 |
def mat_to_r(_line, _mat_object : MatlabObject, _r_object : RObject = RObject()):
"""Move variables from Matlab to R
Parameters
----------
_line : str, Iterable[str]
If str, one of the following:
1. '#! m[at[lab]] -> <vars>'
2. '<vars>'
where <vars> is a comma separated list of Matlab variable names
I... | 22f78c06bcf47a71596563debf6115c954d89e21 | 11,729 |
import os
def read_keys():
""" read aws credentials from file, then stick into global variables... """
with open('%s/.aws/credentials' % os.getenv('HOME'), 'rt') as infile:
for line in infile:
if 'aws_access_key_id' in line:
aws_access_key_id = line.split('=')[-1].strip()
... | c79752cb52045c3d369516dc16343ec766aa9e09 | 11,730 |
def RecalculatedEdgeDegreeAttack(G, remove_fraction = 1.0):
""" Recalculated Edge Degree Attack
"""
n = G.number_of_nodes()
m = int(G.number_of_edges() * (remove_fraction+0.0) )
tot_ND = [0] * (m + 1)
tot_T = [0] * (m + 1)
ND, ND_lambda = ECT.get_number_of_driver_nodes(G)
tot_ND[0] = ND... | ff88430f172a1ca319af9d637c292091cab2bf6f | 11,731 |
def get(url, params=None, headers=None):
"""Return the contents from a URL
Params:
- url (str): Target website URL
- params (dict, optional): Param payload to add to the GET request
- headers (dict, optional): Headers to add to the GET request
Example:
```
get('https://httpbin.org/an... | edb0fe25728fe1bd11d9e74509a630f2d3823af1 | 11,732 |
def get_param_num(model):
""" get the number of parameters
Args:
model:
Returns:
"""
return sum(p.numel() for p in model.parameters()) | 19d98a1bcbdcb827be4a657f82cda2ff09f119e4 | 11,733 |
import os
def get_branch_name():
"""Get the name of the current branch
returns:
The name of the current branch
"""
HEAD = data.get_ref('HEAD', deref=False)
if not HEAD.symbolic:
return None
HEAD = HEAD.value
assert HEAD.startswith('refs/heads/')
return os.path.relpath(H... | 631b08be509503f50826b5e5f7c1ceca95b8f4af | 11,734 |
from typing import Union
def format_tensor_to_ndarray(x: Union[ms.Tensor, np.ndarray]) -> np.ndarray:
"""Unify `mindspore.Tensor` and `np.ndarray` to `np.ndarray`. """
if isinstance(x, ms.Tensor):
x = x.asnumpy()
if not isinstance(x, np.ndarray):
raise TypeError('input should be one of [m... | 6e64a40bbafe2b2f89f5afd200077be369adcfe7 | 11,735 |
from typing import Pattern
import re
def hunt_csv(regex: Pattern, body: str) -> list:
"""
finds chunk of csv in a larger string defined as regex, splits it,
and returns as list. really useful only for single lines.
worse than StringIO -> numpy or pandas csv reader in other cases.
"""
csv_strin... | 9c5574f059ef05e6f99e468a9272f42393d79030 | 11,736 |
import re
def time_key(file_name):
""" provides a time-based sorting key """
splits = file_name.split('/')
[date] = re.findall(r'(\d{4}_\d{2}_\d{2})', splits[-2])
date_id = [int(token) for token in date.split('_')]
recording_id = natural_key(splits[-1])
session_id = session_key(splits[-2])
... | 07a5448b7b39b00780f53080b316981198d54c91 | 11,737 |
import subprocess
def silent_popen(args, **kwargs):
"""Wrapper for subprocess.Popen with suppressed output.
STERR is redirected to STDOUT which is piped back to the
calling process and returned as the result.
"""
return subprocess.Popen(args,
stderr=subprocess.STDOUT,
... | 5075a3ea1891ad3c237d5b05b474f563005ff48f | 11,738 |
def sizeRange(contourList, low, high):
"""Only keeps contours that are in range for size"""
newList = []
for i in contourList:
if (low <= cv2.contourArea(i) <= high):
newList.append(i)
return newList | ac83b09acfd8d8e23a03965b52c5c4cc0361710d | 11,739 |
def number_field_choices(field):
"""
Given a field, returns the number of choices.
"""
try:
return len(field.get_flat_choices())
except AttributeError:
return 0 | b8776e813e9eb7471a480df9d6e49bfeb48a0eb6 | 11,740 |
def _is_an_unambiguous_user_argument(argument: str) -> bool:
"""Check if the provided argument is a user mention, user id, or username (name#discrim)."""
has_id_or_mention = bool(commands.IDConverter()._get_id_match(argument) or RE_USER_MENTION.match(argument))
# Check to see if the author passed a usernam... | adecc093a0597d43292171f867ebcf5a64edc7d8 | 11,741 |
def resize_image(image, size):
"""
Resize the image to fit in the specified size.
:param image: Original image.
:param size: Tuple of (width, height).
:return: Resized image.
:rtype: :py:class: `~PIL.Image.Image`
"""
image.thumbnail(size)
return image | 67db04eac8a92d27ebd3ec46c4946b7662f9c03f | 11,742 |
def one_hot_vector(val, lst):
"""Converts a value to a one-hot vector based on options in lst"""
if val not in lst:
val = lst[-1]
return map(lambda x: x == val, lst) | 401ff1d6666c392b3a217659929a4f7832c52522 | 11,743 |
def follow(request, username):
""" Add user with username to current user's following list """
request.user.followers.add(User.objects.get(username=username))
return redirect('accounts:followers') | 72530b32cfcb2282045cd2ef112df62a19e03239 | 11,744 |
def sesteva_stolpce(seznam_seznamov_stolpcev):
"""sešteje vse 'stolpce' v posameznem podseznamu """
matrika_stolpcev = []
for i in range(len(seznam_seznamov_stolpcev)):
sez = seznam_seznamov_stolpcev[i]
stolpec11 = sez[0]
while len(sez) > 1:
i = 0
stolpec22 = ... | fe69368a79b60e549983a07e140ec3b5e532868e | 11,745 |
def create_response(data={}, status=200, message=''):
"""
Wraps response in a consistent format throughout the API
Format inspired by https://medium.com/@shazow/how-i-design-json-api-responses-71900f00f2db
Modifications included:
- make success a boolean since there's only 2 values
- make messag... | 51346e3a92bdf93085b12eaccc99511b66a34bcf | 11,746 |
def do_sizes_match(imgs):
"""Returns if sizes match for all images in list."""
return len([*filter(lambda x: x.size != x.size[0], imgs)]) > 0 | 7da30972ecfd4d3cac3d21ff380255865ec3b5c8 | 11,747 |
def gaussian_sampling(len_x, len_y, num_samples, spread_factor=5, origin_ball=1):
"""
Create a gaussian sampling pattern where each point is sampled from a
bivariate, concatenated normal distribution.
Args:
len_x (int): Size of output mask in x direction (width)
len_y (int): ... | fce7396b02778aa832c5d24028fb1f55f1013b15 | 11,748 |
import json
def from_cx_jsons(graph_json_str: str) -> BELGraph:
"""Read a BEL graph from a CX JSON string."""
return from_cx(json.loads(graph_json_str)) | c61e415199ce0bfc610c1a4277aa8ba1b74a070a | 11,749 |
from typing import Tuple
def _calculate_dimensions(image: Image) -> Tuple[int, int]:
"""
Returns the width and height of the given pixel data.
The height of the image is the number of rows in the list,
while the width of the image is determined by the number of
pixels on the first row. It is assu... | 7e74f181839b70e45cb64ca8b8517ef663c7caf8 | 11,750 |
def cli(ctx, invocation_id):
"""Get a summary of an invocation, stating the number of jobs which succeed, which are paused and which have errored.
Output:
The invocation summary.
For example::
{'states': {'paused': 4, 'error': 2, 'ok': 2},
'model': 'WorkflowInvocation',
... | 94197a9c55c0d37b311585fdfce9d615c6986cb5 | 11,751 |
import numpy as np
def remove_observations_mean(data,data_obs,lats,lons):
"""
Removes observations to calculate model biases
"""
### Import modules
### Remove observational data
databias = data - data_obs[np.newaxis,np.newaxis,:,:,:]
return databias | 8f0cf60137660878f57dc35caa8c23896944d6ab | 11,752 |
import logging
def joint_extraction_model_fn(features, labels, mode, params):
"""Runs the node-level sequence labeling model."""
logging.info("joint_extraction_model_fn")
inputs = features # Arg "features" is the overall inputs.
# Read vocabs and inputs.
dropout = params["dropout"]
if params["circle_fea... | 1e6eb2028c8924733329bc4fc3079ca12af12d94 | 11,753 |
def jp2yy (sent):
"""take a Japanese sentence in UTF8 convert to YY-mode using mecab"""
### (id, start, end, [link,] path+, form [surface], ipos, lrule+[, {pos p}+])
### set ipos as lemma (just for fun)
### fixme: do the full lattice
yid = 0
start = 0
cfrom = 0
cto = 0
yy = list()
... | d59a047f95761aacdd1b371bc6f03072d708e505 | 11,754 |
def make_ss_matrices(sigma_x, dt):
"""
To make Q full-rank for inversion (so the mle makes sense), use:
Q = [ dt**2 dt/2
dt/2 1 ]
to approximate Q = (dt 1)(dt 1)'
System:
x = [p_x p_y v_x v_y]
y = [p_x' p_y']
:param sigma_x:
:param dt:
:return:
sigma_0:... | 551a1d46ee67360e159ab966c0b3f30dd77254c8 | 11,755 |
def get_icp_val(tmr):
"""Read input capture value"""
return peek(tmr + ICRx) | (peek(tmr + ICRx + 1) << 8) | 0aef45e0c6edeb3c6540a51ae44013ded03c7be7 | 11,756 |
import torch
def validate(segmenter, val_loader, epoch, num_classes=-1):
"""Validate segmenter
Args:
segmenter (nn.Module) : segmentation network
val_loader (DataLoader) : training data iterator
epoch (int) : current epoch
num_classes (int) : number of classes to consider
Returns... | 716f1eda3a283c2707fa8ffd6e8073c351bda560 | 11,757 |
def detect_forward(CoreStateMachine, PostConditionStateMachine):
"""A 'forward ambiguity' denotes a case where the post condition
implementation fails. This happens if an iteration in the core pattern is a
valid path in the post- condition pattern. In this case no decision can be
made about where to res... | 4d6c1952a201f3505b0770f12f42609847728a54 | 11,758 |
def price_sensitivity(results):
"""
Calculate the price sensitivity of a strategy
results
results dataframe or any dataframe with the columns
open, high, low, close, profit
returns
the percentage of returns sensitive to open price
Note
-----
Price sensitivity is calc... | 02ab811bf689e760e011db6d091dcb7c3079f0d1 | 11,759 |
def wrap_zone(tz, key=KEY_SENTINEL, _cache={}):
"""Wrap an existing time zone object in a shim class.
This is likely to be useful if you would like to work internally with
non-``pytz`` zones, but you expose an interface to callers relying on
``pytz``'s interface. It may also be useful for passing non-`... | 7776153859b30ee758b16498b1122d0af294d371 | 11,760 |
async def async_browse_media(
hass, media_content_type, media_content_id, *, can_play_artist=True
):
"""Browse Spotify media."""
info = list(hass.data[DOMAIN].values())[0]
return await async_browse_media_internal(
hass,
info[DATA_SPOTIFY_CLIENT],
info[DATA_SPOTIFY_ME],
me... | d3f912ecbd8949a637d461a453a4b9a9ea73a20c | 11,761 |
from typing import Tuple
import json
def bounds(url: str) -> Tuple[str, str, str]:
"""Handle bounds requests."""
info = main.bounds(url)
return ("OK", "application/json", json.dumps(info)) | 2da1ec2db8b2c0c3a3d28854dc2f68b71aa96bf1 | 11,762 |
import email
def make_message_id():
"""
Generates rfc message id. The returned message id includes the angle
brackets.
"""
return email.utils.make_msgid('sndlatr') | 7030efe1d61f4e54d833bb5c808f582689c626c6 | 11,763 |
def _understand_err_col(colnames):
"""Get which column names are error columns
Examples
--------
>>> colnames = ['a', 'a_err', 'b', 'b_perr', 'b_nerr']
>>> serr, terr = _understand_err_col(colnames)
>>> np.allclose(serr, [1])
True
>>> np.allclose(terr, [2])
True
>>> serr, terr =... | 2fab9346a3ea8fa6e84e406856eef8ad14ad9f66 | 11,764 |
def unpivot(frame):
"""
Example:
>>> df
date variable value
0 2000-01-03 A 0.895557
1 2000-01-04 A 0.779718
2 2000-01-05 A 0.738892
3 2000-01-03 B -1.513487
4 2000-01-04 B -0.543134
5 2000-01-05 B 0.902733
6 20... | 6cda1c29e7e7c9b4176e83b6a0e1d907458721b2 | 11,765 |
import type
def find_viable_generators_aux (target_type, prop_set):
""" Returns generators which can be used to construct target of specified type
with specified properties. Uses the following algorithm:
- iterates over requested target_type and all it's bases (in the order returned bt
t... | 40764a16b17b54c28495e08623d616d0927451d1 | 11,766 |
def analyze(model, Y, print_to_console=True):
"""
Perform variance-based sensitivty analysis for each process.
Parameters
----------
model : object
The model defined in the sammpy
Y : numpy.array
A NumPy array containing the model outputs
print_to_console : bool
Prin... | 119c00becb1c3b507e35cbcecd98762fcb924521 | 11,767 |
import copy
def GetMorganFingerprint(mol, atomId=-1, radius=2, fpType='bv', nBits=2048, useFeatures=False,
**kwargs):
"""
Calculates the Morgan fingerprint with the environments of atomId removed.
Parameters:
mol -- the molecule of interest
radius -- the maximum radius
... | 9fd8077c4f35c83e8996a53981f99baa0e4510a6 | 11,768 |
import math
def _rgb2lab(rgb):
"""Convert an RGB integer to Lab tuple"""
def xyzHelper(value):
"""Helper function for XYZ colourspace conversion"""
c = value / 255
if c > 0.0445:
c = (c + 0.055) / 1.055
c = math.pow(c, 2.4)
else:
c /= 12.92
... | a663370e3908daa9ba795bb0dc2ecb945653221e | 11,769 |
import os
def _resolve_dir(env_name, dflt_dir):
"""Resolve a directory given the override env var and
its default directory. And if '~' is used to indicate
the home directory, then expand that."""
folder = os.environ.get(env_name, dflt_dir)
if folder is not None:
return os.path.expanduser(... | 677c9b3bab970c56f1b3ea0ac8cff75d083e5328 | 11,770 |
import torch
def biband_mask(n: int, kernel_size: int, device: torch.device, v=-1e9):
"""compute mask for local attention with kernel size.
Args:
n (torch.Tensor): the input length.
kernel_size (int): The local attention kernel size.
device (torch.device): transformer mask to the devi... | ab3a5f25f9fe0f83579d0492caa2913a13daa2d7 | 11,771 |
def containsIfElse(node):
""" Checks whether the given node contains another if-else-statement """
if node.type == "if" and hasattr(node, "elsePart"):
return True
for child in node:
if child is None:
pass
# Blocks reset this if-else problem so we ignore them
# ... | 255f58fdf4abe69f10e9b433562ade12cb0bc215 | 11,772 |
import os
def lstm_create_dataset(data_home, batch_size, repeat_num=1, training=True):
"""Data operations."""
ds.config.set_seed(1)
data_dir = os.path.join(data_home, "aclImdb_train.mindrecord0")
if not training:
data_dir = os.path.join(data_home, "aclImdb_test.mindrecord0")
data_set = ds... | c0cfe9e37edbae523e580e0e218f9cfe4c0ff835 | 11,773 |
def get_gitlab_scripts(data):
"""GitLab is nice, as far as I can tell its files have a
flat hierarchy with many small job entities"""
def flatten_nested_string_lists(data):
"""helper function"""
if isinstance(data, str):
return data
elif isinstance(data, list):
... | ad73c1ea6d4edcbce51eea18de317d7ab2d5e536 | 11,774 |
import new
def method(cls):
"""Adds the function as a method to the given class."""
def _wrap(f):
cls.__dict__[f.func_name] = new.instancemethod(f,None,cls)
return None
return _wrap | 0f746420bf9870dec5d8a5e69bcec414530fc1cb | 11,775 |
def maps_from_echse(conf):
"""Produces time series of rainfall maps from ECHSE input data and catchment shapefiles.
"""
# Read sub-catchment rainfall from file
fromfile = np.loadtxt(conf["f_data"], dtype="string", delimiter="\t")
if len(fromfile)==2:
rowix = 1
elif len(fromfile)>2:
... | 31e09c5bed2f7fe3e0d750a59137c05ef987dc2e | 11,776 |
def utility_assn(tfr_dfs):
"""Harvest a Utility-Date-State Association Table."""
# These aren't really "data" tables, and should not be searched for associations
non_data_dfs = [
"balancing_authority_eia861",
"service_territory_eia861",
]
# The dataframes from which to compile BA-Uti... | 6b0357f1d7024bcfddac6981d968e67e5dbeba51 | 11,777 |
def is_smtp_enabled(backend=None):
"""
Check if the current backend is SMTP based.
"""
if backend is None:
backend = get_mail_backend()
return backend not in settings.SENTRY_SMTP_DISABLED_BACKENDS | 988d2173923dc53cd3179cf0866c702ab9fe69d4 | 11,778 |
import requests
def get_presentation_requests_received(tenant: str, state: str = ''):
"""
state: must be in ['propsal-sent', 'proposal-received', 'request-sent', 'request-received', 'presentation-sent', 'presentation-received', 'done', 'abondoned']
"""
possible_states = ['', 'propsal-sent', 'proposal-... | 1157712b8e4df1b269892a2d3ec15dae366d8d71 | 11,779 |
def generate_round():
"""
Генерируем раунд.
Returns:
question: Вопрос пользователю
result: Правильный ответ на вопрос
"""
total_num, random_num = generate_numbers()
question = " ".join(total_num)
answer = str(random_num)
return question, answer | d4b535016e6ca6c6d673c1a6a2ee2c20eca87bc1 | 11,780 |
from datetime import datetime
def get_basic_activity():
"""
A basic set of activity records for a 'Cohort 1' and CoreParticipant participant.
"""
return [
{'timestamp': datetime(2018, 3, 6, 0, 0), 'group': 'Profile', 'group_id': 1,
'event': p_event.EHRFirstReceived},
{'timesta... | 4ee13cf35326d6c09fb4174f0e4217b17a34a545 | 11,781 |
def bad_multi_examples_per_input_estimator_misaligned_input_refs(
export_path, eval_export_path):
"""Like the above (good) estimator, but the input_refs is misaligned."""
estimator = tf.estimator.Estimator(model_fn=_model_fn)
estimator.train(input_fn=_train_input_fn, steps=1)
return util.export_model_and_e... | c08fac8d0ae8679db56128dc8d4a36a5492a6737 | 11,782 |
import os
def page_is_dir(path) -> bool:
"""
Tests whether a path corresponds to a directory
arguments:
path -- a path to a file
returns:
True if the path represents a directory else False
"""
return os.path.isdir(path) | bb52f6f09110e085fbb4cd8aeb9d03b36fe07b84 | 11,783 |
import logging
import yaml
def read_configuration(dirname_f: str) -> dict:
"""
:param dirname_f: path to the project ending with .../cameras_robonomics
:type dirname_f: str
:return: dictionary containing all the configurations
:rtype: dict
Reading config, containing all the required data, suc... | 784c45095d1dd5530c65e9000b0e9d7f95662b20 | 11,784 |
def caption_example(image):
"""Convert image caption data into an Example proto.
Args:
image: A ImageMetadata instance.
Returns:
example: An Example proto with serialized tensor data.
"""
# Collect image object information from metadata.
image_features, positions = read_object(image.objects, image... | f989774a0d3321717cbb09f6342a6c86f5433c54 | 11,785 |
def GetAttributeTableByFid(fileshp, layername=0, fid=0):
"""
GetAttributeTableByFid
"""
res = {}
dataset = ogr.OpenShared(fileshp)
if dataset:
layer = dataset.GetLayer(layername)
feature = layer.GetFeature(fid)
geom = feature.GetGeometryRef()
res["geometry"] = geo... | 42b845ae5b1a3c9976262cc37f5854b80aa7b290 | 11,786 |
def get_root_folder_id(db, tree_identifier, linked_to, link_id):
"""Get id of the root folder for given data category and profile or user group
Args:
db (object): The db object
tree_identifier (str): The identifier of the tree
linked_to (str): ['profile'|'group']
link_id (int): ... | 7378ec4852d90913282109dcce5d8168613c835e | 11,787 |
def str_cell(cell):
"""Get a nice string of given Cell statistics."""
result = f"-----Cell ({cell.x}, {cell.y})-----\n"
result += f"sugar: {cell.sugar}\n"
result += f"max sugar: {cell.capacity}\n"
result += f"height/level: {cell.level}\n"
result += f"Occupied by Agent {cell.agent.id if cell.agen... | d62801290321d5d2b8404dbe6243f2f0ae03ecef | 11,788 |
def get_idx_pair(mu):
"""get perturbation position"""
idx = np.where(mu != 0)[0]
idx = [idx[0], idx[-1]]
return idx | eed8b77f3f21af93c28c84d6f325dd2161740e6f | 11,789 |
def zeeman_transitions(ju, jl, type):
""" Find possible mu and ml for valid ju and jl for a given transistion
polarization
Parameters:
ju (scalar): Upper level J
jl (scalar): Lower level J
type (string): "Pi", "S+", or "S-" for relevant polarization type
Returns:
tu... | 446d9683da6cc027003b2ec755d8828ccb01db5d | 11,790 |
def get_reachable_nodes(node):
"""
returns a list with all the nodes from the tree with root *node*
"""
ret = []
stack = [node]
while len(stack) > 0:
cur = stack.pop()
ret.append(cur)
for c in cur.get_children():
stack.append(c)
return ret | c9ffaca113a5f85484433f214015bf93eea602d1 | 11,791 |
def imagetransformer_sep_channels_16l_16h_imgnet_lrg_loc():
"""separate rgb embeddings."""
hparams = imagetransformer_sep_channels_12l_16h_imagenet_large()
hparams.num_hidden_layers = 16
hparams.local_attention = True
hparams.batch_size = 1
hparams.block_length = 256
return hparams | 1d428cae33a6a34a7844171c72c7821a44fc3e97 | 11,792 |
def torsion_coordinate_names(zma):
""" z-matrix torsional coordinate names
(currently assumes torsional coordinates generated through x2z)
"""
name_dct = standard_names(zma)
inv_name_dct = dict(map(reversed, name_dct.items()))
geo = automol.geom.without_dummy_atoms(geometry(zma))
tors_names... | a7820e1619d4a73260ec4d9255b78cdec2263a55 | 11,793 |
from typing import List
from typing import Dict
def extract_other_creditors_d(
page: pdfplumber.pdf.Page, markers: List[Dict], creditors: List
) -> None:
"""Crop and extract address, key and acct # from the PDf
:param page: PDF page
:param markers: The top and bottom markers
:return: Address, key... | cb66185c68c7ab3febeee611e4384b839b42417e | 11,794 |
from typing import List
from pathlib import Path
def get_dicdirs(mecab_config: str = "mecab-config") -> List[Path]:
"""Get MeCab dictionary directories.
Parameters
----------
mecab_config : str
Executable path of mecab-config, by default "mecab-config".
Returns
-------
List[Path]... | 26d7969c072a9aa0668db31c296ee930b567049f | 11,795 |
def new_instance(settings):
"""
MAKE A PYTHON INSTANCE
`settings` HAS ALL THE `kwargs`, PLUS `class` ATTRIBUTE TO INDICATE THE CLASS TO CREATE
"""
settings = set_default({}, settings)
if not settings["class"]:
Log.error("Expecting 'class' attribute with fully qualified class name")
... | bf32bd41105052816a9a54efb71143f2a250502f | 11,796 |
from sys import path
def find_entry(entries, fn):
"""Find an entry that matches the given filename fn more or less."""
entry = get_entry_by_filename(entries, curr_file)
if entry is not None:
return entry
key = lambda fn: path.splitext(fn)[0]
entry = get_entry_by_filename(entries, curr_fi... | 0552d61bea835b5eb3975a388287062fcb733b33 | 11,797 |
def get_type(k):
"""Takes a dict. Returns undefined if not keyed, otherwise returns the key type."""
try:
v = {
'score': '#text',
'applicant': 'str',
'applicant_sort': 'str',
'author': 'str',
'author_sort': 'str',
'brief': 'boo... | fec3b7e04531dd202c46366f096f687160c68320 | 11,798 |
def al(p):
"""
Given a quaternion p, return the 4x4 matrix A_L(p)
which when multiplied with a column vector q gives
the quaternion product pq.
Parameters
----------
p : numpy.ndarray
4 elements, represents quaternion
Returns
-------
numpy.ndarray
4x4 matrix des... | 1e4803bffd75fb841b723d504261c51019d5d45e | 11,799 |
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