content stringlengths 35 762k | sha1 stringlengths 40 40 | id int64 0 3.66M |
|---|---|---|
import argparse
def parse_options():
"""Parses command line options"""
parser = argparse.ArgumentParser()
parser.add_argument("-o", "--output", help="Output file name (e.g oui.h)")
parser.add_argument("-u", "--url", help="Wireshark oui/manuf file url")
opt = parser.parse_args()
return opt | f01013440685506ef3bef27e6c0d79147c2b896f | 3,611,800 |
def gettext(msg, domain='python-apt'): # real signature unknown; restored from __doc__
"""
gettext(msg: str[, domain: str = 'python-apt']) -> str
Translate the given string. This is much faster than Python's version
and only does translations after setlocale() has been called.
"""
return "" | a6d83a79110ec233f86878fc6aa9f37f2b3e61fa | 3,611,801 |
def as_sparse_or_tensor_variable(x, name=None):
"""
If we can't make a sparse variable, we try to make a tensor variable.
"""
try:
return as_sparse_variable(x,name)
except (ValueError, TypeError):
return theano.tensor.as_tensor_variable(x,name) | 4e9560dc48bd0388b376b9ee29b303850b8ad2e1 | 3,611,802 |
def freeze(slug):
"""
Prevent a builder from updating it's source code to a newer version.
The software will still be re-built if it's dependants are upated.
"""
freeze_file = settings.get('install_path') + 'etc/build-freeze'
return file_filter.AppendUnique(freeze_file, slug).run() | e08b0146fc5c4eafaeba689a3aaf1dff04c06192 | 3,611,803 |
def get_compressor(alg):
"""Return an instance of a compressor
This function returns an object that can be used for data compression.
"""
return _cmp_compressors[alg]() | a40274f069b2fb7bf5afc05efb10b39d5cea5179 | 3,611,804 |
import json
import uuid
import time
def confirm(self, speech, timeout):
"""
Start the view 'confirm'
:param speech: the text that will be use by the Local Manager for tablet and vocal
:type speech: dict
:param timeout: maximum time to wait for a reaction from the local manager
:type timeout: ... | 41a1061879dc14f32a567bb4860195221385609a | 3,611,805 |
def generateAdjMatrix(edgeJsonList, sent_len):
""" Function to generate Adjacency matrix from Depedency Parse Tree """
sparseAdjMatrixPos = [[], [], []]
sparseAdjMatrixValues = []
deptags = []
gov_words = [0] * sent_len
adjMatrix = [0] * sent_len
for i in range(sent_len):
adjMa... | ca8af1991b072c334cab20c317a3cb2e00d8f67f | 3,611,806 |
import operator
def assert_no_duplicate_router_ids(
snapshot=None,
nodes=None,
protocols=None,
soft=False,
session=None,
df_format="table",
):
# type: (Optional[str], Optional[str], Optional[List[str]], bool, Optional[Session], str) -> bool
"""Assert that there are no duplicate router ... | 51d987ece746ea481fa39490aba364765512ce5f | 3,611,807 |
def __find_position_for_conclusion_of_argument(current_arg, list_todos, list_dones, positions):
"""
:param current_arg: Argument
:param list_todos: List of Arguments
:param list_dones: List of Argument.uids
:param positions: List of Statements - return value
:return:
"""
a = [arg.uid fo... | 39a5c5f8e517a166b2e1bcb0072633af3fe2cf93 | 3,611,808 |
from typing import Generator
def de_bruijn(alphabet: bytes, n: int) -> Generator[str, None, None]:
"""De Bruijn sequence for alphabet and subsequences of length n (for compat. w/ pwnlib)."""
k = len(alphabet)
a = [0] * k * n
def db(t: int, p: int) -> Generator[str, None, None]:
if t > n:
... | bc647a3e140a81c47703eaa2216d49e0aa78f088 | 3,611,809 |
def writexl_alt_getsheetref(path_wbrels, path_wb):
"""
Takes a file path for '/xl/_rels/workbook.xml.rels' and '/xl/workbook.xml' files
and returns a dictionary relationship between sheetID, name and xml worksheet file path
rId: xml's indexing between files (workbook.xml.rels defined rID to xml work... | 84852fc99897b471834ce3a9dc721e18b41047e1 | 3,611,810 |
import re
def createPattern(string):
"""Cria um padrรฃo de comandos de bot."""
return re.compile(f"/{string}|{string}") | b2b013dc71d5f49f041402ecf98db8b923f4d22a | 3,611,811 |
def miner_predictions():
"""
Returns a Model Template Prediction Status screen
:return: HTML Template for Model Prediction Status
"""
logger.debug("/predictions - remote addr:" + request.remote_addr)
# render the template
return render_template('predictions.html', version='0.0') | 472bb06ca785f7d3bd6e019cfaa0299ce19972fa | 3,611,812 |
def gnomad_filtered_func(raw_value):
""" We use FILTER in Gnomad3 (GRCh38 only) - need to convert back to bool """
return raw_value not in (None, "PASS") | 6de1d4ef9395e89c11b08cdb43decb045656494b | 3,611,813 |
from bs4 import BeautifulSoup
def parse(html_bytes: bytes, *args, **kwargs) -> BeautifulSoup:
"""Convenience method for ``ZimHtmlParser(html_text).simplify()``."""
return ZimHtmlParser(html_bytes, *args, **kwargs).simplify() | 2b1c711a9ead749e0e8b6279e4861c29b97aa968 | 3,611,814 |
def register(name):
"""Registers a new logs preprocessor function under the given name."""
def add_to_dict(func):
_PREPROCESSORS[name] = func
return func
return add_to_dict | a07008f74ea4a93a6763d1062c78d50a64d9614e | 3,611,815 |
import os
import posixpath
def _gather_proto_info_from_repo(repo):
"""Gathers all protos from the given repo.
Args:
* repo (RecipeRepo) - The repo to gather all protos from.
Returns List[_ProtoInfo]
"""
# Tuples of
# * fwd-slash path relative to repo.path of where to look for protos.
# * fwd-s... | 3382653c66d4ddbb1895998cdb21a9da2626d7a6 | 3,611,816 |
import torch
def _project_z(z, project_method='clip'):
"""To be used for projected gradient descent over z."""
if project_method == 'norm':
z_p = torch.nn.functional.normalize(z, p=2, dim=-1)
#elif project_method == 'clip': #not reimplemented yet
# z_p = tf.clip_by_value(z, -1, 1)
else:
raise Value... | 6cabb462dcbfff7ffdc065601f4a68671822f93f | 3,611,817 |
from datetime import datetime
def __dirnames_matching_format(dirnames, format):
"""
Iterates through dirnames and returns a sorted array of directory names
that match the provided format.
"""
matching_dates = []
for dirname in dirnames:
try:
dt = datetime.strptime(dirname, ... | 52349f0992a0ac0366d75f5328f674ab179246be | 3,611,818 |
import re
def solve(s):
"""doc"""
return "".join([w.capitalize() for w in re.split(r"(\W+)", s)]) | 28f075dd47c3ec57d6bb2a1675ae77815378786e | 3,611,819 |
import requests
def marco_china_hk_trade_diff_ratio() -> pd.DataFrame:
"""
ไธๆน่ดขๅฏ-็ปๆตๆฐๆฎไธ่ง-ไธญๅฝ้ฆๆธฏ-้ฆๆธฏๅๅ่ดธๆๅทฎ้ขๅนด็
https://data.eastmoney.com/cjsj/foreign_8_7.html
:return: ้ฆๆธฏๅๅ่ดธๆๅทฎ้ขๅนด็
:rtype: pandas.DataFrame
"""
url = "https://datainterface.eastmoney.com/EM_DataCenter/JS.aspx"
params = {
... | 7d60526def9c00944638b80311dbbd6913a11ca2 | 3,611,820 |
from typing import Optional
def make_default_sim_env(
interface: Optional[GymTrainedInterface] = None,
) -> CustomSimEnv:
""" A simulator environment with the following characteristics:
The action and observation spaces are continuous.
An action in this environment is a pilot signal for each EVSE,
... | e023dc37fc81fb8d5e17f87d66b3035e9909a3aa | 3,611,821 |
from iris.cube import Cube
from iris.coords import DimCoord
def make_dummy_1d_cube(job_n=0):
"""
Makes a dummy 1d cube filled with dummy data. It has a scalar job coordinate
to make ensemble stacking convenient
"""
x = np.arange(100)
y = np.sin(x) * np.cos(x + 0.3)
obs = DimCoord(x, var_... | 992251299f13bbfa7581f647602a349b98547635 | 3,611,822 |
def edit_delivery(request, delivery):
"""Edit a delivery as a full network admin: act upon its lifecycle, control which subgroups have been validated,
change the products characteristics, change other users' orders."""
dv = m.Delivery.objects.get(id=delivery)
if dv.network.staff.filter(id=request.user.i... | 7d807af78d2b063555a529a525295352513af919 | 3,611,823 |
def get_fields_by_name(model_cls, *field_names):
"""Return a dict of `models.Field` instances for named fields.
Supports wildcard fetches using `'*'`.
>>> get_fields_by_name(User, 'username', 'password')
{'username': <django.db.models.fields.CharField: username>,
'password': <django.d... | 8ce9c845adbff9bb53da50c7d7e208aa8077e718 | 3,611,824 |
def pyramidnet110_a84_svhn(num_classes=10, **kwargs):
"""
PyramidNet-110 (a=84) model for SVHN from 'Deep Pyramidal Residual Networks,' https://arxiv.org/abs/1610.02915.
Parameters:
----------
num_classes : int, default 10
Number of classification classes.
pretrained : bool, default Fal... | 085571ae5ab102de5e1bdeab100d6244608f899a | 3,611,825 |
def list_of_comments(fname) :
"""Returns list of str objects - comment records from file.
- fname - file name for text file.
"""
#if not os.path.lexists(fname) : raise IOError('File %s is not available' % fname)
f=open(fname,'r')
cmts = []
for rec in f :
if rec.isspace() : conti... | 5aea0668c006b4a4615cab01acd07db8dc1fb2b5 | 3,611,826 |
def publish_branch(branch):
"""Publishes given branch."""
repo_check()
return repo.git.execute([git,
'push', '-u', remote.name, branch]) | 7335704d94efdc5dfba65dab914ab75a70bc24d9 | 3,611,827 |
import base64
def pil_to_base64(pilimage): # pragma: no cover
"""Returns base64 encoded image given a PIL Image"""
buffer = BytesIO()
pilimage.save(buffer, "png")
return base64.b64encode(buffer.getvalue()).decode() | 9c2673b97a86544c5281cbd43ff6dfdad31a4253 | 3,611,828 |
def save_result(x,time,lev,copy_from_source,dflt_units='k'):
"""Saves results from projection in netcdf output format.
Input parameters:
x: projection indices (2dim array with time,mode)
time: coordinates from input netcdf file
lev: level coordinates (PCA modes)
copy_from_s... | 704eb922bf8ccb4f8669df5ee0cf6b134ed4b55c | 3,611,829 |
import os
def pick_a_filename(i):
"""
Input: {
(directory) - the directory name from which to pick a filename (defaults to '.' - current directory)
(file_suffix) - the file type (defaults to '' - none)
}
Output: {
return ... | 1054e93bb0b7d747eec32e7e1fee868bdfe41ed5 | 3,611,830 |
def linkcode_resolve(domain, info, author, package):
"""Determine the URL corresponding to a Python object."""
try:
module = import_module(info["module"])
except ModuleNotFoundError:
# No URL is returned when the object is not in
# any module, or the module cannot be imported
... | ec849260610890510f0686ab4b1150eb30efe99c | 3,611,831 |
def _max(self, dim=None, keepdim=False):
"""Map of 'max' pytorch method."""
x = self
dim_orig = dim
if dim is None:
dim = _build_fwd_tuple(x.shape)
elif isinstance(dim, int):
dim = (dim,)
dim = _dim_tuple_explicit(x.shape, dim)
ret_max = P.array_max(x, dim)
ret_argmax =... | ecf96de331d24b0b692c12fa24269fb9863121bb | 3,611,832 |
import os
def main(list_packed_vars):
"""
Model simulation
Parameters
----------
list_packed_vars : list
list of packed variables that enable the use of parallels
Returns
-------
netcdf files of the simulation output (specific output is dependent on the output option)
"""... | 56a7ab91c39883eadaf9dfe3ffe6dbe440731fd3 | 3,611,833 |
import re
def minify(source):
"""
Removes comments from the source code
"""
multiline = re.compile("(/\*.*?\*/)", re.DOTALL)
singleline = re.compile("//.*?\n")
remove_multiline = lambda f: re.sub(multiline, "", f)
remove_singleline = lambda f: re.sub(singleline, "", f)
return map(remove_multiline, ... | 3743e4071485d1ae085037a4bf4cd492f4f81d29 | 3,611,834 |
def configmap_data_keys():
"""
Build keys for the ``data`` mapping of a ``ConfigMap``.
"""
return builds(
lambda labels, dot: dot + u".".join(labels),
labels=lists(object_name(), average_size=2, min_size=1, max_size=253//2),
dot=sampled_from([u"", u"."]),
).filter(
la... | 4c88839707f37cfb334f6bedce080b4f97a84c58 | 3,611,835 |
from typing import Callable
from typing import Any
def handler_assertions(
handler_name: str,
test_case: str,
error_name: str = None,
) -> Callable:
"""Configurable decorator for testing assertions for a given handler"""
def decorator_function(
decorated_function: Callable... | 7abb8776e029c330c0ad4b060bdf8e0c1ea3af35 | 3,611,836 |
import random
def create_bitmap_dataset(bitmap_data, output_dir, output_name, classnames, output_shards):
"""
Writes the provided bitmap_data as tf.Example in tf.Record
:param bitmap_data: tuple of lists containing (x_train, y_train, x_test, y_test)
:param output_dir: path where to write the outp... | 050fe1ed5a66cf49741d24e21062fadba08a0c7c | 3,611,837 |
import logging
def with_logger(cls):
"""Class decorator to add a logger to a class."""
attr_name = '_logger'
cls_name = cls.__qualname__
module = cls.__module__
if module is not None:
cls_name = module + '.' + cls_name
else:
raise AssertionError
setattr(cls, attr_name, logg... | 77f854ac6d1cbe95ff7804184a1a67a513ac81ae | 3,611,838 |
import itertools
def _generate_mesh_simplices(
*, limits, mesh_size, periodic=False, skip_origin=False
):
"""
Generate the starting simplices for given limits and mesh size.
"""
dim = len(limits)
if len(mesh_size) != dim:
raise ValueError(
"Inconsistent dimensions: ... | 7b2008906aaafb411c22128ffcdd4f2ce1c13471 | 3,611,839 |
def write_tfrecords(data_path,video_paths,action_labels,
n_vids_per_batch,subset,
n_frames_batch = 16,
n_frames_chunk = 512):
"""Function to write tfrecords.
:param data_path: name of tfrecords file to write
:param video_paths: list contain... | 4c6e27a2cc9a2079a8f2828d288ea65542b8e56a | 3,611,840 |
def _set_up_thermo_mets(base_df: pd.DataFrame, mets_list: list, mets_conc_df: pd.DataFrame) -> tuple:
"""
Given the base excel input file, the list of metabolites in the model and a dataframe with metabolite
concentrations averages and respective stdev, fills in the thermoMets sheet.
First fills in conc... | c048a6c220de7055f5cb5ce0a65f969b3d0a9be7 | 3,611,841 |
def setup_constant(prefix, **kwargs):
""" Set up a simple constant function model.
:param prefix: Model prefix
:type prefix: string
:param kwargs: Keyword arguments
:return: LMFIT model and parameters
:rtype: (lmfit.Model, lmfit.Parameters)
"""
amplitude = kwargs.pop('amplitude', 5)
... | 3d0c24887e81c34b499190a79185822fef641bd8 | 3,611,842 |
def subapp_css_static(filename):
"""
set css files.
:param filename: css file name.
:return: static path.
"""
return static_file(filename, root='kokemomo/plugins/subapp/view/resource/css') | bf29bc7a7f9cbab9e2db3da0841eab018c57d96b | 3,611,843 |
def graph1D(n: int, pbc: bool = True) -> Graph:
"""
1D PBC chain with n sites
:param n:
:return:
"""
g = nx.Graph()
for i in range(n):
g.add_node(i)
for i in range(n - 1):
g.add_edge(i, i + 1, weight=1.0)
if pbc is True:
g.add_edge(n - 1, 0, weight=1.0)
... | fdb809ee46c7b9d7ebdd241175e199db747f9227 | 3,611,844 |
def _solve_triangular_right(a, b, left_side, lower, trans_a):
"""An unrolled right-looking triangular solve on (blocked) LapaxMatrices."""
n = a.shape[-1]
def solve(a, b):
return _solve_triangular_left(a, b, left_side, lower, trans_a)
if n == 1:
return solve(a.bview(1), b.bview(1))
out = full_like(... | 1dc6826bfb717a8b162bd2a5d997368276ae0b47 | 3,611,845 |
from numpy import linspace, meshgrid
def _get_latlons(nlat, nlon):
"""Short summary.
Parameters
----------
nlat : type
Description of parameter `nlat`.
nlon : type
Description of parameter `nlon`.
Returns
-------
type
Description of returned object.
"""
... | f43553b4f758ac2a060f609e2781645b79466cb4 | 3,611,846 |
def abs(x: Array, /) -> Array:
"""
Array API compatible wrapper for :py:func:`np.abs <numpy.abs>`.
See its docstring for more information.
"""
if x.dtype not in _numeric_dtypes:
raise TypeError("Only numeric dtypes are allowed in abs")
return Array._new(np.abs(x._array)) | cb37d3486fd82535de77f4df56a30c7e713127b9 | 3,611,847 |
def challenge_hash(peer_challenge, auth_challenge, user_name):
"""
RFC 2759
section 8.2
ChallengeHash
:param peer_challenge:
:param auth_challenge:
:param user_name:
:return: challenge
example
peer_challenge = "\x21\x40\x23\x24\x25\x5E\x26\x2A\x28\x29\x5F\x2B\x3A\x33\x7C\x7E"
... | 153f33509e09ea140433d6ef46aab2225bbb5808 | 3,611,848 |
def var_historic(r, level=5):
"""
Returns the historic Value at Risk at a specified level
i.e. returns the number such that "level" percent of the returns
fall below that number, and the (100-level) percent are above
"""
if isinstance(r, pd.DataFrame):
return r.aggregate(var_historic, le... | dd2b23c15b7aee470886621ba8d64bee571488f9 | 3,611,849 |
from typing import Dict
def convert_to_km(distance: float, print_output: bool = True) -> Dict[str, float]:
"""Convert a miles distance into the double of km.
Args:
distance: a distance (in miles).
print_output: if True, prints the progress.
Returns:
A dictionary with two keys ('o... | 1fb9dbbeb890a348d0feeebaea1a308bc06b039d | 3,611,850 |
import torch
def discriminator_loss(D, real_images, fake_images):
"""Loss computed to train the GAN discriminator.
Args:
D: The discriminator.
real_images of shape (batch_size, nc, 28, 28): Real images.
fake_images of shape (batch_size, nc, 28, 28): Fake images produces by the generator.
... | 397c1cd3c4ad8f90e78f4d2d0eb0501093133735 | 3,611,851 |
def Lucas_chain(n, f, g, x_0, x_1):
"""
Given an integer n, two functions f and g, and initial value (x_0, x_1),
compute (x_n, x_{n+1}), where the sequence {x_i} is defined as:
x_{2i} = f(x_i)
x_{2i+1} = g(x_i, x_{i+1})
"""
binary = arith1.expand(n, 2)
u = x_0
v = x_1
while b... | 514d9977434cbc5538d97e9622ea6c983a0bf604 | 3,611,852 |
import itertools
def build_input_from_segments(
history, reply, tokenizer, lm_labels=False, with_eos=True
):
""" Build a sequence of input from 2 segments: history and candidate reply. """
bos, eos, speaker1, speaker2 = tokenizer.convert_tokens_to_ids(SPECIAL_TOKENS[:-1])
# build input sequence as:
... | 1ab5a269a253e8042c920f8c74990923fee7ad3d | 3,611,853 |
import aiohttp
def aiohttp_socket_timeout(socket_timeout_s):
""" Return a aiohttp.ClientTimeout object with only socket timeouts set. """
return aiohttp.ClientTimeout(total=None,
connect=None,
sock_connect=socket_timeout_s,
... | c17a40a532aee15557b4e507439b0a7b2e98989e | 3,611,854 |
import json
from datetime import datetime
def get_contributions_from_file(site, username):
"""Get a list of Wikipedia-namespace contributions."""
with open("my-contribs.json") as my_contribs_file:
data = json.load(my_contribs_file)
for contrib in data:
time = datetime.datetime.strp... | f4458c4882beadca212560f30da4d12b49d811e6 | 3,611,855 |
def alignment_to_search_path(algn):
"""
Given an alignment, make searchpath.
Searchpath must step exactly one position in x XOR y at each time step.
In the case of a block of deletions, the order found by DP is not meaningful.
To make things consistent and to improve the probability of recoveri... | c5daa5c1bd9045527f588c8ca856f69b5d52838f | 3,611,856 |
def getMulitples(indices):
"""Return a subset with no multiples (filters out the bad ones)."""
multiples = []
added = []
for i in range(0, len(indices) - 1):
if indices[i][0] == indices[i + 1][0]:
added.append(indices[i])
elif added:
added.append(indices[i])
... | 4846fe1950f7d1a5379595b93e18c3ed0eb2d160 | 3,611,857 |
def get_pourbaix_info(entry: dict) -> dict:
"""
Grabs the relevant pourbaix entries for a given mpid
from Materials Project and constructs a pourbaix diagram for it. This currently only supports MP materials.
Args:
entry: bulk structure entry as constructed by
catlas.load_bulk_st... | c53cb58af64a3b63909e56706dfee1d933db20da | 3,611,858 |
def do_math(a, b, operator):
"""Helper function that performs computation between two numbers."""
if operator == "+":
return int(b) + int(a)
elif operator == "-":
return int(b) - int(a)
elif operator == "*":
return int(b) * int(a)
elif operator == "/":
return int(b)... | 5bffd1db1659c9f3420cc66a28525698de3beef5 | 3,611,859 |
def getFrequencyBands(sessionId):
"""
Get the frequency bands supported by this server.
Returns: A list of frequency bands for the sensors managed by this server.
"""
@testcase
def getFrequencyBandsWorker(sessionId):
try:
if not Config.isConfigured():
util.de... | 904ee2c0ad5a35ae5acd66b96edc0737b2687db4 | 3,611,860 |
def deg_to_arcsec(angle: float) -> float:
"""
Convert degrees to arcseconds.
Args:
angle: Angle in units of degrees.
Returns:
angle: Angle in units of arcseconds.
"""
return float(angle) * 3600. | 02fd099627970116bf5513af8b8d2d62bdc8ed41 | 3,611,861 |
def pixel_level_peak_finder_1d(correlation_lines: np.ndarray) -> np.ndarray:
"""
This function returns a numpy array containing the location of the maximum surface value
to pixel level accuracy for each row of the input matrix.
:return: The location of the maximum surface values to pixel level accuracy... | 6afa9b3a9e565aeab9915e7c8b5699df0842d498 | 3,611,862 |
def Shift(**kwargs):
"""
Calculates register shifts between strands based on their pairing and length
"""
refbluefile = kwargs.get('refblue')
seg1 = kwargs.get('seg1')
seg2 = kwargs.get('seg2')
refblue = Blueprint(refbluefile)
nseg1 = len( refblue.segment_... | b0a377131df521e3d96790a0b6f9d1e2d1893a64 | 3,611,863 |
import time
import os
def ul_lands_download(save_dir = None):
"""
Downloads las files from University Lands Texas
This function downloads files from the university lands ftp
website located at publiftp.utlands.utsystem.edu. It inventories
readable logs into a csv file containing header data in t... | 912b9f75d0c4a93581d942b47f62fed2fa154765 | 3,611,864 |
async def test_ap_fails(injector):
"""Async providers must not be usable in sync consumers"""
class A:
pass
a = A()
@injector.consumer
def consumer(a_: A):
assert a_ is a
@injector.provider
async def bean() -> A:
return a
with pytest.raises(pyserp.InjectionErr... | f9cb09ec0a5c8246b1ed65c5f388a8904d4e60d4 | 3,611,865 |
def gru_run(params, x_t):
"""Run the Vanilla RNN T steps, where T is shape[0] of input.
Args:
params: dict of GRU parameters
x_t: np array of inputs with dim ntime x u
Returns:
2-tuple of np arrays (hidden states w dim ntime x n, outputs w dim ntim x o)
"""
return gru_run_with_h0(params, x_... | 294dbd3e56d1a8ea337c03bd99b15443b6a908f5 | 3,611,866 |
def set_window_width(image, MIN_BOUND=-1000.0, MAX_BOUND=400.0):
"""่ฎพ็ฝฎ็ชๅฎฝ"""
image[image > MAX_BOUND] = MAX_BOUND
image[image < MIN_BOUND] = MIN_BOUND
return image | 0dfa6e858c74cacc2cc8724d33f9b7fd96835d0c | 3,611,867 |
def _process_merge(p1_ctx, p2_ctx, ctx):
"""compute the appropriate changed files for a changeset with two parents
This is a more advance case. The information we need to record is summarise
in the following table:
โโโโโโโโโโโโโโโโฌโโโโโโโโโโโโโโโฌโโโโโโโโโโโโโโโฌโโโโโโโโโโโโโโโฌโโโโโโโโโโโโโโโ
โ diff... | 8c3fedad5578c37eccf35a7fdd844ab3c244d57c | 3,611,868 |
def create_mmt_encoder_inputs(data_cfg: cfg.DataConfig):
"""Creates inputs for `MmtEncoder`."""
patch_embedding_size = (data_cfg.patch_size ** 2) * 3
num_patch_per_row = data_cfg.image_size // data_cfg.patch_size
num_patches = num_patch_per_row ** 2
max_seq_len = data_cfg.max_seq_len
word_ids = tf.keras.... | 1ccbe6468e25cccd32049dd65300426819d9737a | 3,611,869 |
import json
def update_chart_info(_figure, chart_data_json_str):
"""
A callback function to set the sample count for the number of samples that
have been displayed on the chart.
Args:
_figure (object): A figure object for a dash-core-components Graph for
the strip chart - triggers... | fd28e28b7b48131bb56d6d9f29e4fe438b33bb7a | 3,611,870 |
def record_copy_all(node, **kwargs):
""" A default rcd implementation that copies all kwargs to the tape.
the impl is used for the vjp and vjp primitives.
the impl is can be used for the apl primitives if no rcd is given;
but we use 'record_copy_autodiff' to save a much smaller subset
... | e7e957c1d9fb0cc36bf54c1ab431ba4c7892838c | 3,611,871 |
from typing import Tuple
def split_df_train_test(data: pd.DataFrame, perc_train: float) -> Tuple[list, list]:
"""Create train test split"""
# get percentages
assert perc_train >= 0.0
assert perc_train <= 1.0
# get number of examples to use for training
num_train = int(perc_train * len(data))
... | 48a5de60273189e56969ab87588d236074d50de1 | 3,611,872 |
def read_file(filename):
""" Return the content of a file as a list of strings, each corresponding to a line
:param filename: string: location and name of the file
:return: content of filename
"""
with open(filename, 'r') as ofile:
content = ofile.read().splitlines()
return content | 58a2718265fef848e484178e407aee6f7017a52a | 3,611,873 |
def parse_record(raw_record):
"""Parses a record containing a training example of an image.
The input record is parsed into a label and image, and the image is passed
through preprocessing steps (cropping, flipping, and so on).
Args:
raw_record: scalar Tensor tf.string containing a serialized
... | 2f669bda6cec630e4fd81576532a96f1ec6d6a00 | 3,611,874 |
def helicsFederateRegisterGlobalTypeInput(fed: HelicsFederate, name: str, type: str, units: str) -> HelicsInput:
"""
Register a global publication with an arbitrary type.
The publication becomes part of the federate and is destroyed when the federate is freed so there are no separate free functions for subs... | 487179f3de8d9f72efaa696e50441250e49f5438 | 3,611,875 |
from typing import Optional
from typing import Mapping
def get_cluster(cluster_identifier: Optional[str] = None,
tags: Optional[Mapping[str, str]] = None,
opts: Optional[pulumi.InvokeOptions] = None) -> AwaitableGetClusterResult:
"""
Provides details about a specific redshift c... | bd5ca8151d0fafbeef735707b1971c03f05ec9e8 | 3,611,876 |
def translate_to_origin(structure, weight="mass", atom_mask=None, dimension=None):
"""Translate a structure to the origin based on the centroid of the whole system or a subset of atom(s).
Parameters
----------
structure : str or :class:`parmed.Structure`
Molecular structure containing coordinat... | 269f566e4fbf43308bf4db8b2972adc3487fcde9 | 3,611,877 |
def score_1(game, player): # 82.14%
"""
Heuristics computing score using #player moves - k * #opponent moves
:param game: game
:param player: player
:return: score
"""
if game.is_winner(player) or game.is_loser(player):
return game.utility(player)
opponent = game.get_opponent(p... | 3995237f5d5474660c752c308e1077aad1743d06 | 3,611,878 |
def parse_line( line ):
"""Returns data located in the line."""
tokens = line.split()
return int(tokens[1]), tokens[2], (
int(tokens[4]), # n_i
int(tokens[6]), # s_i
) | 487421bcc50e4d542227e54a1362008a8a678b5b | 3,611,879 |
def find_ancestors(starting_resource, full_name):
"""Find the ancestors for a given resource.
Take advantage of the full name from the data model which has
the entire hierarchy.
Keeping this outside of the class, because the class is mocked out during
testing.
Args:
starting_resource ... | e307c902422077405eb79171d6abc9038724f03b | 3,611,880 |
import random
def select_from_existing_derivations():
"""
Which derivation does the user want to review?
Alternatively, the user can generate a PDF
>>> select_from_existing_derivations()
"""
trace_id = str(random.randint(1000000, 9999999))
logger.info("[trace page start " + trace_id + "]"... | ab6f18277f076d13141b5b7bacf5071510f7a26a | 3,611,881 |
import asyncio
async def is_streamable(filename: str) -> bool:
"""Return if a file is streamable by pyatv.
This method will return if the file format of the given file is supported
and streamable by pyatv. It will never raise an exception, e.g. because the
file is missing or lack of permissions.
... | f924ed95b18c04cb9f9247fecaa92f903a0663cf | 3,611,882 |
def forward_pass(x: np.ndarray, weights: np.ndarray, bias: float) -> np.ndarray:
"""
Method that calculates the activation of the sigmoid function
from a given input, weights and biases.
:param x: input data
:param weights: tuple with the weights
:param bias: value of the biases
:return: ac... | 2ae788aebe921f743cfa9379d1ea496b1b9881f5 | 3,611,883 |
def get_long_description():
"""
Provides the long description.
"""
with open("README.rst", "r", encoding="utf-8") as file_stream:
return file_stream.read() | 35e8b7d1c4db25e1cf49328d4be1d1d2f9ddf581 | 3,611,884 |
def get_connections(ccs_path):
""" Returns list of installed connection names.
Searches "<ccs_path>/ccs_base/common/targetdb/connections" directory for
installed connection names.
Args:
ccs_path (str): full path to ccs installation to use
Returns:
list: connection names
Raise... | 73bc6f875c61f792d746687277fe1a29c04539ac | 3,611,885 |
def escape_latex(strng):
"""Consistently escape LaTeX special characters for _repr_latex_ in IPython
Implementation taken from the IPython magic `format_latex`
Examples
--------
escape_latex('disease_rate') # 'disease\_rate'
Parameters
----------
strng : str
string to esc... | 50958dc7c736b6c3b7fb3d4c2715fcd2e1855205 | 3,611,886 |
import json
def list_subnets(sort_by='name'):
"""
Get list of subnets from maas server
CLI Example:
.. code-block:: bash
salt 'maas-node' maasng.list_subnets
"""
subnets = {}
maas = _create_maas_client()
json_res = json.loads(maas.get(u'api/2.0/subnets/').read())
for ite... | 313d917f6938ecd5ed3a9288fe3116493f128f7a | 3,611,887 |
import os
def stream_profile_sample(self, stream_data): # FileData object
"""Profiles a stream container: look at it as one big blob"""
tracks = {}
stream_data.crc32 = 0x0 # start value crc
meta_length = 0
stream_data.crc32 = calc_crc32(stream_data.name)
# do track stuff
track = TrackData()
track.track_nu... | 048e17beb3ec82fb2aeca76b9a3fbd47d5812451 | 3,611,888 |
def multinomial_as_basic(multinomial, *symbols):
"""
Converts the multinomial to Add/Mul/Pow instances.
multinomial is a dict of {powers: coefficient} pairs, powers is a tuple of
python integers, coefficient is a python integer.
"""
l = []
for powers, k in multinomial.iteritems():
t... | 0d481de0c572966b6fa99073173dc0cbef241fb7 | 3,611,889 |
from typing import List
from typing import Tuple
from typing import Any
import joblib
def topic_modelling(all_data_t: List[List[float]],
tfidf: TfidfVectorizer, n_keywords: int,
param_grid=TRAIN_PARAM_GRID_LDA,
retrain=False, plot=False,
... | 04a5d3f775bb9bc01f8815ba2d842edbbe43c597 | 3,611,890 |
from typing import List
def get_gpu_memory() -> List[int]:
"""Query GPU's for amount of VRAM
Modified from:
https://stackoverflow.com/questions/59567226/how-to-programmatically-determine-available-gpu-memory-with-tensorflow
Returns
-------
VRAM, List[int]
Total GPU VRAM in bits for ea... | facfe363c38b0d9d55b824fd48e79fb44b888ae2 | 3,611,891 |
import base64
def smiles2inchi(smiles):
"""
Converts SMILES to InChi. This method accepts urlsafe_base64 encoded string containing single or multiple SMILES
optionally containing header line, specific to *.smi format.
cURL examples:
curl -X GET ${BEAKER_ROOT_URL}smiles2inchi/$(cat aspirin_with_header.smi | b... | b4bf76ba132d7f52fe5be503ec72ed5149e0a859 | 3,611,892 |
from typing import Dict
from typing import Tuple
def list_vaults_command(client: Client, args: Dict) -> Tuple[str, Dict, Dict]:
"""Lists all vaults.
"""
max_results = int(args.get('max_results', 0))
raw_response = client.list_vaults(max_results)
vaults = raw_response.get('vault')
if vaults:
... | 9e8760eca79e94f0ad52a94aa205531592074b84 | 3,611,893 |
def strip_ddp_state_dict(state_dict):
""" Workaround the fact that DistributedDataParallel prepends 'module.' to
every key, but the sampler models will not be wrapped in
DistributedDataParallel. (Solution from PyTorch forums.)"""
clean_state_dict = type(state_dict)()
for k, v in state_dict.items():
... | f4cd6917db3df384e70c6b54dc4142dd760dd1d2 | 3,611,894 |
def parameter_attention(x,
total_key_depth,
total_value_depth,
output_depth,
memory_rows,
num_heads,
dropout_rate,
name=None):
"""Attention over param... | 199c0d205913a480ee67fce53030ab7d27c45df3 | 3,611,895 |
def plot_gp_plotly(
model: GPModel, mins: TensorType, maxs: TensorType, grid_density=20
) -> go.Figure:
"""
Plots 2-dimensional plot of a GP model's predictions with mean and 2 standard deviations.
:param model: a gpflow model
:param mins: list of 2 lower bounds
:param maxs: list of 2 upper bou... | 42203278f142dbfc30e00df21a2bbc3212e34f64 | 3,611,896 |
def pareto(all_y, maximize=False):
"""
Returns the indices of Pareto-optimal solutions.
Args:
Y [list]: A list of lists containing values to be evaluated for Pareto-
optimality
Returns:
list - The indices of the entries which are Pareto-optimal
"""
all_y = np.asarra... | 02985b54638d90b1ffc0026ff779ddbfaad77ebc | 3,611,897 |
def _import(module_name, class_name):
"""
Return class of the module_name, where module_name is of the form
package.module (testoob's Asserter, which does simple __import__, returns
package, not package.module in this situation).
"""
mod = __import__(module_name)
components = module_name.spl... | 27a20935b305e3c387c861392429794976d7d866 | 3,611,898 |
def plot_roc(labels, score, title='ROC', verbose=True):
"""Plot ROC curve
Parameters
----------
labels : np.ndarray
vector of ground truth
score : np.ndarray
vector of scores assigned by classifier (i.e.
clf.pred_proba(...)[-1] in sklearn)
title : str
title of p... | 4b395988249e10fee803201997140debe3314739 | 3,611,899 |
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