content stringlengths 35 762k | sha1 stringlengths 40 40 | id int64 0 3.66M |
|---|---|---|
import time
import shutil
import os
def local_run(
inputs,
build_results,
timeout=10,
number=3,
repeat=1,
min_repeat_ms=0,
cooldown_interval=0,
enable_cpu_cache_flush=False,
verbose=1,
):
"""
Run function of LocalRunner to test the performance of the input BuildResults.
... | abe40ae0a18612fc3080d9516efbeca7e92ee0f5 | 69,800 |
from typing import Tuple
from typing import Optional
import os
def log_model_summary(model: nn.Module,
input_size: Tuple[int],
full_summary: bool=True,
working_dir: str=".",
model_name: Optional[str]=None,
verbose: bool=1):
"""
produce a text file with the model summary
TODO: A... | 0ca293db7e761dd401ee805e8b9431cae623f455 | 69,801 |
def load_pretrain_embed(embedding_path, max_scan_num=1000000, add_seg_vocab=False):
"""
从pretrained word embedding中读取前max_scan_num的词向量
Args:
embedding_path: 词向量路径
max_scan_num: 最多读多少
"""
## 如果是使用add_seg_vocab, 则全局遍历
if add_seg_vocab:
max_scan_num = -1
embed_dict = di... | dadf109469c70baf922791c3b20f4a5339e1a46b | 69,802 |
def get_object_name(object):
""" Retrieves the name of object.
Parameters:
object (obj): Object to get name.
Returns:
str: Object name.
"""
if object.name[-5:-3] == '}.':
return object.name[:-4]
return object.name | fc695c8bf19817c3217bf6000358695c88de07aa | 69,803 |
def list_functor(annotation):
"""Convert to List of type values"""
to_type = next(iter(annotation), None)
if _is_subtype(to_type, entities.AttributeV2):
return partial(map, attr_v2_functor(to_type.__args__)), list
return partial(map, entities.converter(to_type)), list | 3e8eeec884756964a8c2287a56ed421986b6fff9 | 69,804 |
def create_nine_digit_product(num):
""" Create a nine digit string resulting from the concatenation of
the product from num and multipliers (1, 2, 3,).... Return 0 if string
cannot be length 9.
"""
result = ''
counter = 1
while len(result) < 9:
result += str(num * counter)
... | 9c6765349edfa7e03dc8d2ffe7bf6a45155f3ad0 | 69,805 |
import os
import logging
import re
def main(unused_argv):
"""Moves swig generated classes to a common container class.
The .csproj filename is used to find the .cs file (with the same name) which
will contain all of the other SWIG generated classes.
Args:
unused_argv: Extra arguments not consumed by the... | 063e3d2eaa77c4bd3e920e005bdbae6c76016661 | 69,806 |
def ReplaceValues(df, lY, iQ1, iQ2):
"""
Purpose:
Replace all values in dataframe below i1 by i1, and all values above i2 by i2.
Inputs:
lY list of names of relevant columns from df
df dataframe
i1 first value (lower boarder)
i2 second value ... | 30c1199f645e2b10ffb885d543783d513818f254 | 69,807 |
def peak_indices_to_times(time, picked_peaks):
"""
Converts peak indices to times.
Parameters
----------
time: ndarray
array of time, should match the indices.
picked_peaks: dict
dictionary containing list of indices of peak start, center, and end.
Returns
-----------
... | 99aa76fbc399b2b99d4dc9c8d3e4b67e4ee2d3af | 69,808 |
from typing import Optional
from typing import List
from typing import Any
from typing import Tuple
def _create_on_round_end_fn(
file_checkpoint_manager: Optional[FileCheckpointManager] = None,
metrics_managers: Optional[List[MetricsManager]] = None,
validation_fn: Optional[ValidationFnType] = None):
""... | 6f48db732bfb24e63cc49ce8935f3f44a7aca498 | 69,809 |
import pandas as pd
import os
def nsw74psid_a(path):
"""A Subset of the nsw74psid1 Data Set
The `nsw74psidA` data frame has 252 rows and 10 columns. See
`nsw74psid1` for more information.
This data frame contains the following columns:
trt
a numeric vector
age
a numeric vector
educ
... | 8c69590cf0b75eac5fc8f8faca4388df97c8e186 | 69,810 |
from typing import Tuple
import asyncio
async def read_govee() -> Tuple[float, float]:
"""Connects to the H5179 device and gets the lab temperature and humidity."""
h5179 = config["sensors"]["H5179"]
reader, writer = await asyncio.wait_for(
asyncio.open_connection(h5179["host"], h5179["port"]),
... | 3489957c1a68f00731c6924606c6d15faa15a613 | 69,811 |
def init_baseline_artm(
dataset,
modalities_to_use,
main_modality,
num_topics,
bcg_topics,
model_params: dict = None,
):
"""
Creates simple artm model with standard scores.
Parameters
----------
dataset : Dataset
modalities_to_use : list of str
... | 9aa0339316a75417e4afc756810a43d9a50a936b | 69,812 |
def es_annotation_doc():
"""
Minimal JSON document for an annotation as returned from Elasticsearch.
This contains only fields which can be assumed to exist on all annotations.
"""
return {
"_id": "annotation_id",
"_source": {
"authority": "hypothes.is",
"tar... | 085f8077d5f5cbf278a3b1be1734de081a55b769 | 69,813 |
def incmean(prevmean, n, x):
"""Calculate incremental mean"""
newmean = prevmean + int(round((x - prevmean) / n))
return newmean | 4176a07d0ad8eb96d3dd5d8b2cb46b8aecd1da20 | 69,814 |
def ccode(expr, dtype=np.float32, **settings):
"""Generate C++ code from an expression calling CodePrinter class
:param expr: The expression
:param settings: A dictionary of settings for code printing
:returns: The resulting code as a string. If it fails, then it returns the expr
"""
return Cod... | 1fdceb916a1e1c5536bf8794852d58b393f47aef | 69,815 |
import torch
def uses_placeholder_y(ds):
"""If ``ds`` is a ``skorch.dataset.Dataset`` or a
``skorch.dataset.Dataset`` nested inside a
``torch.utils.data.Subset`` and uses
y as a placeholder, return ``True``."""
if isinstance(ds, torch.utils.data.Subset):
return uses_placeholder_y(ds.datas... | 1bbdfdfa644db3298a6148380155980a57183d62 | 69,816 |
def evenFibSum(limit):
"""Sum even Fib numbers below 'limit'"""
sum = 0
a,b = 1,2
while b < limit:
if b % 2 == 0:
sum += b
a,b = b,a+b
return sum | cdf9cdb1cfb419713e794afff4d806945994692e | 69,817 |
def copy_arrays(mapper, reverse=False):
"""
Build an Iteration/Expression tree performing the copy ``k = v``, or
``v = k`` if reverse=True, for each (k, v) in mapper. (k, v) are expected
to be of type :class:`IndexedData`. The loop bounds are inferred from
the dimensions used in ``k``.
"""
i... | 44d346a751d8f92edb34729c9093d174ec55f499 | 69,818 |
def OneHotFromList(elements, dtype='float32', strict=True, name=None): # pylint: disable=invalid-name
"""A block that converts PyObject input to a one-hot encoding.
Differs from `OneHot` in that the user specifies the elements covered by the
one-hot encoding rather than assuming they are consecutive integers.
... | cde6231cc9701d450e6d7f5b44d630f08a657899 | 69,819 |
def _get_tfbt(output_dir, feature_cols):
"""Configures TF Boosted Trees estimator based on flags."""
learner_config = learner_pb2.LearnerConfig()
learner_config.learning_rate_tuner.fixed.learning_rate = FLAGS.learning_rate
learner_config.regularization.l1 = 0.0
# Set the regularization per instance in such a... | e5a548858850745087add9fb65bc233c880b3aa3 | 69,820 |
from datetime import datetime
def dateandtime_now() -> str:
"""
Returns the datetime in following format as string
YYYYMMDD_HHMMSS
"""
jetzt = datetime.datetime.now()
dt = ''
for time in ['year', 'month', 'day', 'hour', 'minute', 'second']:
_time = str(getattr(jetzt, time))
... | 700032adc66298f98fc6687c5dbf48fe4b0706c5 | 69,821 |
def get_n_first(file_names, checksums, N_first):
"""
Given a list of file_names and a list of checksums, returns the 'N_first'
items from both lists as a zip object.
:param file_names: list of file names
:param checksums: list of sha256 checksums
:param N_first: int or None. If None, all items ... | 13a8157dcd55fa43b0cd71eb877abddc832ff143 | 69,822 |
from typing import Tuple
def singular_value_decomposition(
m: np.ndarray
) -> Tuple[np.ndarray, np.ndarray, np.ndarray]:
"""Perform singular value decomposition.
:param m: an input matrix M.
:returns: a tuple (d, U, V), where d is a 1d matrix containing the diagonal elements of
a non-ne... | b9e469f3d42b1140fc4d3303d763954d8541c69a | 69,823 |
def get_library(gi, lib_name, lib_desc="", lib_synopsis="", create=True):
"""
Get the id corresponding to given library, and create it if it doesn't exist yet
"""
print("Looking for lib '" + lib_name + "'")
libs = gi.libraries.get_libraries()
found_lib = None
for lib in libs:
if not... | b8f9c6fff4c0162185fc71c08de9ff7b03272d4b | 69,824 |
def state_to_index(valuation, base):
"""
Maps states to an decimal integers.
"""
factor = 1
integer = 0
for i in range(len(valuation)):
integer += factor * valuation[i]
factor *= base
return integer | c05deefd07d0faf2749489fbc6f37576e1433c8d | 69,825 |
def check_index_values_are_unique(data, index=None, duplicates_as_error=True):
"""Checks index for duplicate rows.
Args:
data: DataFrame to check
index: optional index to use. If not specified, uses index from `data`.
duplicates_as_error: If True, raises an error if duplicates are found... | cf29309022e0303c0c49b716388b2cf73909f547 | 69,826 |
def extract_conversions(conversions_path, index_path, alignments=None, quality=27, n_threads=8):
"""Wrapper around `extract_conversions_part` that works in parallel.
:param conversions_path: path to conversions CSV
:type conversions_path: str
:param index_path: path to conversions index
:type index... | 503268fe61d6ae3bc4c2bb607b12781d00f09233 | 69,827 |
def bgr2luma(im):
"""Converts BGR image to grayscale Luma
:param im: np.ndarray BGR uint8
:returns nd.array GRAY uint8
"""
im_y, _, _ = cv.split(cv.cvtColor(im, cv.COLOR_BGR2YUV))
return im_y | 39f97822dea6170be74d60c357fc51f4160e1acd | 69,828 |
def get_lock_path_from_repo(git_repo):
"""
>>> app_module = {'git_repo': 'git@github.com:claranet/ghost.git'}
>>> get_lock_path_from_repo(app_module['git_repo'])
'/ghost/.mirrors/.locks/git@github.com:claranet/ghost.git'
>>> app_module = {'git_repo': ' git@github.com:claranet/spaces.git '}
>>> g... | b722e69dcaa5fd6a6299ee42ddaa7f14097a25a4 | 69,829 |
def cross_entropy_with_selfnorm(input,
label,
name=None,
coeff=1.0,
softmax_selfnorm_alpha=0.1,
layer_attr=None):
"""
A loss layer for multi class entro... | b8bda752dc9eaf1b69014481bd27be992fc4870b | 69,830 |
def random_contrast(img, low=0.5, high=1.5):
""" Randomly scales the contrast of a given RGB image. """
mean = img.mean(axis=(0,1), keepdims=True)
cf = np.random.uniform(low, high, mean.shape)
img -= mean
img *= cf
img += mean
img[img > 1] = 1
img[img < 0] = 0
return img | 7a3ae56c2bbf79dac312bfc176d021dc5bccc1cb | 69,831 |
import os
import json
import collections
from datetime import datetime
def load_file(filename):
"""raise EOFError als file niet gelezen kan worden
geeft geen resultaat als bestand niet bestaat
"""
if not os.path.exists(filename):
return {}
with open(filename, "r") as f_in:
nt_data ... | 9145ee9062ecc6bd1711e1ccc95548b17bc215fb | 69,832 |
def get_movie_or_create(movie: str):
"""
Находит фильм в бд или создает его, возвращает id фильма.
"""
try:
result = Movies.select().where(Movies.name==movie).get()
except DoesNotExist:
result = Movies.create(name=movie)
return result.id | c7581ec1421d7a487fc253f3a65c544f8a3f60c6 | 69,833 |
def generalized_box_iou(boxes1, boxes2):
"""Compute GIoU of each pais in boxes1 and boxes2
GIoU = IoU - |A_c - U| / |A_c|
where A_c is the smallest convex hull that encloses both boxes, U is the union of boxes
Details illustrations can be found in https://giou.stanford.edu/
Args:
boxes1: ... | 671520a3967b6120d23c8944456e13e3118ef8a7 | 69,834 |
def getConstValue(stateStruct, obj):
"""
Evaluates the obj, in case it is a expression which can be evaluated at compile time.
"""
if hasattr(obj, "getConstValue"): return obj.getConstValue(stateStruct)
if isinstance(obj, (CNumber,CStr,CChar)):
return obj.content
if isinstance(obj, CFunc... | 91c1ae469ef23b91ef4f76bf35481560243cdfc7 | 69,835 |
def prepare_vcf_table(varfile, sample, variants):
"""Prepare vcf table."""
header = [
"CHROM",
"POS",
"REF",
"ALT",
"AF",
"DP",
"DP4",
"GEN[0].AD",
"SB",
"FS",
"EFF[*].GENE",
"ID",
"EFF[*].AA",
]
head... | 396eb3966196352dbbbe0ff6c9386aba7fcc032b | 69,836 |
def counts_from_confusion(confusion):
"""
Obtain TP, FN FP, and TN for each class in the confusion matrix
"""
counts_list = []
# Iterate through classes and store the counts
for i in range(confusion.shape[0]):
tp = confusion[i, i]
fn_mask = np.zeros(confusion.shape)
fn... | 7c9b1f8309ef7a0304aa218e75f90d0c6a09bd66 | 69,837 |
def vaccination_view():
"""
App route to display India level vaccination data
:return:
"""
dates, cumulative_data, daily_data, fully_vaccinated, daily_fully_vaccinated, sources = service.vaccination_data()
context = {
'dates': dates.tolist(),
'cumulative_data': cumulative_data.to... | 0f4fb72c72abf31d65c2b541fc891d6c574c6252 | 69,838 |
def im_to_torch(img):
"""Transform ndarray image to torch tensor.
Parameters
----------
img: numpy.ndarray
An ndarray with shape: `(H, W, 3)`.
Returns
-------
torch.Tensor
A tensor with shape: `(3, H, W)`.
"""
img = np.transpose(img, (2, 0, 1)) # C*H*W
img = to_t... | fcda6a9e65d87b09ff5d1340dcf958fb1f14089e | 69,839 |
from typing import Sequence
from typing import Optional
def animate_atom_phonon(
position: Sequence[float],
qpt_cart: np.ndarray,
d_vector: np.ndarray,
n_frames: int = 30,
s_frame: int = 0,
e_frame: Optional[int] = None,
magnitude: float = 1.0,
):
"""Return atom position series determi... | 72cdb958f540bd16525ccb1a885f75e38b1482e7 | 69,840 |
def get_f1sc(y_true, y_pred, threshold = 0.5):
"""
- Description
y_true: should be one-hot encoded tensor
y_pred: should be logit tensor
threshold: thres to claim it is 1
- Reutrn
f1-score under threshold
"""
y_true = tf.argmax(y_true, axis = 1)
y_pred = y_pred[:,1] >= threshold
... | c21436263fcfa938ee70c2c90bf2ed4375edceec | 69,841 |
import os
import json
import requests
def init_api_client():
"""
Initialize Flask API Client
This is necessary for the grant code method
"""
log = Logger()
config = get_config()
app_name = config.get('application', 'name')
app = Flask('{0}_api_client'.format(app_name), template_folder... | 6cfd5d8604d2b40c8578b682994da3aea4658b15 | 69,842 |
def rules(supvisors):
""" Return the instance to test. """
return ProcessRules(supvisors) | 68fd580498e590a320cfb8ba25e177fdfbe7f512 | 69,843 |
def _parse_build(encoded_data, pointer=0, spec=None, spec_params=None, strict=False):
"""
Parses a byte string generically, or using a spec with optional params
:param encoded_data:
A byte string that contains BER-encoded data
:param pointer:
The index in the byte string to parse from
... | 3824e87b120b63cbbc18a140b8b2c0cca95d5405 | 69,844 |
def cache_basic_crud_update_row_view(request, id):
"""
Renders the Django edit form page and execute the update statement.
But, with invalidating the cache to clear the previous cached results.
"""
if request.method == "GET":
# Check if the row id existed or not.
if is_contact_us_id... | 83d90a5fe70715dd6e8e0aff8b342a193c77ac19 | 69,845 |
def interpolate_at_times(df_or_series, new_times) -> ndarray:
"""
Parameters
-----------
df_or_series: Pandas DataFrame or Series
new_times: iterable, numpy array
can be a n-d array, list.
"""
assert df_or_series.index.is_monotonic_increasing, "df_or_series must be a increasing ... | f9dd3dbb780331f40d38d505bceac609ed88df86 | 69,846 |
def PFullInstantiate (inOTF, access, err):
""" Fully instantiate an OTF by opening and closing
return 0 on success, else failure
inOTF = Python OTF object
access = access code 1=READONLY, 2=WRITEONLY, 3=READWRITE
err = Python Obit Error/message stack
"""
#######################... | fa5691292e27153afeebe6ef42fe91b974c2b933 | 69,847 |
from typing import Any
async def get_user_info_by_id_async(client: Any, user_id: str):
"""Gets profile information about a user by id."""
return (await make_call_async(client, "users.info", user=user_id))["user"] | 262dc6afa0f17a3f2debd0d05738b20441f4f2d9 | 69,848 |
def getStep(raw, config):
"""
Detect the type of the build step and generate a model from it
"""
if exists(raw, "partitiontable"):
ptable = partitiontable()
ptable.reference = raw["partitiontable"]
return ptable
if exists(raw, "format"):
form = format()
form.r... | 54518f813709b5b578cf87504343024a9306450c | 69,849 |
def _compute_background_amplitude(image_spot):
"""Compute amplitude of a spot and background minimum value.
Parameters
----------
image_spot : np.ndarray, np.uint
A 3-d image with detected spot and shape (z, y, x).
Returns
-------
psf_amplitude : float or int
Amplitude of t... | 84a5138d2757459f8e0a61c12222cb32fa24662d | 69,850 |
def strip_comments(string, comment_symbols=frozenset(('#', '//'))):
"""
:param string: A string containing json with comments started by comment_symbols.
:param comment_symbols: Iterable of symbols that start a line comment (default # or //).
:return: The string with the comments removed.
"""
lines = string.split... | 4dfc1b0e627d8559db61f00b10fa5cb807ba2d01 | 69,851 |
def return_user_best_video(username):
"""
In GET request
- Returns video ID of the video uploaded by the user with the highest view count.
"""
if request.method == 'GET':
return str(db.get_best_video_ID(username)) | 9751f36a0cd45c54ca38f4e2f19a6be43df8fed3 | 69,852 |
def get_unique_tasks(*task_groups):
"""
Compare input JSON objects containing tasks and return a unique set
:param json_objects: lists of task objects
:type json_objects: list
:rtype: list
"""
# Combine all sub-json objects into a single group
unique_tasks = []
# Get a list of ta... | c9eb32ea0a953e797ea28021c3a434941f7b05ff | 69,853 |
def get_srl16_init(site, srl):
"""
Decodes SRL16 INIT parameter. Returns two initialization strings, each one
for one of two SRL16s.
"""
lut_init = get_lut_init(site, srl)
bits = lut_init.replace("64'b", "")
assert bits[1::2] == bits[::2]
srl_init = bits[::2]
return "16'b{}".forma... | 651cef9d266fe2edd896f17018cda1455d2d54a8 | 69,854 |
def problema(n):
"""
Input
n - maxim number of digits that can produce this result
"""
suma = 0
b = {}
for i in product(range(10), repeat=n):
aux = reduce(lambda x, y: 10*x + y, i)
b[aux] = sum(map(lambda x: x**5, i))
if aux == b[aux]:
suma += aux
... | f6c5d0436b8d41f82c56c996f9e26fb53887abd8 | 69,855 |
import sys
def mergeRectify(input_frames, cameras, grid):
"""
This function performs image rectifications at one timestamp given
the associated extrinsics, intrinsics, and distorted images
corresponding to each camera contained within the CameraData object.
The function utilizes matchHist to match... | 14bb579fb81fb652a06deec20736b7c07a13f02f | 69,856 |
def news_detail(news_id):
"""
新闻详情
:param news_id:
:return:
"""
# 显示用户是否登录的逻辑
print('test')
user = g.user
print(user)
# 右侧新闻排行的逻辑
news_list = []
try:
news_list = News.query.order_by(News.clicks.desc()).limit(constants.CLICK_RANK_MAX_NEWS)
except Exception as e... | abf8f3d3542ca80eb0fbd907dfcc4cb7a668c4dd | 69,857 |
def directorio_imagen(instance, filename):
"""Obtiene el directorio para guardar las imagenes de los platillos"""
# Obtenemos la extension del archivo para guardar la imagen solo con el id y nombre del platillo
extension = filename.rsplit('.', 1)[1]
return f"platillo/imagen/{instance.id}_{instance.nomb... | 90db760562327a16858e1bf6419fb1ed6e9eeefa | 69,858 |
import json
def output_fn(prediction, accept):
"""Format prediction output
The default accept/content-type between containers for serial inference is JSON.
We also want to set the ContentType or mimetype as the same value as accept so the next
container can read the response payload correctly.
""... | 47ad5dcb528c8fbaca9b0de22f6745dd1c058da2 | 69,859 |
def stack_error_improvement_matrix(result_list, model_names, error='mae'):
"""Computes the stacked error improvement matrix, which for each element (i,j) contains the pairwise stacked error improvement of model_list i and j. Returns as pd.DataFrame.
Arguments:
result_list: a list of SPSbBandwidthOptimi... | 540d01a8764643ccec3db68fb8bd5a95ddb423ae | 69,860 |
from typing import Union
def gen_batch_vectors(
n_batches: int,
n_features: int,
batch_scale: float,
bio_batch_angle: Union[float, None] = None,
projection_to_bio: Union[np.ndarray, None] = None,
) -> np.ndarray:
"""Generates a batch-effect vector for each batch, optionally with some
relat... | 744ffced9013686b14a6c4100a24f8df81b70093 | 69,861 |
def main():
"""
Main procedure; accept the file name as a command-line parameter and run the solver.
"""
if len(sys.argv) < 2:
print 'Specify the file name corresponding to the Brick Pop screenshot as the first ' \
'positional argument.'
return sys.exit(1)
return solve... | 9db3fc1fd77a07e1a58c2eafe513edf357a08167 | 69,862 |
def is_multiple_folder(schema_map):
"""
Return True if the schema map identifies a multiple folder.
:param schema_map: the schema map to be examined
:return: True if the map identifies a multiple folder
"""
property_type = get_type(schema_map)
if property_type == "array":
return get_... | c18d6a7557e458998a4d2c008f7b1f3b74fff2c7 | 69,863 |
def cicle_move(A):
"""
move first to last and move elements between first and last 1 element back
:param A: list to execute cicle move
:return:
"""
tmp = A[0]
for i in range(len(A) - 1):
A[i] = A[i + 1]
A[len(A) - 1] = tmp
return A | 4948b863829d77a879ad0ec9745bb3a35e580026 | 69,864 |
import torch
def test_is_index_valid() -> None:
"""
Test if checks for valid sequence positions work.
"""
def _create(pos: int) -> ScalarDataSource:
z = torch.empty(0)
return ScalarDataSource(metadata=GeneralSampleMetadata(id="", sequence_position=pos),
... | cb3210c2fd59ceb013b8bc909fa9f08cf03e1af1 | 69,865 |
def load_keras_model(dataset, model_name):
"""
Loads pretrained model from disk for a given dataset type.
"""
folder_path = '../Models/'
model_path = folder_path + dataset + '/' + model_name + '_model.json'
try:
json_file = open(model_path, 'r')
except IOError:
print('\nE... | 70f2670d414466a675646e6689dff7ac4f609c08 | 69,866 |
def _is_float_or_nan(val):
"""Check whether a given item is a float or np.nan"""
try:
float(val)
except ValueError:
if val is np.nan:
return True
return False
else:
if not isinstance(val, bool):
return True
else:
return False | 9eadced4492fd052173b4a6d953df7862df2c370 | 69,867 |
import collections
def resize(img, size, interpolation=Image.BILINEAR):
"""Resize the input PIL.Image to the given size.
Args:
img (PIL.Image): Image to be resized.
size (sequence or int): Desired output size. If size is a sequence like
(h, w), the output size will be matched to th... | 829bbdeea7cb99dbc2f935330b5180319e17da9e | 69,868 |
from operator import concat
def scriptGen(step, config):
"""
Generate a script command from a parser.executor.script
"""
if not step.model.command == None:
return concat(["\n# Executing custom script"], script.script(shell="", payload=step.model.command).exec())
with open(step.model.file, ... | bc1bd50e05c8514d32483d3c5aaf9951494d15f6 | 69,869 |
def read_binary_file(bf: str):
"""
to read binary file
:param bf:
:type bf:
:return:
:rtype:
"""
# example: f'./local_data/MSG+0415.3km.lon'
data = np.fromfile(bf, '<f4') # little-endian float32
# data = np.fromfile(bf, '>f4') # big-endian float32
return data | 4ecf7fb3098339b5ea0e77e738bb59f863cf641c | 69,870 |
def get_bounding_boxes(start_path = '.'):
""" Extracts a bounding box file and returns a dictionary
"""
return GetBoundingBoxes(start_path).unpack_all() | a0d80d6d6a77555e4bdbecaf7bd52e8403270965 | 69,871 |
def get_VAE_os(X):
"""
takes in only data 'X', in samples as rows format
returns only list of outlier scores for each sample
higher score = more outlier
gives reconstruciton error from AE, should be largest for outliers
"""
losses = get_vae_losses(X)
return losses | 1c1a078409b29d2e7306b72ddbe670f56cf9f538 | 69,872 |
def get_activation_gradients(label):
"""Gets the sample gradient w.r.t activation according to the model_fn."""
# The sample loss is (label - logits)**2, where
# logits = \sum_j^HIDDEN_LAYER_SIZE (
# \sum_i^EMBEDDING_DIM w_i * kernel + bias)
#
# Note kernel and bias are both constant initializer... | 6714795be6893106ecbfacecd368854b377ae75c | 69,873 |
import os
def get_scene_path(scene_id):
"""
Gibson scene path
:param scene_id: scene id
:return: scene path for this scene_id
"""
data_path = gibson2.g_dataset_path
assert scene_id in os.listdir(
data_path) or scene_id == 'stadium', "Scene {} does not exist".format(scene_id)
r... | 3bdb59e61441930f75c266d8d5c60c44c75fe47b | 69,874 |
import gzip
import tqdm
import json
def read_examples(input_file):
"""Read a SQuAD-like json file into a list of Examples."""
def is_whitespace(c):
if c == " " or c == "\t" or c == "\r" or c == "\n" or ord(c) == 0x202F:
return True
return False
reader = tf.gfile.Open(input_file, "rb")
if input... | f0ea238c4313ec6a0779452014c7875feeefbb4e | 69,875 |
def make_options(
testcase_id='1',
current=False,
build='chromium',
disable_goma=False,
goma_threads=10,
goma_load=8,
iterations=11,
disable_xvfb=False,
target_args=None,
edit_mode=False,
skip_deps=False,
enable_debug=False,
extra_log_params=None,
force=False):
... | 79ca25f9ea7fc4266ecc4dc76f73e7f620408096 | 69,876 |
async def record(request):
"""Renders the video recording and upload view."""
return templates.TemplateResponse("record.html", {"request": request}) | fa3d6633a68f9cf1f01aab8d45b3198024a4d219 | 69,877 |
import ctypes
import readline
def rl_get_point() -> int: # pragma: no cover
"""
Returns the offset of the current cursor position in rl_line_buffer
"""
if rl_type == RlType.GNU:
return ctypes.c_int.in_dll(readline_lib, "rl_point").value
elif rl_type == RlType.PYREADLINE:
return i... | 257dd29b23869b6e6245773f86e64ef58f9e763b | 69,878 |
def plot_averages(
fig: go.Figure,
data: pd.DataFrame,
value_col: str,
aggregate: dict,
color: str,
line_shape: str = "spline",
color_discrete_sequence: list = px.colors.qualitative.G10,
category_orders: dict = default_category_orders(),
mode: str = "polar",
):
"""Add traces for ... | b3f99ee216fc8375ea071ca7483c9c003fe38bff | 69,879 |
import typing
def rating(apikey: str, symbol: str) -> typing.List[typing.Dict]:
"""
Query FMP /rating/ API.
:param apikey: Your API key.
:param symbol: Company ticker.
:return: A list of dictionaries.
"""
path = f"rating/{symbol}"
query_vars = {"apikey": apikey}
return __return_js... | fddc609276e0f63e2f6523337c47a95c9f651a94 | 69,880 |
import tokenize
def tokenize_code(text):
"""Tokenize code strings.
This simply considers whitespaces as token delimiters.
Args:
text: A code string to be tokenized.
Returns:
A list of strings representing the tokens in the code.
"""
return tokenize.RegexpTokenizer(r'\w+').tokenize(text) | 692eec16363f4d6816482025942aac7e149f3910 | 69,881 |
def getScriptClass(scriptVersion, script):
"""
getScriptClass returns the class of the script from the known standard
types. NonStandardTy will be returned when the script does not parse.
NOTE: All scripts that are not version 0 are currently considered
non standard.
"""
if scriptVersion !... | ead86ca55a820bf0f93aa31f70c74c733a61f253 | 69,882 |
import sys
import subprocess
import string
import MySQLdb
import reportlab
import xlwt
import os
from re import T
def about():
"""
The About page provides details on the software
depedencies and versions available to this instance
of Sahana Eden.
"""
python_version = sys.version
web2py_ver... | 592243b25ec429d5247d44e0cf8487fbcaa180a5 | 69,883 |
def print_compare(x, y):
"""
Helper method used in
:meth:`Sets.ParentMethods._test_elements_eq_symmetric`,
:meth:`Sets.ParentMethods._test_elements_eq_tranisitive`.
INPUT:
- ``x`` -- an element
- ``y`` -- an element
EXAMPLES::
sage: from sage.categories.sets_cat import print... | 7a591b52fb20bc2bf0ec8ea029e4f10b3e1fee26 | 69,884 |
def Words_Before_and_after(words, item, nbr):
"""
:param words: list of words
:param item: word of interest
:param nbr: number of words wanted before and after the word of interest
:return: list of words before and after the word of interest
"""
liste = [[words[item], item]]
for n in ran... | 6dc874565a308cc642bf0510a3be56264c6d89e9 | 69,885 |
async def get_mocked_redis_client(*args, **kwargs) -> RedisCluster:
"""
Return a stable RedisCluster object that have deterministic
nodes and slots setup to remove the problem of different IP addresses
on different installations and machines.
"""
cluster_slots = kwargs.pop("cluster_slots", defau... | 5fb6e3b70971a27ceaef2676741b2a36f4168039 | 69,886 |
import yaml
def df_to_yaml(df):
""" conert DataFrame to yaml string """
d = df.to_dict(orient='records')
return yaml.dump(d) | 285b4cad92e73fbaec19e631664bb474ecaf309f | 69,887 |
import sys
import os
import importlib
def get_detector(net, prefix, epoch, data_shape, mean_pixels, ctx,
nms_thresh=0.5, force_nms=True):
"""
wrapper for initialize a detector
Parameters:
----------
net : str
test network name
prefix : str
load model prefix
... | bd5609cb4bb42379702ccfe365da1eaac97fbe83 | 69,888 |
from datetime import datetime
def naturaltime(text, now=None):
"""Convert a naturaltime string to a datetime object."""
text = text.lower().strip()
if not now:
now = datetime.now()
if text == 'now':
return now
if text == 'yesterday':
return now - timedelta(days=1)
if t... | 25f56b5afd11cd5e4b6dd4a94a1de3c47476bd1e | 69,889 |
def get_polar(d, Re=6371.):
""" Convert to polar coordinates """
th = d.grange / Re
r = d.height + Re
dop, sth, dth = d.dop, d.sth, d.dth
return th, r, dop, sth, dth | 1d4710152b5dbbbfd09cdc5cbf934f3adb94deeb | 69,890 |
def _corr_vectors(A, B, axis=0):
"""Compute pairwise correlation of multiple pairs of vectors.
Fast way to compute correlation of multiple pairs of vectors without
computing all pairs as would with corr(A,B). Borrowed from Oli at Stack
overflow. Note the resulting coefficients vary slightly from the on... | 51df38f9e1703c98718d3f15b481975ce82f47a2 | 69,891 |
def getGenomesInHal(halFile):
"""Get a set of all genomes in the hal file."""
spaceSeparatedGenomes = popenCatch("halStats --genomes %s" % halFile).strip()
return set(spaceSeparatedGenomes.split(" ")) | fad81779e8a8e8788117099d96526083e8d635b1 | 69,892 |
def diagflat(d, k=0):
"""
Create a two-dimensional array with the flattened input as a diagonal.
Parameters
----------
d : array_like
Input data, which is flattened and set as the `k`-th
diagonal of the output.
k : int, optional
Diagonal to set; 0, the default, correspon... | 6dbf5f72eda5771bd0a7080a353de69a65ebeca3 | 69,893 |
import re
def hasNoProcessExtension(file_name: str):
""" Determine if the file should not be processed, just copied directly """
m = re.search(r'(?<=\.)[^.]+', file_name)
return m.group() in CONFIG['ignoredExtensions'] if m else False | cc67d7e8633454a852f87a7a41aa7d85624cbf21 | 69,894 |
def get_patchy_N0s(qekey_in, npatches, pixivmap_t, pixivmap_p, cls_unl, cls_cmb_dat, cls_cmb_filt, cls_weight, lmin_ivf, lmax_ivf, lmax_qlm, transf,
rvmap_uKamin_t_data=None, rvmap_uKamin_p_data=None, joint_TP=False,
nlevt_fid=None, nlevp_fid=None, cacher=cachers.cacher_mem(), source... | 3e504133ea53409bff3475468843dbf3ae183b87 | 69,895 |
def generate_sphere(radius):
"""Generates a centered boolean mask of a 3D sphere"""
rint = np.ceil(radius).astype('int')
t = np.arange(-rint, rint+1, 1)
x,y,z = np.meshgrid(t, t, t, indexing='ij')
r = np.sqrt(x*x + y*y + z*z)
sphere = r < radius
return sphere | 56b3e45397464701ecd472e90ffc863785646200 | 69,896 |
def find_percentile_coordinate(cube: Cube) -> Coord:
"""Find percentile coord in cube.
Args:
cube:
Cube contain one or more percentiles.
Returns:
Percentile coordinate.
Raises:
TypeError: If cube is not of type iris.cube.Cube.
CoordinateNotFoundError: If no... | 718f4ef482a317784c46c397bf68e8630631e857 | 69,897 |
def get_user_plants(user_id):
"""Returns a list of plants a user has added."""
user_plants = User.query.get(user_id).plants
unpacked_user_plants = {}
for plant in user_plants:
unpacked_user_plants[plant.plant_id] = plant.__dict__
if '_sa_instance_state' in unpacked_user_plants[plant.p... | f2fdd16bc535eab5fcfe28d65f2ebe74dfaeceb5 | 69,898 |
import six
import sh
def apply_sh(actions):
"""Add the shell function to any actions that are strings"""
return [ a if six.callable(a) else sh(a, log_command=False) for a in actions ] | dd2d24fccb0e8d02752a3f5bd86bc0b41161b87d | 69,899 |
Subsets and Splits
No community queries yet
The top public SQL queries from the community will appear here once available.