uid stringlengths 24 24 | split stringclasses 1
value | category stringclasses 2
values | content stringlengths 5 482k | signature stringlengths 1 14k | suffix stringlengths 1 482k | prefix stringlengths 9 14k | prefix_token_count int64 3 5.01k | prefix_token_budget int64 64 256 | element_token_count int64 1 292k | signature_token_count int64 1 5.01k | prefix_context_token_count int64 0 255 | repo stringlengths 7 112 | path stringlengths 4 208 | language stringclasses 1
value | name stringlengths 1 218 | qualname stringlengths 1 218 | start_line int64 1 26.7k | end_line int64 1 26.7k | signature_start_line int64 1 26.7k | signature_end_line int64 1 26.7k | source_hash stringlengths 40 40 | source_dataset stringclasses 1
value | source_split stringclasses 1
value |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
373cc79e198cb302d06dbf14 | train | class | class UnprocessedParamType(ParamType):
name = "text"
def convert(self, value, param, ctx):
return value
def __repr__(self):
return "UNPROCESSED"
| class UnprocessedParamType(ParamType):
| name = "text"
def convert(self, value, param, ctx):
return value
def __repr__(self):
return "UNPROCESSED"
| , param, ctx):
try:
return self.func(value)
except ValueError:
try:
value = str(value)
except UnicodeError:
value = value.decode("utf-8", "replace")
self.fail(value, param, ctx)
class UnprocessedParamType(ParamType):
| 64 | 64 | 45 | 9 | 55 | click-contrib/asyncclick | src/click/types.py | Python | UnprocessedParamType | UnprocessedParamType | 156 | 163 | 156 | 156 | b57281ee7aa6833ba5a719c867290c5b458562c3 | bigcode/the-stack | train |
4646b1fd20752b8c993d6b40 | train | class | class Path(ParamType):
"""The path type is similar to the :class:`File` type but it performs
different checks. First of all, instead of returning an open file
handle it returns just the filename. Secondly, it can perform various
basic checks about what the file or directory should be.
.. versionc... | class Path(ParamType):
| """The path type is similar to the :class:`File` type but it performs
different checks. First of all, instead of returning an open file
handle it returns just the filename. Secondly, it can perform various
basic checks about what the file or directory should be.
.. versionchanged:: 6.0
`al... | automatically close the file
# at the end of the context execution (or flush out). If a
# context does not exist, it's the caller's responsibility to
# properly close the file. This for instance happens when the
# type is used with prompts.
if ctx is not No... | 255 | 256 | 1,134 | 6 | 249 | click-contrib/asyncclick | src/click/types.py | Python | Path | Path | 645 | 789 | 645 | 645 | 9efe0762d672fd8c316e0aa62b9b2703e3d9bc58 | bigcode/the-stack | train |
490994060fead851670d5633 | train | class | class ParamType:
"""Represents the type of a parameter. Validates and converts values
from the command line or Python into the correct type.
To implement a custom type, subclass and implement at least the
following:
- The :attr:`name` class attribute must be set.
- Calling an instance of t... | class ParamType:
| """Represents the type of a parameter. Validates and converts values
from the command line or Python into the correct type.
To implement a custom type, subclass and implement at least the
following:
- The :attr:`name` class attribute must be set.
- Calling an instance of the type with ``No... | import os
import stat
from datetime import datetime
from ._compat import _get_argv_encoding
from ._compat import filename_to_ui
from ._compat import get_filesystem_encoding
from ._compat import get_strerror
from ._compat import open_stream
from .exceptions import BadParameter
from .utils import LazyFile
from .utils im... | 84 | 256 | 936 | 4 | 79 | click-contrib/asyncclick | src/click/types.py | Python | ParamType | ParamType | 15 | 123 | 15 | 15 | 9d7aa194bc716b155ca0f1fbca5ba9034782ed69 | bigcode/the-stack | train |
1b999a827da493521d2c7c74 | train | class | class _NumberRangeBase(_NumberParamTypeBase):
def __init__(self, min=None, max=None, min_open=False, max_open=False, clamp=False):
self.min = min
self.max = max
self.min_open = min_open
self.max_open = max_open
self.clamp = clamp
async def to_info_dict(self):
inf... | class _NumberRangeBase(_NumberParamTypeBase):
| def __init__(self, min=None, max=None, min_open=False, max_open=False, clamp=False):
self.min = min
self.max = max
self.min_open = min_open
self.max_open = max_open
self.clamp = clamp
async def to_info_dict(self):
info_dict = await super().to_info_dict()
... | None:
return converted
plural = "s" if len(self.formats) > 1 else ""
formats_str = ", ".join(repr(f) for f in self.formats)
self.fail(
f"{value!r} does not match the format{plural} {formats_str}.", param, ctx
)
def __repr__(self):
return "DateTi... | 161 | 161 | 538 | 11 | 150 | click-contrib/asyncclick | src/click/types.py | Python | _NumberRangeBase | _NumberRangeBase | 357 | 425 | 357 | 357 | abc60ca77853d3e7e75b93761df963684b05a55d | bigcode/the-stack | train |
4934f5b2c83c4bfb74bacd32 | train | function | def convert_type(ty, default=None):
"""Find the most appropriate :class:`ParamType` for the given Python
type. If the type isn't provided, it can be inferred from a default
value.
"""
guessed_type = False
if ty is None and default is not None:
if isinstance(default, (tuple, list)):
... | def convert_type(ty, default=None):
| """Find the most appropriate :class:`ParamType` for the given Python
type. If the type isn't provided, it can be inferred from a default
value.
"""
guessed_type = False
if ty is None and default is not None:
if isinstance(default, (tuple, list)):
# If the default is empty, t... | return f"<{' '.join(ty.name for ty in self.types)}>"
@property
def arity(self):
return len(self.types)
def convert(self, value, param, ctx):
if len(value) != len(self.types):
raise TypeError(
"It would appear that nargs is set to conflict with the"
... | 113 | 113 | 378 | 9 | 104 | click-contrib/asyncclick | src/click/types.py | Python | convert_type | convert_type | 831 | 891 | 831 | 831 | f729f2a1d217f968c455ef37fd03761284a1373a | bigcode/the-stack | train |
aa6d43ca9ad6bc6dc66c04aa | train | class | class File(ParamType):
"""Declares a parameter to be a file for reading or writing. The file
is automatically closed once the context tears down (after the command
finished working).
Files can be opened for reading or writing. The special value ``-``
indicates stdin or stdout depending on the mod... | class File(ParamType):
| """Declares a parameter to be a file for reading or writing. The file
is automatically closed once the context tears down (after the command
finished working).
Files can be opened for reading or writing. The special value ``-``
indicates stdin or stdout depending on the mode.
By default, the... | if needed.
raise RuntimeError("Clamping is not supported for open bounds.")
class BoolParamType(ParamType):
name = "boolean"
def convert(self, value, param, ctx):
if value in {False, True}:
return bool(value)
norm = value.strip().lower()
if norm in {"1", "true",... | 249 | 249 | 832 | 6 | 243 | click-contrib/asyncclick | src/click/types.py | Python | File | File | 545 | 642 | 545 | 545 | e7b21c60a6600a5107977344b075702b0aaeea93 | bigcode/the-stack | train |
5404d53a87cb9073e234eb72 | train | class | class OASELogID:
Ary = {}
# LOSE
Ary['LOSE00000'] = "Failed to get OASE_T_MAIL_ACTION_HISTORY table. (action_his_id: {}, Traceback: {})"
Ary['LOSE00001'] = "Failed to get OASE_T_ITA_ACTION_HISTORY table. (action_his_id: {}, Traceback: {})"
Ary['LOSE00002'] = "Error has occurred. {}"
Ary['LOSE01000']... | class OASELogID:
| Ary = {}
# LOSE
Ary['LOSE00000'] = "Failed to get OASE_T_MAIL_ACTION_HISTORY table. (action_his_id: {}, Traceback: {})"
Ary['LOSE00001'] = "Failed to get OASE_T_ITA_ACTION_HISTORY table. (action_his_id: {}, Traceback: {})"
Ary['LOSE00002'] = "Error has occurred. {}"
Ary['LOSE01000'] = "RestAPI acces... | # Copyright 2019 NEC Corporation
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writi... | 147 | 256 | 18,078 | 6 | 141 | wreathvine/oase | oase-root/libs/messages/oase_logid.py | Python | OASELogID | OASELogID | 21 | 838 | 21 | 21 | a898a17c5a0ae4f1fa88258691c5873e6645865c | bigcode/the-stack | train |
343880e998c40675cd3015ee | train | class | class DayOfWeekField(BaseField):
REAL = False
COMPILERS = BaseField.COMPILERS + [WeekdayRangeExpression]
def get_value(self, dateval):
return dateval.weekday()
| class DayOfWeekField(BaseField):
| REAL = False
COMPILERS = BaseField.COMPILERS + [WeekdayRangeExpression]
def get_value(self, dateval):
return dateval.weekday()
| ]
class DayOfMonthField(BaseField):
COMPILERS = BaseField.COMPILERS + [WeekdayPositionExpression,
LastDayOfMonthExpression]
def get_max(self, dateval):
return monthrange(dateval.year, dateval.month)[1]
class DayOfWeekField(BaseField):
| 64 | 64 | 46 | 8 | 56 | hephaestus9/Ironworks | lib/apscheduler/triggers/cron/fields.py | Python | DayOfWeekField | DayOfWeekField | 95 | 100 | 95 | 95 | d6034b2888c766e3c3f04ebc087d91b1cf6f51fc | bigcode/the-stack | train |
2ee2d92fc7c873c09c13cf8b | train | class | class WeekField(BaseField):
REAL = False
def get_value(self, dateval):
return dateval.isocalendar()[1]
| class WeekField(BaseField):
| REAL = False
def get_value(self, dateval):
return dateval.isocalendar()[1]
| __(self):
expr_strings = (str(e) for e in self.expressions)
return ','.join(expr_strings)
def __repr__(self):
return "%s('%s', '%s')" % (self.__class__.__name__, self.name,
str(self))
class WeekField(BaseField):
| 64 | 64 | 30 | 6 | 58 | hephaestus9/Ironworks | lib/apscheduler/triggers/cron/fields.py | Python | WeekField | WeekField | 80 | 84 | 80 | 80 | 48e6888faf2b0bc9eea5db0d3ef680b040cd3f0d | bigcode/the-stack | train |
e4fdb62f05d87f84c290c92e | train | class | class DayOfMonthField(BaseField):
COMPILERS = BaseField.COMPILERS + [WeekdayPositionExpression,
LastDayOfMonthExpression]
def get_max(self, dateval):
return monthrange(dateval.year, dateval.month)[1]
| class DayOfMonthField(BaseField):
| COMPILERS = BaseField.COMPILERS + [WeekdayPositionExpression,
LastDayOfMonthExpression]
def get_max(self, dateval):
return monthrange(dateval.year, dateval.month)[1]
| ):
return "%s('%s', '%s')" % (self.__class__.__name__, self.name,
str(self))
class WeekField(BaseField):
REAL = False
def get_value(self, dateval):
return dateval.isocalendar()[1]
class DayOfMonthField(BaseField):
| 64 | 64 | 55 | 8 | 56 | hephaestus9/Ironworks | lib/apscheduler/triggers/cron/fields.py | Python | DayOfMonthField | DayOfMonthField | 87 | 92 | 87 | 87 | 419cdb72187c00ad598e4136c9a132a196035f0f | bigcode/the-stack | train |
d5d9a84ab717fc4ccfc0c681 | train | class | class BaseField(object):
REAL = True
COMPILERS = [AllExpression, RangeExpression]
def __init__(self, name, exprs, is_default=False):
self.name = name
self.is_default = is_default
self.compile_expressions(exprs)
def get_min(self, dateval):
return MIN_VALUES[self.name]
... | class BaseField(object):
| REAL = True
COMPILERS = [AllExpression, RangeExpression]
def __init__(self, name, exprs, is_default=False):
self.name = name
self.is_default = is_default
self.compile_expressions(exprs)
def get_min(self, dateval):
return MIN_VALUES[self.name]
def get_max(self, date... | _VALUES = {'year': 2 ** 63, 'month': 12, 'day:': 31, 'week': 53,
'day_of_week': 6, 'hour': 23, 'minute': 59, 'second': 59}
DEFAULT_VALUES = {'year': '*', 'month': 1, 'day': 1, 'week': '*',
'day_of_week': '*', 'hour': 0, 'minute': 0, 'second': 0}
class BaseField(object):
| 113 | 113 | 378 | 5 | 108 | hephaestus9/Ironworks | lib/apscheduler/triggers/cron/fields.py | Python | BaseField | BaseField | 22 | 77 | 22 | 22 | f983124c8e0e941d6f40906bba1b8a0ddcc8f470 | bigcode/the-stack | train |
0db82194372dbcc443aa74af | train | class | class AccountRoutes:
class AccountView(StrictSchemaView):
tags = ["Account"]
class AccountInfo(AccountView):
summary = "Get an account info"
parameters = []
responses = {
HTTPStatus.OK: response_definition(
"Account information", schema=AccountInfoSch... | class AccountRoutes:
| class AccountView(StrictSchemaView):
tags = ["Account"]
class AccountInfo(AccountView):
summary = "Get an account info"
parameters = []
responses = {
HTTPStatus.OK: response_definition(
"Account information", schema=AccountInfoSchema
),
... | # pyre-ignore-all-errors
# Copyright (c) The Diem Core Contributors
# SPDX-License-Identifier: Apache-2.0
from http import HTTPStatus
from typing import Dict
from flask import request, Blueprint
import context
from diem import identifier, utils
from diem_utils.types.currencies import DiemCurrency
from wallet.servic... | 241 | 256 | 1,856 | 4 | 237 | tanshuai/reference-wallet | backend/webapp/routes/account.py | Python | AccountRoutes | AccountRoutes | 41 | 339 | 41 | 41 | 064cd2f3ab0bd0d05ecc16a1d2565dd52f72542a | bigcode/the-stack | train |
8cbe7c32232d462805be12a0 | train | function | def getsize(hi,ker,srd):
pad = np.asarray((0,0))
dil = np.asarray((1,1))
new_size = np.asarray(hi)
ker = np.asarray(ker)
srd = np.asarray(srd)
return(tuple((np.squeeze(\
(new_size+2*pad-dil*[ker-1]-1)/srd+1\
)).astype(int)))
| def getsize(hi,ker,srd):
| pad = np.asarray((0,0))
dil = np.asarray((1,1))
new_size = np.asarray(hi)
ker = np.asarray(ker)
srd = np.asarray(srd)
return(tuple((np.squeeze(\
(new_size+2*pad-dil*[ker-1]-1)/srd+1\
)).astype(int)))
| import torch
import torch.nn as nn
import torch.nn.functional as F
import numpy as np
def getsize(hi,ker,srd):
| 31 | 64 | 92 | 10 | 20 | cherepas/circles_public | plot_output/e075/e075l007/cnet.py | Python | getsize | getsize | 5 | 13 | 5 | 5 | 1e51fd827958899ac4d55b1e8083a87f49622608 | bigcode/the-stack | train |
ad9dd2163f404ce7cf961bbb | train | class | class CNet(torch.nn.Module):
#network from Henderson, Ferrari article
def __init__(self, hidden_dim, chidden_dim,
kernel_sizes, cnum, h, w, usehaf):
# , lb, ro, C, angles_list,
super(CNet, self).__init__()
# (h, w) = (h, w)
# print('h, w=, ',h, w)
self.use... | class CNet(torch.nn.Module):
#network from Henderson, Ferrari article
| def __init__(self, hidden_dim, chidden_dim,
kernel_sizes, cnum, h, w, usehaf):
# , lb, ro, C, angles_list,
super(CNet, self).__init__()
# (h, w) = (h, w)
# print('h, w=, ',h, w)
self.usehaf = usehaf
if usehaf:
self.conv0 = nn.Conv2d(cnum, 3... | import torch
import torch.nn as nn
import torch.nn.functional as F
import numpy as np
def getsize(hi,ker,srd):
pad = np.asarray((0,0))
dil = np.asarray((1,1))
new_size = np.asarray(hi)
ker = np.asarray(ker)
srd = np.asarray(srd)
return(tuple((np.squeeze(\
(new_size+2*pad-dil*[ker-1]-1)/s... | 129 | 256 | 1,099 | 16 | 113 | cherepas/circles_public | plot_output/e075/e075l007/cnet.py | Python | CNet | CNet | 14 | 107 | 14 | 15 | 2a9eba5f2b4b862e994df99887b145627d8b106a | bigcode/the-stack | train |
8e3e91e7b85cf910fe23113b | train | function | def dbugp(s):
if _debug:
print(col.WHT+"["+col.BLK+"debug"+col.WHT+"] "+col.BLN+str(s))
| def dbugp(s):
| if _debug:
print(col.WHT+"["+col.BLK+"debug"+col.WHT+"] "+col.BLN+str(s))
| .BLN+str(s))
def logfp(s,logf=None):
print(col.WHT+"["+col.MGN+" log"+col.WHT+"] "+col.BLN+str(s))
if logf is not None: logf.write(str(s)+"\n")
def dbugp(s):
| 64 | 64 | 36 | 6 | 58 | pcrain/review-reappropriator | common.py | Python | dbugp | dbugp | 67 | 69 | 67 | 67 | bbfe06c68b863d587ca89056c0c0b08e896a0831 | bigcode/the-stack | train |
6559374dc6b8567db41ad3ea | train | function | def timeit(method):
def timed(*args, **kw):
start = timer()
result = method(*args, **kw)
end = timer()
dbugp(" Took {} seconds".format(end-start))
return result
return timed
| def timeit(method):
| def timed(*args, **kw):
start = timer()
result = method(*args, **kw)
end = timer()
dbugp(" Took {} seconds".format(end-start))
return result
return timed
| ["+col.CYN+" recv"+col.WHT+"] "+s+col.BLN)
def passp(s):
return getpass(col.WHT+"["+col.BLU+"paswd"+col.WHT+"] "+str(s)+col.BLN)
#Timer decorator for method execution time
def timeit(method):
| 64 | 64 | 56 | 5 | 58 | pcrain/review-reappropriator | common.py | Python | timeit | timeit | 85 | 92 | 85 | 85 | f3e3d28241ccb6bd3c11a774086103ecd253e594 | bigcode/the-stack | train |
72e44fa98fd0d08385793de5 | train | function | def findNgramInSortedList(item,sortedlist):
ipoint = sortedlist.bisect_left([item,[DEFAULTTUPLE]])
return None if (ipoint == len(sortedlist) or (sortedlist[ipoint][0] != item)) else ipoint
| def findNgramInSortedList(item,sortedlist):
| ipoint = sortedlist.bisect_left([item,[DEFAULTTUPLE]])
return None if (ipoint == len(sortedlist) or (sortedlist[ipoint][0] != item)) else ipoint
| tokenlist:
if not RE_WORD.search(token[0]):
continue
if token[1] in STOPWORDS: #Check if lemmatized version is in stopwords
continue
validtokens.append(token)
return validtokens
def findNgramInSortedList(item,sortedlist):
| 64 | 64 | 58 | 12 | 51 | pcrain/review-reappropriator | common.py | Python | findNgramInSortedList | findNgramInSortedList | 239 | 241 | 239 | 239 | fea28e4d32cc1c4f277f2b597f81f0ab5b17671f | bigcode/the-stack | train |
d16dfb214405934e1154bed5 | train | class | class MySocket:
def __init__(self, sock=None):
if sock is None: self.sock = socket.socket(socket.AF_INET, socket.SOCK_STREAM)
else: self.sock = sock
def setsockopt(self,a,b,c):
self.sock.setsockopt(a,b,c)
def bind(self,hostport):
self.sock.bind(hostport)
def connect(self, host, por... | class MySocket:
| def __init__(self, sock=None):
if sock is None: self.sock = socket.socket(socket.AF_INET, socket.SOCK_STREAM)
else: self.sock = sock
def setsockopt(self,a,b,c):
self.sock.setsockopt(a,b,c)
def bind(self,hostport):
self.sock.bind(hostport)
def connect(self, host, port):
self.soc... | # self.nlp = spacy.load('en_core_web_sm')
def processText(self,text):
structure = {}
structure["text"] = text
structure["_md5"] = md5(text)
structure.update(nlpPreprocess(self.nlp,text))
structure["ideaunits"] = getIdeaUnits(structure)
structure["unigrams"] = []
structure["bi... | 199 | 199 | 664 | 4 | 194 | pcrain/review-reappropriator | common.py | Python | MySocket | MySocket | 284 | 376 | 284 | 284 | 3604c94003084b75bdce72d6d6e265225b712e4c | bigcode/the-stack | train |
12297b4d7c0ba58e81b45485 | train | function | def warnp(s):
print(col.WHT+"["+col.YLW+" warn"+col.WHT+"] "+col.BLN+str(s))
| def warnp(s):
| print(col.WHT+"["+col.YLW+" warn"+col.WHT+"] "+col.BLN+str(s))
| (col.WHT+"["+col.BLK+"debug"+col.WHT+"] "+col.BLN+str(s))
def simup(s):
if _simulate:
print(col.WHT+"["+col.CYN+"simul"+col.WHT+"] "+col.BLN+str(s))
def warnp(s):
| 64 | 64 | 30 | 5 | 59 | pcrain/review-reappropriator | common.py | Python | warnp | warnp | 73 | 74 | 73 | 73 | 01ebc8223b6528baf6f011ec6bc66642961d482a | bigcode/the-stack | train |
3dd4c6eb6d085ff8d63b39f8 | train | function | def sendp(s):
print(col.WHT+"["+col.CYN+" send"+col.WHT+"] "+s+col.BLN)
| def sendp(s):
| print(col.WHT+"["+col.CYN+" send"+col.WHT+"] "+s+col.BLN)
| print(col.WHT+"["+col.YLW+" warn"+col.WHT+"] "+col.BLN+str(s))
def erorp(s):
sys.stderr.write(col.WHT+"["+col.RED+"error"+col.WHT+"] "+col.BLN+str(s)+"\n")
def sendp(s):
| 64 | 64 | 29 | 5 | 59 | pcrain/review-reappropriator | common.py | Python | sendp | sendp | 77 | 78 | 77 | 77 | ee21591fd982874de2280ee24f580280da07d16e | bigcode/the-stack | train |
eacbdd5a70e8ce7520e915d4 | train | function | def nlpPreprocess(nlpmodel,sentence):
structure = {}
structure["_tokens"] = []
structure["_units"] = []
sentence = sentence.lower()
doc = nlpmodel(sentence)
for token in doc:
structure["_tokens"].append([ #Make sure this matches TOKEN_STRUCTURE above
token.text, ... | def nlpPreprocess(nlpmodel,sentence):
| structure = {}
structure["_tokens"] = []
structure["_units"] = []
sentence = sentence.lower()
doc = nlpmodel(sentence)
for token in doc:
structure["_tokens"].append([ #Make sure this matches TOKEN_STRUCTURE above
token.text, #Plaintext of the token
token... | given as substring spans
def getRootSpan(token):
spanmin = token.idx
for child in token.children:
spanmin = min(spanmin,getRootSpan(child))
return spanmin
#Preprocess a string using our default nlp
def nlpPreprocess(nlpmodel,sentence):
| 64 | 64 | 173 | 11 | 52 | pcrain/review-reappropriator | common.py | Python | nlpPreprocess | nlpPreprocess | 194 | 211 | 194 | 194 | cb7d00c906f2a64be7ab6b3285dba9bec86964a2 | bigcode/the-stack | train |
c2e6d39038684e155f2adf7a | train | function | def compressedWrite(data,filename):
with gzip.GzipFile(filename, 'w') as fout:
fout.write(data.encode('utf-8'))
| def compressedWrite(data,filename):
| with gzip.GzipFile(filename, 'w') as fout:
fout.write(data.encode('utf-8'))
| file
def jsonWrite(data,filename,indent=2):
with open(filename, 'w') as fout:
fout.write(json.dumps(data,indent=indent))
# pprint.PrettyPrinter(width=118,indent=indent,stream=fout).pprint(data)
def compressedWrite(data,filename):
| 64 | 64 | 31 | 7 | 57 | pcrain/review-reappropriator | common.py | Python | compressedWrite | compressedWrite | 122 | 124 | 122 | 122 | 64e6ab7003a1f511ab11aedfde7080266ffb360c | bigcode/the-stack | train |
1b4aad439e32b20d5c7595a2 | train | function | def passp(s):
return getpass(col.WHT+"["+col.BLU+"paswd"+col.WHT+"] "+str(s)+col.BLN)
| def passp(s):
| return getpass(col.WHT+"["+col.BLU+"paswd"+col.WHT+"] "+str(s)+col.BLN)
| ")
def sendp(s):
print(col.WHT+"["+col.CYN+" send"+col.WHT+"] "+s+col.BLN)
def recvp(s):
print(col.WHT+"["+col.CYN+" recv"+col.WHT+"] "+s+col.BLN)
def passp(s):
| 64 | 64 | 33 | 5 | 59 | pcrain/review-reappropriator | common.py | Python | passp | passp | 81 | 82 | 81 | 81 | ff1bc40fcceb4b27fb110e83590dd0d376811c95 | bigcode/the-stack | train |
bc5a5dfc562003452075827b | train | function | def infop(s):
print(col.WHT+"["+col.GRN+" info"+col.WHT+"] "+col.BLN+str(s))
| def infop(s):
| print(col.WHT+"["+col.GRN+" info"+col.WHT+"] "+col.BLN+str(s))
| m' # Cyan
WHT = '\033[1;37m' # White
# Useful printing codes (long)
def inptp(s):
return input(col.WHT+"["+col.BLU+"input"+col.WHT+"] "+str(s)+col.BLN)
def infop(s):
| 64 | 64 | 30 | 5 | 59 | pcrain/review-reappropriator | common.py | Python | infop | infop | 62 | 63 | 62 | 62 | bd57a5ffce8fa46cc5ee16b33f7c6ab65e206038 | bigcode/the-stack | train |
8fa0fbb9f34fa27c670ae57f | train | class | class NLP_Pipeline():
def __init__(self,model=None):
self.nlp = spacy.load('en_core_web_sm' if model is None else model)
# self.nlp = spacy.load('en_core_web_sm')
def processText(self,text):
structure = {}
structure["text"] = text
structure["_md5"] = md5(text)
structure.update(nlpPr... | class NLP_Pipeline():
| def __init__(self,model=None):
self.nlp = spacy.load('en_core_web_sm' if model is None else model)
# self.nlp = spacy.load('en_core_web_sm')
def processText(self,text):
structure = {}
structure["text"] = text
structure["_md5"] = md5(text)
structure.update(nlpPreprocess(self.nlp,text... | similarphrases.append([ #Join the ngram and multiply the weights together
ngram,
reduce(lambda x, y: x*y, [p[0] for p in permutation]),
])
return similarphrases
#Pipeline to transform a string of text into usable NLP metadata
class NLP_Pipeline():
| 66 | 66 | 221 | 5 | 60 | pcrain/review-reappropriator | common.py | Python | NLP_Pipeline | NLP_Pipeline | 262 | 281 | 262 | 262 | 3b35778ee9f15d442819111345beb31a0b334d97 | bigcode/the-stack | train |
5a21b2189bb26d34b4cbffcb | train | function | def logfp(s,logf=None):
print(col.WHT+"["+col.MGN+" log"+col.WHT+"] "+col.BLN+str(s))
if logf is not None: logf.write(str(s)+"\n")
| def logfp(s,logf=None):
| print(col.WHT+"["+col.MGN+" log"+col.WHT+"] "+col.BLN+str(s))
if logf is not None: logf.write(str(s)+"\n")
| return input(col.WHT+"["+col.BLU+"input"+col.WHT+"] "+str(s)+col.BLN)
def infop(s):
print(col.WHT+"["+col.GRN+" info"+col.WHT+"] "+col.BLN+str(s))
def logfp(s,logf=None):
| 64 | 64 | 52 | 9 | 55 | pcrain/review-reappropriator | common.py | Python | logfp | logfp | 64 | 66 | 64 | 64 | be2f89b756f534be9d75ce473b63c9f84039fdb6 | bigcode/the-stack | train |
cae7c8a6de2c54f2e612e22b | train | class | class JsonStreamLoader:
# from jsonstreamer import JSONStreamer
def __init__(self):
self._json_streamer = JSONStreamer() #same for JSONStreamer
self.partial_json = None
self.substructures = []
self.keys = []
# self._dicttype = SortedDict
# self._dicttype ... | class JsonStreamLoader:
# from jsonstreamer import JSONStreamer
| def __init__(self):
self._json_streamer = JSONStreamer() #same for JSONStreamer
self.partial_json = None
self.substructures = []
self.keys = []
# self._dicttype = SortedDict
# self._dicttype = blist.sorteddict
# self._dicttype = blist.sorteddict
... | len(chunk)
bb = b''.join(chunks)
# print(bb)
return bb
def receiveInt(self):
nbytes = struct.unpack(">b",self.receiveBytes(1))[0]
if nbytes == 1:
return struct.unpack(">b",self.receiveBytes(nbytes))
elif nbytes == 2:
return struct.unpack(">h",self.receiveBytes(nbytes))
elif n... | 217 | 217 | 726 | 15 | 201 | pcrain/review-reappropriator | common.py | Python | JsonStreamLoader | JsonStreamLoader | 379 | 458 | 379 | 380 | 63cee593a2ed27846c56c7ce463c4302ade8b820 | bigcode/the-stack | train |
b1aa610663d702df9b849403 | train | function | def erorp(s):
sys.stderr.write(col.WHT+"["+col.RED+"error"+col.WHT+"] "+col.BLN+str(s)+"\n")
| def erorp(s):
| sys.stderr.write(col.WHT+"["+col.RED+"error"+col.WHT+"] "+col.BLN+str(s)+"\n")
| _simulate:
print(col.WHT+"["+col.CYN+"simul"+col.WHT+"] "+col.BLN+str(s))
def warnp(s):
print(col.WHT+"["+col.YLW+" warn"+col.WHT+"] "+col.BLN+str(s))
def erorp(s):
| 64 | 64 | 34 | 5 | 59 | pcrain/review-reappropriator | common.py | Python | erorp | erorp | 75 | 76 | 75 | 75 | 190450ead77cb53c8250b914927c4622a02e68c4 | bigcode/the-stack | train |
61fddb5d9964c74b6cca26cf | train | function | def inptp(s):
return input(col.WHT+"["+col.BLU+"input"+col.WHT+"] "+str(s)+col.BLN)
| def inptp(s):
| return input(col.WHT+"["+col.BLU+"input"+col.WHT+"] "+str(s)+col.BLN)
| m' # Blue
MGN = '\033[1;35m' # Magenta
CYN = '\033[1;36m' # Cyan
WHT = '\033[1;37m' # White
# Useful printing codes (long)
def inptp(s):
| 64 | 64 | 32 | 6 | 58 | pcrain/review-reappropriator | common.py | Python | inptp | inptp | 60 | 61 | 60 | 60 | b3a0e5c8390d05a0a105339d80819735097f8439 | bigcode/the-stack | train |
09467a3a06606890894af9d1 | train | class | class col:
BLN = '\033[0m' # Blank
UND = '\033[1;4m' # Underlined
INV = '\033[1;7m' # Inverted
CRT = '\033[1;41m' # Critical
BLK = '\033[1;30m' # Black
RED = '\033[1;31m' # Red
GRN = '\033[1;32m' # Green
YLW = '\033[1;33m' # Yellow
BLU = '\033[1;34m' # Blue
MGN = '\033[1;35m' # Magenta
CYN = ... | class col:
| BLN = '\033[0m' # Blank
UND = '\033[1;4m' # Underlined
INV = '\033[1;7m' # Inverted
CRT = '\033[1;41m' # Critical
BLK = '\033[1;30m' # Black
RED = '\033[1;31m' # Red
GRN = '\033[1;32m' # Green
YLW = '\033[1;33m' # Yellow
BLU = '\033[1;34m' # Blue
MGN = '\033[1;35m' # Magenta
CYN = '\033[1;36m... | 'was', 'here', 'than'
}
ALPHA = 'abcdefghijklmnopqrstuvwxyz'
RE_WORD = re.compile(r"""[\-\'a-zA-Z]{2,}""")
DEFAULTTUPLE = [0,9999,9999]
_debug = True
#Colors
class col:
| 64 | 64 | 183 | 3 | 60 | pcrain/review-reappropriator | common.py | Python | col | col | 45 | 57 | 45 | 45 | c24cb4d84b742a262ba960e0eaa8a0d5d300e722 | bigcode/the-stack | train |
0cf15406d97bdbadc72e89e0 | train | function | def writeDictToCsv(file,headerfields,datadict):
with open(file,'w') as fout:
writer = csv.writer(fout,delimiter='\t')
writer.writerow(headerfields)
for entry in datadict:
writer.writerow([entry[f] if f in entry else "" for f in headerfields])
| def writeDictToCsv(file,headerfields,datadict):
| with open(file,'w') as fout:
writer = csv.writer(fout,delimiter='\t')
writer.writerow(headerfields)
for entry in datadict:
writer.writerow([entry[f] if f in entry else "" for f in headerfields])
| = timer()
result = method(*args, **kw)
end = timer()
dbugp(" Took {} seconds".format(end-start))
return result
return timed
#Write a list of dictionaries to a CSV
def writeDictToCsv(file,headerfields,datadict):
| 64 | 64 | 69 | 14 | 49 | pcrain/review-reappropriator | common.py | Python | writeDictToCsv | writeDictToCsv | 95 | 100 | 95 | 95 | 7ae76a53a39efffa55ca28e3490ed7e42188d0ef | bigcode/the-stack | train |
81f2e0e67f5c8b8a86378f28 | train | function | def getValidTokens(tokenlist):
validtokens = []
for token in tokenlist:
if not RE_WORD.search(token[0]):
continue
if token[1] in STOPWORDS: #Check if lemmatized version is in stopwords
continue
validtokens.append(token)
return validtokens
| def getValidTokens(tokenlist):
| validtokens = []
for token in tokenlist:
if not RE_WORD.search(token[0]):
continue
if token[1] in STOPWORDS: #Check if lemmatized version is in stopwords
continue
validtokens.append(token)
return validtokens
| its-1):
curunit += 1
units.append([])
nextunitpos = len(review["text"]) if (curunit == nunits-1) else review["_units"][curunit+1]
units[-1].append(t)
return units
def getValidTokens(tokenlist):
| 64 | 64 | 68 | 7 | 56 | pcrain/review-reappropriator | common.py | Python | getValidTokens | getValidTokens | 229 | 237 | 229 | 229 | da8bc8945fa12084a6aa020a15d020ce869962d6 | bigcode/the-stack | train |
ed81f5ebac0cffed812cbd0f | train | function | def recvp(s):
print(col.WHT+"["+col.CYN+" recv"+col.WHT+"] "+s+col.BLN)
| def recvp(s):
| print(col.WHT+"["+col.CYN+" recv"+col.WHT+"] "+s+col.BLN)
| ):
sys.stderr.write(col.WHT+"["+col.RED+"error"+col.WHT+"] "+col.BLN+str(s)+"\n")
def sendp(s):
print(col.WHT+"["+col.CYN+" send"+col.WHT+"] "+s+col.BLN)
def recvp(s):
| 64 | 64 | 29 | 5 | 59 | pcrain/review-reappropriator | common.py | Python | recvp | recvp | 79 | 80 | 79 | 79 | d7403302c7e2877a30e8c0243c0d55216a07cd70 | bigcode/the-stack | train |
7b55d81cbb7ef5bb65c45c87 | train | function | def skipgrams(sequence, n, k, **kwargs):
"""
Returns all possible skipgrams generated from a sequence of items, as an iterator.
Skipgrams are ngrams that allows tokens to be skipped.
Refer to http://homepages.inf.ed.ac.uk/ballison/pdf/lrec_skipgrams.pdf
:param sequence: the source data to be conver... | def skipgrams(sequence, n, k, **kwargs):
| """
Returns all possible skipgrams generated from a sequence of items, as an iterator.
Skipgrams are ngrams that allows tokens to be skipped.
Refer to http://homepages.inf.ed.ac.uk/ballison/pdf/lrec_skipgrams.pdf
:param sequence: the source data to be converted into trigrams
:type sequence: seq... | Pad an ngram sequence
def pad_sequence(sequence, n, pad_left=False, pad_right=False, pad_symbol=None):
if pad_left:
sequence = chain((pad_symbol,) * (n-1), sequence)
if pad_right:
sequence = chain(sequence, (pad_symbol,) * (n-1))
return sequence
#Generate skipgrams from a sequence
def skip... | 91 | 91 | 305 | 12 | 78 | pcrain/review-reappropriator | common.py | Python | skipgrams | skipgrams | 155 | 184 | 155 | 155 | 6a5f9fa8d3ecf6ef53e51a76459cd2b0b6282352 | bigcode/the-stack | train |
3eef45876cc6e8558b557465 | train | function | def jsonWrite(data,filename,indent=2):
with open(filename, 'w') as fout:
fout.write(json.dumps(data,indent=indent))
| def jsonWrite(data,filename,indent=2):
| with open(filename, 'w') as fout:
fout.write(json.dumps(data,indent=indent))
| ikey] : { f : row[i] for i,f in enumerate(fields) } for row in reader}
#Create a directory and all children necessary
def makedir(directory):
os.makedirs(directory,exist_ok=True)
#Write a JSON to a file
def jsonWrite(data,filename,indent=2):
| 64 | 64 | 33 | 11 | 52 | pcrain/review-reappropriator | common.py | Python | jsonWrite | jsonWrite | 117 | 119 | 117 | 117 | bc35e454d4103a2ab95d60906b8d25377f55f358 | bigcode/the-stack | train |
0bd6bc6b3424b3dda204267a | train | function | def pad_sequence(sequence, n, pad_left=False, pad_right=False, pad_symbol=None):
if pad_left:
sequence = chain((pad_symbol,) * (n-1), sequence)
if pad_right:
sequence = chain(sequence, (pad_symbol,) * (n-1))
return sequence
| def pad_sequence(sequence, n, pad_left=False, pad_right=False, pad_symbol=None):
| if pad_left:
sequence = chain((pad_symbol,) * (n-1), sequence)
if pad_right:
sequence = chain(sequence, (pad_symbol,) * (n-1))
return sequence
| print("obj.%s = %r" % (attr, getattr(obj, attr)))
except: print("obj.%s = %s" % (attr, "error"))
# Pad an ngram sequence
def pad_sequence(sequence, n, pad_left=False, pad_right=False, pad_symbol=None):
| 64 | 64 | 65 | 19 | 44 | pcrain/review-reappropriator | common.py | Python | pad_sequence | pad_sequence | 147 | 152 | 147 | 147 | 06a3a808e9f51bc3f71547287b406a5600094b65 | bigcode/the-stack | train |
a939a720bb806c01696ec316 | train | function | def makedir(directory):
os.makedirs(directory,exist_ok=True)
| def makedir(directory):
| os.makedirs(directory,exist_ok=True)
| :
return [ { f : row[i] for i,f in enumerate(fields) } for row in reader ]
return { row[ikey] : { f : row[i] for i,f in enumerate(fields) } for row in reader}
#Create a directory and all children necessary
def makedir(directory):
| 64 | 64 | 14 | 5 | 58 | pcrain/review-reappropriator | common.py | Python | makedir | makedir | 113 | 114 | 113 | 113 | ddff5be3b548ea9c00df0273baad4942e25cef88 | bigcode/the-stack | train |
096a2a074fd124ac40a453f8 | train | function | def loadCsvAsDict(file,ikey=None):
with open(file,"r") as csvfile:
reader = csv.reader((x.replace('\0', ' ') for x in csvfile),delimiter='\t',quoting=csv.QUOTE_NONE)
fields = next(reader)
ikey = None if not ikey in fields else fields.index(ikey)
if ikey is None:
return [ { f : row[i] for i,f in ... | def loadCsvAsDict(file,ikey=None):
| with open(file,"r") as csvfile:
reader = csv.reader((x.replace('\0', ' ') for x in csvfile),delimiter='\t',quoting=csv.QUOTE_NONE)
fields = next(reader)
ikey = None if not ikey in fields else fields.index(ikey)
if ikey is None:
return [ { f : row[i] for i,f in enumerate(fields) } for row in read... | (fout,delimiter='\t')
writer.writerow(headerfields)
for entry in datadict:
writer.writerow([entry[f] if f in entry else "" for f in headerfields])
#Load a CSV into a list of dictionaries or dictionary of dictionaries
def loadCsvAsDict(file,ikey=None):
| 64 | 64 | 131 | 10 | 53 | pcrain/review-reappropriator | common.py | Python | loadCsvAsDict | loadCsvAsDict | 103 | 110 | 103 | 103 | b774571ef46c9ca79f59eb8c235b69f12fb12d11 | bigcode/the-stack | train |
5be65790456715ab9d3da6ef | train | function | def md5(string):
return hashlib.md5(string.encode('utf-8')).hexdigest()
| def md5(string):
| return hashlib.md5(string.encode('utf-8')).hexdigest()
| ).encode('utf-8'))
#Decompress and read a JSON from a file
def compressedJsonRead(filename):
with gzip.GzipFile(filename, 'r') as fin:
return json.loads(fin.read().decode('utf-8'))
#Compute md5sum for string
def md5(string):
| 64 | 64 | 20 | 5 | 58 | pcrain/review-reappropriator | common.py | Python | md5 | md5 | 137 | 138 | 137 | 137 | 004d58309ea8bec4f00b5bb7c678da1721290359 | bigcode/the-stack | train |
358237eaffa7cebb27efeb94 | train | function | def compressedJsonRead(filename):
with gzip.GzipFile(filename, 'r') as fin:
return json.loads(fin.read().decode('utf-8'))
| def compressedJsonRead(filename):
| with gzip.GzipFile(filename, 'r') as fin:
return json.loads(fin.read().decode('utf-8'))
| 8'))
#Compress and write a JSON to a file
def compressedJsonWrite(data,filename):
with gzip.GzipFile(filename, 'w') as fout:
fout.write(json.dumps(data).encode('utf-8'))
#Decompress and read a JSON from a file
def compressedJsonRead(filename):
| 64 | 64 | 33 | 6 | 57 | pcrain/review-reappropriator | common.py | Python | compressedJsonRead | compressedJsonRead | 132 | 134 | 132 | 132 | 140df910a877e2d5611fa8b4105d540ffbbf1b88 | bigcode/the-stack | train |
edc291108c4a83f3685b2a9d | train | function | def findSimilarPhrases(item,similaritydict,max_synonyms=10):
mutations = [[] for _ in item] #Generate an empty list of mutations
for ind,word in enumerate([w[1] for w in item]): #Use lemmatized form of each word
if word not in similaritydict:
continue
for synonym in similaritydict[word][:max_synonyms]... | def findSimilarPhrases(item,similaritydict,max_synonyms=10):
| mutations = [[] for _ in item] #Generate an empty list of mutations
for ind,word in enumerate([w[1] for w in item]): #Use lemmatized form of each word
if word not in similaritydict:
continue
for synonym in similaritydict[word][:max_synonyms]: #Get the top max_synonyms for each word and it's sim-weight... | findNgramInSortedList(item,sortedlist):
ipoint = sortedlist.bisect_left([item,[DEFAULTTUPLE]])
return None if (ipoint == len(sortedlist) or (sortedlist[ipoint][0] != item)) else ipoint
def findSimilarPhrases(item,similaritydict,max_synonyms=10):
| 73 | 73 | 245 | 16 | 56 | pcrain/review-reappropriator | common.py | Python | findSimilarPhrases | findSimilarPhrases | 243 | 259 | 243 | 243 | fff2a811abe38aa1b0469a3d036e3daa7e76a083 | bigcode/the-stack | train |
7089657f7fbf83265f9a7c31 | train | function | def simup(s):
if _simulate:
print(col.WHT+"["+col.CYN+"simul"+col.WHT+"] "+col.BLN+str(s))
| def simup(s):
| if _simulate:
print(col.WHT+"["+col.CYN+"simul"+col.WHT+"] "+col.BLN+str(s))
| .BLN+str(s))
if logf is not None: logf.write(str(s)+"\n")
def dbugp(s):
if _debug:
print(col.WHT+"["+col.BLK+"debug"+col.WHT+"] "+col.BLN+str(s))
def simup(s):
| 64 | 64 | 36 | 5 | 59 | pcrain/review-reappropriator | common.py | Python | simup | simup | 70 | 72 | 70 | 70 | b9bb1e4b9b95d8b6c20a809f5afce4a9cbcfa415 | bigcode/the-stack | train |
3c4961871b228366afbff59f | train | function | def compressedJsonWrite(data,filename):
with gzip.GzipFile(filename, 'w') as fout:
fout.write(json.dumps(data).encode('utf-8'))
| def compressedJsonWrite(data,filename):
| with gzip.GzipFile(filename, 'w') as fout:
fout.write(json.dumps(data).encode('utf-8'))
| =118,indent=indent,stream=fout).pprint(data)
def compressedWrite(data,filename):
with gzip.GzipFile(filename, 'w') as fout:
fout.write(data.encode('utf-8'))
#Compress and write a JSON to a file
def compressedJsonWrite(data,filename):
| 64 | 64 | 35 | 8 | 55 | pcrain/review-reappropriator | common.py | Python | compressedJsonWrite | compressedJsonWrite | 127 | 129 | 127 | 127 | e66735306836da6c137c80dfe0b7870c11cb1ea9 | bigcode/the-stack | train |
33ec4f4db265d9aefba09c9b | train | function | def getRootSpan(token):
spanmin = token.idx
for child in token.children:
spanmin = min(spanmin,getRootSpan(child))
return spanmin
| def getRootSpan(token):
| spanmin = token.idx
for child in token.children:
spanmin = min(spanmin,getRootSpan(child))
return spanmin
| tail = ngram[1:]
for skip_tail in combinations(tail, n - 1):
if skip_tail[-1] is SENTINEL:
continue
yield head + skip_tail
#Given a token, break it into idea units given as substring spans
def getRootSpan(token):
| 64 | 64 | 37 | 6 | 57 | pcrain/review-reappropriator | common.py | Python | getRootSpan | getRootSpan | 187 | 191 | 187 | 187 | 87829d2840bba521807c5cb8f4e6f771249b660f | bigcode/the-stack | train |
562b8826b770ce42a9125bc0 | train | function | def dump(obj):
for attr in dir(obj):
try: print("obj.%s = %r" % (attr, getattr(obj, attr)))
except: print("obj.%s = %s" % (attr, "error"))
| def dump(obj):
| for attr in dir(obj):
try: print("obj.%s = %r" % (attr, getattr(obj, attr)))
except: print("obj.%s = %s" % (attr, "error"))
| with gzip.GzipFile(filename, 'r') as fin:
return json.loads(fin.read().decode('utf-8'))
#Compute md5sum for string
def md5(string):
return hashlib.md5(string.encode('utf-8')).hexdigest()
# Dump an object's attributes
def dump(obj):
| 64 | 64 | 52 | 4 | 59 | pcrain/review-reappropriator | common.py | Python | dump | dump | 141 | 144 | 141 | 141 | 99e305a4fa3b5d642a8464793e7587bfff5097b8 | bigcode/the-stack | train |
494c7673d667320018ecb61d | train | function | def getIdeaUnits(review):
nunits = len(review["_units"])
if nunits == 1:
return [review["_tokens"]]
units = [ [] ]
curunit = 0
nextunitpos = review["_units"][curunit+1]
for t in review["_tokens"]:
if t[2] >= nextunitpos: #t[2] = offset of token into string
if (curunit < nunits-1):
... | def getIdeaUnits(review):
| nunits = len(review["_units"])
if nunits == 1:
return [review["_tokens"]]
units = [ [] ]
curunit = 0
nextunitpos = review["_units"][curunit+1]
for t in review["_tokens"]:
if t[2] >= nextunitpos: #t[2] = offset of token into string
if (curunit < nunits-1):
curunit += 1
... | tag for token
token.pos_, #Part of Speech tag for token
token.head.idx, #Offset of parent token into the original string
])
if token.dep_ == "ROOT":
structure["_units"].append(getRootSpan(token))
return structure
def getIdeaUnits(review):
| 64 | 64 | 155 | 6 | 57 | pcrain/review-reappropriator | common.py | Python | getIdeaUnits | getIdeaUnits | 213 | 227 | 213 | 213 | cdd27a7baa61fb8f7a41034d1081bb322ea87a1c | bigcode/the-stack | train |
36e70566d4661a70cc1b1f81 | train | class | class SubProcArgs:
base = {'stdout': subprocess.PIPE, 'stderr': subprocess.STDOUT}
win = {'creationflags': subprocess.DETACHED_PROCESS | subprocess.CREATE_NEW_PROCESS_GROUP}
darwin = {'preexec_fn': os.setpgrp}
linux = {}
@classmethod
def get_host_args(cls):
if sys.platform.startswit... | class SubProcArgs:
| base = {'stdout': subprocess.PIPE, 'stderr': subprocess.STDOUT}
win = {'creationflags': subprocess.DETACHED_PROCESS | subprocess.CREATE_NEW_PROCESS_GROUP}
darwin = {'preexec_fn': os.setpgrp}
linux = {}
@classmethod
def get_host_args(cls):
if sys.platform.startswith('win'): return cl... | cache():
global runzCache, runz_dir
if runzCache is None:
runz_dir = get_lazydir(True).joinpath('runz')
runzCache = Cache(directory = runz_dir.as_posix())
return runzCache
class SubProcArgs:
| 64 | 64 | 140 | 5 | 58 | trisongz/lazycls | lazy/runz/core.py | Python | SubProcArgs | SubProcArgs | 27 | 43 | 27 | 27 | e74d5c8b0adfb67a49f03964ce9103bb08011b14 | bigcode/the-stack | train |
8c1b0f62ab9d9d8358d05966 | train | class | class RunzType(type):
@classmethod
def run_system(cls, cmd: str):
"""
alias for os.system(cmd)
"""
return os.system(cmd)
@classmethod
def run_cmd(cls, cmd: Union[List[str], str], shell: bool = True, raise_error: bool = True, **kwargs):
"""
Uses subproces... | class RunzType(type):
@classmethod
| def run_system(cls, cmd: str):
"""
alias for os.system(cmd)
"""
return os.system(cmd)
@classmethod
def run_cmd(cls, cmd: Union[List[str], str], shell: bool = True, raise_error: bool = True, **kwargs):
"""
Uses subprocess.check_output(cmd, shell=shell, **kwarg... | def get_runzcache():
global runzCache, runz_dir
if runzCache is None:
runz_dir = get_lazydir(True).joinpath('runz')
runzCache = Cache(directory = runz_dir.as_posix())
return runzCache
class SubProcArgs:
base = {'stdout': subprocess.PIPE, 'stderr': subprocess.STDOUT}
win = {'creatio... | 213 | 213 | 712 | 10 | 203 | trisongz/lazycls | lazy/runz/core.py | Python | RunzType | RunzType | 46 | 114 | 46 | 48 | 41ef2abe6f3d58beea7f66ad0e76713ea473f2da | bigcode/the-stack | train |
c50c528ebb424a103e14f6d8 | train | function | def get_runzcache():
global runzCache, runz_dir
if runzCache is None:
runz_dir = get_lazydir(True).joinpath('runz')
runzCache = Cache(directory = runz_dir.as_posix())
return runzCache
| def get_runzcache():
| global runzCache, runz_dir
if runzCache is None:
runz_dir = get_lazydir(True).joinpath('runz')
runzCache = Cache(directory = runz_dir.as_posix())
return runzCache
| PathLike, get_lazydir
from lazy.io.cachez import Cache
from .utils import *
runz_dir: PathLike = None #get_lazydir(True).joinpath('runz')
runzCache: Cache = None # = Cache(directory = )
def get_runzcache():
| 64 | 64 | 63 | 6 | 58 | trisongz/lazycls | lazy/runz/core.py | Python | get_runzcache | get_runzcache | 19 | 24 | 19 | 19 | db955bb479bd4213808f1575b80934163c763a59 | bigcode/the-stack | train |
ede9d9c023b359ebe1116560 | train | function | def almostEqual(a, b, thresh=0.01):
return a <= b + thresh * abs(b) and a >= b - thresh * abs(b)
| def almostEqual(a, b, thresh=0.01):
| return a <= b + thresh * abs(b) and a >= b - thresh * abs(b)
| def almostEqual(a, b, thresh=0.01):
| 13 | 64 | 34 | 13 | 0 | Sagar133/alpha-homora-v2-public-contract | tests/utils.py | Python | almostEqual | almostEqual | 1 | 2 | 1 | 1 | 0da36ddf019c3d5649ea38c70c1a49564924dec2 | bigcode/the-stack | train |
f0afdd3db350b43e93a166d0 | train | class | class ConfluenceReportBuilder(Builder):
name = 'internal-confluence-report'
def __init__(self, app):
super(ConfluenceReportBuilder, self).__init__(app)
def init(self):
validate_configuration(self)
self.config.sphinx_verbosity = self.app.verbosity
| class ConfluenceReportBuilder(Builder):
| name = 'internal-confluence-report'
def __init__(self, app):
super(ConfluenceReportBuilder, self).__init__(app)
def init(self):
validate_configuration(self)
self.config.sphinx_verbosity = self.app.verbosity
| : utf-8 -*-
"""
:copyright: Copyright 2020 Sphinx Confluence Builder Contributors (AUTHORS)
:license: BSD-2-Clause (LICENSE)
"""
from sphinx.builders import Builder
from sphinxcontrib.confluencebuilder.config.checks import validate_configuration
class ConfluenceReportBuilder(Builder):
| 64 | 64 | 63 | 8 | 55 | bob-schumaker/confluencebuilder | sphinxcontrib/confluencebuilder/reportbuilder.py | Python | ConfluenceReportBuilder | ConfluenceReportBuilder | 10 | 18 | 10 | 10 | 4bccc9a6551c7f9b5cd37ea9568cd47cd3c8bb37 | bigcode/the-stack | train |
18e38cb461a44d77cb588b39 | train | function | def run_load_test():
mock_test_file = load_json_file_test('load_tests_file_mock.json')
bert_wrapper = BertModelWrapper()
best_post_processor = BertNaturalAnswerPostprocessor()
for num_word in num_words:
start_time = time.time()
print('----------------------------')
print('load t... | def run_load_test():
| mock_test_file = load_json_file_test('load_tests_file_mock.json')
bert_wrapper = BertModelWrapper()
best_post_processor = BertNaturalAnswerPostprocessor()
for num_word in num_words:
start_time = time.time()
print('----------------------------')
print('load test with ', num_word,... | 100', '150', '200', '250', '300', '350', '400', '450', '500', '550', '600', '650', '700', '750', '800',
'850', '900', '950', '1000'
]
def run_load_test():
| 64 | 64 | 183 | 5 | 59 | guillaume-chevalier/ReuBERT | test/acceptance/charges_test/bert_user_input_load_test.py | Python | run_load_test | run_load_test | 20 | 45 | 20 | 20 | ff4e4e08edcbc14691b68d1379cc9ebcc61afb86 | bigcode/the-stack | train |
985cf12995c6bdb68ac9828a | train | function | def load_json_file_test(json_name):
with open(os.path.join(os.path.dirname(os.path.realpath(__file__)), json_name), encoding="utf8") as json_data:
return json.load(json_data)
| def load_json_file_test(json_name):
| with open(os.path.join(os.path.dirname(os.path.realpath(__file__)), json_name), encoding="utf8") as json_data:
return json.load(json_data)
| import os
import json
import time
from src.infrastructure.pipeline_steps.bert_model_wrapper import BertModelWrapper
from src.infrastructure.pipeline_steps.bert_natural_answer_postprocessor import BertNaturalAnswerPostprocessor
def load_json_file_test(json_name):
| 50 | 64 | 44 | 8 | 41 | guillaume-chevalier/ReuBERT | test/acceptance/charges_test/bert_user_input_load_test.py | Python | load_json_file_test | load_json_file_test | 9 | 11 | 9 | 9 | f8ea7656f0328a9d4ec6522625dbde189e7a4e4d | bigcode/the-stack | train |
0db099494afa6da97966f5f8 | train | class | class MockRenderer(ScopeRenderer):
def function(self, content: str, escape: bool = True) -> str:
return self._wrap_with_scope_style(content, "entity.name.function")
def punctuation(self, content: str) -> str:
return self._wrap_with_scope_style(content, "punctuation")
def parameter(self, c... | class MockRenderer(ScopeRenderer):
| def function(self, content: str, escape: bool = True) -> str:
return self._wrap_with_scope_style(content, "entity.name.function")
def punctuation(self, content: str) -> str:
return self._wrap_with_scope_style(content, "punctuation")
def parameter(self, content: str, emphasize: bool = False... | """
JSON_STRINGIFY = """"""
def create_signature(label: str, *param_labels, **kwargs) -> dict:
raw = dict(label=label, parameters=list(dict(label=param_label) for param_label in param_labels))
raw.update(kwargs)
return raw
class MockRenderer(ScopeRenderer):
| 64 | 64 | 168 | 7 | 56 | AmjadHD/LSP | tests/test_signature_help.py | Python | MockRenderer | MockRenderer | 118 | 133 | 118 | 119 | 021dd78f19dcd9ec1c2186c5e45c14f1f749b88d | bigcode/the-stack | train |
4be6447a0659e679f98ac108 | train | class | class GetDocumentationTests(unittest.TestCase):
def test_absent(self):
self.assertIsNone(get_documentation({}))
def test_is_str(self):
self.assertEqual(get_documentation({'documentation': 'str'}), 'str')
def test_is_dict(self):
self.assertEqual(get_documentation({'documentation': ... | class GetDocumentationTests(unittest.TestCase):
| def test_absent(self):
self.assertIsNone(get_documentation({}))
def test_is_str(self):
self.assertEqual(get_documentation({'documentation': 'str'}), 'str')
def test_is_dict(self):
self.assertEqual(get_documentation({'documentation': {'value': 'value'}}), 'value')
| , emphasize: bool = False) -> str:
return '\n<{}{}>{}</{}>'.format(scope, " emphasize" if emphasize else "", content, scope)
def markdown(self, content: str) -> str:
return content
renderer = MockRenderer()
class GetDocumentationTests(unittest.TestCase):
| 64 | 64 | 77 | 8 | 56 | AmjadHD/LSP | tests/test_signature_help.py | Python | GetDocumentationTests | GetDocumentationTests | 139 | 148 | 139 | 140 | 53f8a8789cc95a63a1e4e1a498a77efd9130355d | bigcode/the-stack | train |
ef10a90f77f66159dfd3b119 | train | function | def create_signature(label: str, *param_labels, **kwargs) -> dict:
raw = dict(label=label, parameters=list(dict(label=param_label) for param_label in param_labels))
raw.update(kwargs)
return raw
| def create_signature(label: str, *param_labels, **kwargs) -> dict:
| raw = dict(label=label, parameters=list(dict(label=param_label) for param_label in param_labels))
raw.update(kwargs)
return raw
| .name.function>
</pre></div>
<p>Foobaring with a multiplier</p>
<p><b>multiplier</b>: Change foobar to work on larger increments</p>"""
JSON_STRINGIFY = """"""
def create_signature(label: str, *param_labels, **kwargs) -> dict:
| 64 | 64 | 49 | 17 | 46 | AmjadHD/LSP | tests/test_signature_help.py | Python | create_signature | create_signature | 112 | 115 | 112 | 112 | 598ab04e0403c813d1d55c1cfd0cbde0d2f2c9e0 | bigcode/the-stack | train |
d7c822fe37c4fa64a0220d22 | train | class | class RenderSignatureLabelTests(unittest.TestCase):
def test_no_parameters(self):
sig = create_signature("foobar()")
help = create_signature_help(dict(signatures=[sig]))
if help:
label = render_signature_label(renderer, help.active_signature(), 0)
self.assertEqual(la... | class RenderSignatureLabelTests(unittest.TestCase):
| def test_no_parameters(self):
sig = create_signature("foobar()")
help = create_signature_help(dict(signatures=[sig]))
if help:
label = render_signature_label(renderer, help.active_signature(), 0)
self.assertEqual(label, "\n<entity.name.function>foobar()</entity.name.f... | .assertIsNotNone(help)
if help:
self.assertEqual(help._active_signature_index, 0)
self.assertEqual(help._active_parameter_index, -1)
def test_dockerfile_signature_help(self):
info = parse_signature_information({
'label': 'RUN [ "command" "parameters", ... ]',
... | 256 | 256 | 981 | 9 | 247 | AmjadHD/LSP | tests/test_signature_help.py | Python | RenderSignatureLabelTests | RenderSignatureLabelTests | 190 | 276 | 190 | 191 | 6d453bafe518aa77d3b1c381ad304f109495755d | bigcode/the-stack | train |
6c12818bb327e0a1e9f54ffe | train | class | class SignatureHelpTests(unittest.TestCase):
def test_single_signature(self):
help = SignatureHelp([signature_information])
self.assertIsNotNone(help)
if help:
content = help.build_popup_content(renderer)
self.assertFalse(help.has_multiple_signatures())
s... | class SignatureHelpTests(unittest.TestCase):
| def test_single_signature(self):
help = SignatureHelp([signature_information])
self.assertIsNotNone(help)
if help:
content = help.build_popup_content(renderer)
self.assertFalse(help.has_multiple_signatures())
self.assertEqual(content, SINGLE_SIGNATURE)
... | </variable.parameter>: int,\
<br> \n<variable.parameter emphasize>bar_if_needed</variable.parameter>: Optional[str],\
<br> \n<variable.parameter>in_uppercase</variable.parameter>: Optional[bool]
<punctuation>)</punctuation> -> Optional[str]</entity.name.function>""")
c... | 92 | 92 | 308 | 8 | 84 | AmjadHD/LSP | tests/test_signature_help.py | Python | SignatureHelpTests | SignatureHelpTests | 279 | 317 | 279 | 280 | 964d6201de816118fd7c1bc562391b53b5961685 | bigcode/the-stack | train |
810c3e2a61cfe1e3f7fbdcd2 | train | class | class CreateSignatureHelpTests(unittest.TestCase):
def test_none(self):
self.assertIsNone(create_signature_help(None))
def test_empty(self):
self.assertIsNone(create_signature_help({}))
def test_default_indices(self):
help = create_signature_help({"signatures": [signature]})
... | class CreateSignatureHelpTests(unittest.TestCase):
| def test_none(self):
self.assertIsNone(create_signature_help(None))
def test_empty(self):
self.assertIsNone(create_signature_help({}))
def test_default_indices(self):
help = create_signature_help({"signatures": [signature]})
self.assertIsNotNone(help)
if help:
... | content
renderer = MockRenderer()
class GetDocumentationTests(unittest.TestCase):
def test_absent(self):
self.assertIsNone(get_documentation({}))
def test_is_str(self):
self.assertEqual(get_documentation({'documentation': 'str'}), 'str')
def test_is_dict(self):
self.assertEqu... | 93 | 93 | 312 | 9 | 84 | AmjadHD/LSP | tests/test_signature_help.py | Python | CreateSignatureHelpTests | CreateSignatureHelpTests | 151 | 187 | 151 | 152 | 2f884dbfe834fd1ab7d42a342a0ce2d910ffc2ed | bigcode/the-stack | train |
eb9215945ea88afb3969b417 | train | class | class Animal(Model):
__table__="animals" | class Animal(Model):
| __table__="animals" | """Animal Model."""
from masoniteorm.models import Model
class Animal(Model):
| 16 | 64 | 11 | 4 | 11 | ehuber0601/online_zoo_backend | app/Animal.py | Python | Animal | Animal | 6 | 7 | 6 | 6 | 4836ec4b2258e48c0af229c154c9bd0f117a6996 | bigcode/the-stack | train |
6b54f6e8b8dc87c7e77df969 | train | class | class Broker:
"""
This class provides a template interface for all those broker related
actions/tasks wrapping the actual implementation class internally
"""
factory: BrokerFactory
stocks_ifc: StocksInterface
account_ifc: AccountInterface
def __init__(self, factory: BrokerFactory) -> N... | class Broker:
| """
This class provides a template interface for all those broker related
actions/tasks wrapping the actual implementation class internally
"""
factory: BrokerFactory
stocks_ifc: StocksInterface
account_ifc: AccountInterface
def __init__(self, factory: BrokerFactory) -> None:
s... | from typing import Any, Dict, List, Optional
from ...interfaces import Market, MarketHistory, MarketMACD, Position
from .. import Interval, TradeDirection
from . import AccountInterface, BrokerFactory, StocksInterface
class Broker:
| 49 | 198 | 662 | 3 | 45 | stungkit/TradingBot | tradingbot/components/broker/broker.py | Python | Broker | Broker | 8 | 99 | 8 | 8 | 6ac3e9471ff889debc28a280cea93c0410d96412 | bigcode/the-stack | train |
15d5be7485dccab8096595c3 | train | function | def generate_user_knowledge_database(answers_dict):
# texts = pd.read_csv("3000.csv")
user_id = answers_dict['username']
user_tests_stack = redis_db.get("username_" + user_id + "_last_test")
print("generate_user_knowledge_database >> user_tests_stack", user_tests_stack)
if user_tests_stack is not N... | def generate_user_knowledge_database(answers_dict):
# texts = pd.read_csv("3000.csv")
| user_id = answers_dict['username']
user_tests_stack = redis_db.get("username_" + user_id + "_last_test")
print("generate_user_knowledge_database >> user_tests_stack", user_tests_stack)
if user_tests_stack is not None:
# user_tests_stack["username_" + user_id + "_last_test"] = None
redis_... | json.load(f)
"""
json_text_map = get_text_map("./text_8.txt")
#print(json_text_map['sentences_map'][0])
user.update_vector_with_answer_sentence(json_text_map['sentences_map'][0],1)
user.update_vector_with_answer_sentence(json_text_map['sentences_map'][4],1)
user.update_vector_with_answer_sentence(json_text_map['sen... | 113 | 113 | 377 | 22 | 91 | NatalieIsupova/hseling-repo-autotutor | hseling_api_autotutor/app/recommendation_logic/get_marked_datasets.py | Python | generate_user_knowledge_database | generate_user_knowledge_database | 35 | 63 | 35 | 37 | 9edda33726df71565dfe77ccec91a981017d71b4 | bigcode/the-stack | train |
d7b7ecc59ae0523319d16998 | train | function | def hex_bits(features):
# We always to full bytes
flen = (max(features + [0]) + 7) // 8 * 8
res = bitstring.BitArray(length=flen)
# Big endian sucketh.
for f in features:
res[flen - 1 - f] = 1
return res.hex
| def hex_bits(features):
# We always to full bytes
| flen = (max(features + [0]) + 7) // 8 * 8
res = bitstring.BitArray(length=flen)
# Big endian sucketh.
for f in features:
res[flen - 1 - f] = 1
return res.hex
| ln.testing.utils import EXPERIMENTAL_DUAL_FUND
EXPERIMENTAL_FEATURES = env("EXPERIMENTAL_FEATURES", "0") == "1"
COMPAT = env("COMPAT", "1") == "1"
def hex_bits(features):
# We always to full bytes
| 64 | 64 | 78 | 13 | 51 | openoms/lightning | tests/utils.py | Python | hex_bits | hex_bits | 11 | 18 | 11 | 12 | e81a6052e06d917b7049527416ed546689f763a2 | bigcode/the-stack | train |
8ceb93706ceb6a659edc6472 | train | function | def check_coin_moves(n, account_id, expected_moves, chainparams):
moves = n.rpc.call('listcoinmoves_plugin')['coin_moves']
node_id = n.info['id']
acct_moves = [m for m in moves if m['account_id'] == account_id]
for mv in acct_moves:
print("{{'type': '{}', 'credit': {}, 'debit': {}, 'tag': '{}'}}... | def check_coin_moves(n, account_id, expected_moves, chainparams):
| moves = n.rpc.call('listcoinmoves_plugin')['coin_moves']
node_id = n.info['id']
acct_moves = [m for m in moves if m['account_id'] == account_id]
for mv in acct_moves:
print("{{'type': '{}', 'credit': {}, 'debit': {}, 'tag': '{}'}},"
.format(mv['type'],
Millisa... | for this configuration"""
features = []
return hex_bits(features + extra)
def move_matches(exp, mv):
if mv['type'] != exp['type']:
return False
if mv['credit'] != "{}msat".format(exp['credit']):
return False
if mv['debit'] != "{}msat".format(exp['debit']):
return False
... | 114 | 114 | 380 | 15 | 98 | openoms/lightning | tests/utils.py | Python | check_coin_moves | check_coin_moves | 77 | 114 | 77 | 77 | cf4ed34662693c0c498d8a395a580f1fd41e3833 | bigcode/the-stack | train |
1bdb9614f1dc5d158386b496 | train | function | def expected_peer_features(wumbo_channels=False, extra=[]):
"""Return the expected peer features hexstring for this configuration"""
features = [1, 5, 7, 9, 11, 13, 15, 17, 27]
if EXPERIMENTAL_FEATURES:
# OPT_ONION_MESSAGES
features += [103]
# option_anchor_outputs
features +... | def expected_peer_features(wumbo_channels=False, extra=[]):
| """Return the expected peer features hexstring for this configuration"""
features = [1, 5, 7, 9, 11, 13, 15, 17, 27]
if EXPERIMENTAL_FEATURES:
# OPT_ONION_MESSAGES
features += [103]
# option_anchor_outputs
features += [21]
if wumbo_channels:
features += [19]
i... | 7) // 8 * 8
res = bitstring.BitArray(length=flen)
# Big endian sucketh.
for f in features:
res[flen - 1 - f] = 1
return res.hex
def expected_peer_features(wumbo_channels=False, extra=[]):
| 64 | 64 | 146 | 12 | 51 | openoms/lightning | tests/utils.py | Python | expected_peer_features | expected_peer_features | 21 | 36 | 21 | 21 | e6bf4baeda51df58d02732c5cd456cd6eee3e8f9 | bigcode/the-stack | train |
a10cf81726fc54c066586591 | train | function | def move_matches(exp, mv):
if mv['type'] != exp['type']:
return False
if mv['credit'] != "{}msat".format(exp['credit']):
return False
if mv['debit'] != "{}msat".format(exp['debit']):
return False
if mv['tag'] != exp['tag']:
return False
return True
| def move_matches(exp, mv):
| if mv['type'] != exp['type']:
return False
if mv['credit'] != "{}msat".format(exp['credit']):
return False
if mv['debit'] != "{}msat".format(exp['debit']):
return False
if mv['tag'] != exp['tag']:
return False
return True
| option_dual_fund
features += [29]
return hex_bits(features + extra)
def expected_channel_features(wumbo_channels=False, extra=[]):
"""Return the expected channel features hexstring for this configuration"""
features = []
return hex_bits(features + extra)
def move_matches(exp, mv):
| 64 | 64 | 83 | 7 | 57 | openoms/lightning | tests/utils.py | Python | move_matches | move_matches | 65 | 74 | 65 | 65 | 7ea2a0f6d5d11a684fb4c837ac15e43c97a93b1d | bigcode/the-stack | train |
0167aa0255151f534d0a906a | train | function | def check_coin_moves_idx(n):
""" Just check that the counter increments smoothly"""
moves = n.rpc.call('listcoinmoves_plugin')['coin_moves']
idx = 0
for m in moves:
c_idx = m['movement_idx']
# verify that the index count increments smoothly here, also
if c_idx == 0 and idx == 0:
... | def check_coin_moves_idx(n):
| """ Just check that the counter increments smoothly"""
moves = n.rpc.call('listcoinmoves_plugin')['coin_moves']
idx = 0
for m in moves:
c_idx = m['movement_idx']
# verify that the index count increments smoothly here, also
if c_idx == 0 and idx == 0:
continue
... | _moves[number_moves:]
else:
if not move_matches(m, acct_moves[0]):
raise ValueError("Unexpected move {}: {} != {}".format(num, acct_moves[0], m))
acct_moves = acct_moves[1:]
assert acct_moves == []
def check_coin_moves_idx(n):
| 63 | 64 | 98 | 7 | 56 | openoms/lightning | tests/utils.py | Python | check_coin_moves_idx | check_coin_moves_idx | 117 | 127 | 117 | 117 | fcd566a8e99779a03da294d54b24d0026eceab20 | bigcode/the-stack | train |
73634ba75be07b45ddd51608 | train | function | def account_balance(n, account_id):
moves = n.rpc.call('listcoinmoves_plugin')['coin_moves']
chan_moves = [m for m in moves if m['account_id'] == account_id]
assert len(chan_moves) > 0
m_sum = 0
for m in chan_moves:
m_sum += int(m['credit'][:-4])
m_sum -= int(m['debit'][:-4])
ret... | def account_balance(n, account_id):
| moves = n.rpc.call('listcoinmoves_plugin')['coin_moves']
chan_moves = [m for m in moves if m['account_id'] == account_id]
assert len(chan_moves) > 0
m_sum = 0
for m in chan_moves:
m_sum += int(m['credit'][:-4])
m_sum -= int(m['debit'][:-4])
return m_sum
| moves:
c_idx = m['movement_idx']
# verify that the index count increments smoothly here, also
if c_idx == 0 and idx == 0:
continue
assert c_idx == idx + 1
idx = c_idx
def account_balance(n, account_id):
| 64 | 64 | 97 | 8 | 55 | openoms/lightning | tests/utils.py | Python | account_balance | account_balance | 130 | 138 | 130 | 130 | f869ab1b82d5296101baac2c0e8727aaddb5bc0d | bigcode/the-stack | train |
899407facb982a06cabd01c0 | train | function | def expected_channel_features(wumbo_channels=False, extra=[]):
"""Return the expected channel features hexstring for this configuration"""
features = []
return hex_bits(features + extra)
| def expected_channel_features(wumbo_channels=False, extra=[]):
| """Return the expected channel features hexstring for this configuration"""
features = []
return hex_bits(features + extra)
| :
features += [19]
if EXPERIMENTAL_DUAL_FUND:
# option_anchor_outputs
features += [21]
# option_dual_fund
features += [29]
return hex_bits(features + extra)
def expected_channel_features(wumbo_channels=False, extra=[]):
| 64 | 64 | 37 | 12 | 52 | openoms/lightning | tests/utils.py | Python | expected_channel_features | expected_channel_features | 59 | 62 | 59 | 59 | 52e3ab4e03c874a132eda40487af1c1965b4865b | bigcode/the-stack | train |
6ae4380ed46953af55136770 | train | function | def expected_node_features(wumbo_channels=False, extra=[]):
"""Return the expected node features hexstring for this configuration"""
features = [1, 5, 7, 9, 11, 13, 15, 17, 27, 55]
if EXPERIMENTAL_FEATURES:
# OPT_ONION_MESSAGES
features += [103]
# option_anchor_outputs
featur... | def expected_node_features(wumbo_channels=False, extra=[]):
| """Return the expected node features hexstring for this configuration"""
features = [1, 5, 7, 9, 11, 13, 15, 17, 27, 55]
if EXPERIMENTAL_FEATURES:
# OPT_ONION_MESSAGES
features += [103]
# option_anchor_outputs
features += [21]
if wumbo_channels:
features += [19]
... | _dual_fund
features += [29]
return hex_bits(features + extra)
# With the addition of the keysend plugin, we now send a different set of
# features for the 'node' and the 'peer' feature sets
def expected_node_features(wumbo_channels=False, extra=[]):
| 64 | 64 | 149 | 12 | 51 | openoms/lightning | tests/utils.py | Python | expected_node_features | expected_node_features | 41 | 56 | 41 | 41 | f2596816b596ddc3e35137ff6e1b573d3bfff226 | bigcode/the-stack | train |
91b4a6317214c2d625789b74 | train | function | def scriptpubkey_addr(scriptpubkey):
if 'addresses' in scriptpubkey:
return scriptpubkey['addresses'][0]
elif 'address' in scriptpubkey:
# Modern bitcoin (at least, git master)
return scriptpubkey['address']
return None
| def scriptpubkey_addr(scriptpubkey):
| if 'addresses' in scriptpubkey:
return scriptpubkey['addresses'][0]
elif 'address' in scriptpubkey:
# Modern bitcoin (at least, git master)
return scriptpubkey['address']
return None
| ):
if EXPERIMENTAL_FEATURES or EXPERIMENTAL_DUAL_FUND:
# option_anchor_outputs
weight = 1124
else:
weight = 724
return (weight * feerate) // 1000
def scriptpubkey_addr(scriptpubkey):
| 64 | 64 | 62 | 9 | 54 | openoms/lightning | tests/utils.py | Python | scriptpubkey_addr | scriptpubkey_addr | 154 | 160 | 154 | 154 | 9fb8c42df5551fffc7541d43690fde8cafa65230 | bigcode/the-stack | train |
8e7e16d69ef6a888f0f4bf38 | train | function | def basic_fee(feerate):
if EXPERIMENTAL_FEATURES or EXPERIMENTAL_DUAL_FUND:
# option_anchor_outputs
weight = 1124
else:
weight = 724
return (weight * feerate) // 1000
| def basic_fee(feerate):
| if EXPERIMENTAL_FEATURES or EXPERIMENTAL_DUAL_FUND:
# option_anchor_outputs
weight = 1124
else:
weight = 724
return (weight * feerate) // 1000
| m_sum -= int(m['debit'][:-4])
return m_sum
def first_channel_id(n1, n2):
return only_one(only_one(n1.rpc.listpeers(n2.info['id'])['peers'])['channels'])['channel_id']
def basic_fee(feerate):
| 64 | 64 | 61 | 7 | 57 | openoms/lightning | tests/utils.py | Python | basic_fee | basic_fee | 145 | 151 | 145 | 145 | 1eeaee8861beb540e55b00c82de243cc2395a3b1 | bigcode/the-stack | train |
f751ded18bc60df3f59f7ccd | train | function | def first_channel_id(n1, n2):
return only_one(only_one(n1.rpc.listpeers(n2.info['id'])['peers'])['channels'])['channel_id']
| def first_channel_id(n1, n2):
| return only_one(only_one(n1.rpc.listpeers(n2.info['id'])['peers'])['channels'])['channel_id']
| assert len(chan_moves) > 0
m_sum = 0
for m in chan_moves:
m_sum += int(m['credit'][:-4])
m_sum -= int(m['debit'][:-4])
return m_sum
def first_channel_id(n1, n2):
| 64 | 64 | 40 | 10 | 53 | openoms/lightning | tests/utils.py | Python | first_channel_id | first_channel_id | 141 | 142 | 141 | 141 | 0e534a7ca6cab2ec5a2d12bdfb16140badbaa961 | bigcode/the-stack | train |
0e7210a2fba39db5a05ce9f0 | train | class | class UnconfiguredProviderException(Exception):
pass
| class UnconfiguredProviderException(Exception):
| pass
| : blob})
out_fileno.write(header)
out_fileno.flush()
_aepipe.seal(key, in_fileno, out_fileno)
@contextmanager
def closing_fd(fd):
try:
yield fd
finally:
os.close(fd)
class UnconfiguredProviderException(Exception):
| 64 | 64 | 10 | 7 | 57 | hashbrowncipher/gcmpipe | keypipe/__init__.py | Python | UnconfiguredProviderException | UnconfiguredProviderException | 88 | 89 | 88 | 88 | f8a4faa14fb7b04486eaa8c64360bd493e1afc1c | bigcode/the-stack | train |
45bbab5e0b946ae6fa8356c6 | train | function | def seal(provider_name, provider_args, context, in_fileno, out_fileno):
module = get_provider_by_name(provider_name)
(plaintext, blob) = module.get_keypair(**provider_args)
salt = os.urandom(64)
checksum, key = derive_key(plaintext, salt, context)
# The checksum serves only to identify whether the... | def seal(provider_name, provider_args, context, in_fileno, out_fileno):
| module = get_provider_by_name(provider_name)
(plaintext, blob) = module.get_keypair(**provider_args)
salt = os.urandom(64)
checksum, key = derive_key(plaintext, salt, context)
# The checksum serves only to identify whether the correct key has been
# derived. Most of the header could be garbage... | ; indeed, it is an essential requirement
# that the leakage of one key produced by the KDF should not compromise
# other such keys"
checksum = next(generator)
return checksum, key
def seal(provider_name, provider_args, context, in_fileno, out_fileno):
| 64 | 64 | 157 | 18 | 45 | hashbrowncipher/gcmpipe | keypipe/__init__.py | Python | seal | seal | 64 | 77 | 64 | 64 | 7ae72a5b391ff1ed2432dc5ce222920d64ff932a | bigcode/the-stack | train |
a09fc65b4312883fbf9bc36f | train | function | def get_provider_by_name(name):
module_name = providers[name]
return get_provider_module(module_name)
| def get_provider_by_name(name):
| module_name = providers[name]
return get_provider_module(module_name)
| = b""
for i in range(0, 255):
t = hmac(prk, t + info + bytes([1 + i]), hashlib.sha256)
yield t
def get_provider_module(module_name):
return importlib.import_module(module_name)
def get_provider_by_name(name):
| 64 | 64 | 22 | 7 | 57 | hashbrowncipher/gcmpipe | keypipe/__init__.py | Python | get_provider_by_name | get_provider_by_name | 42 | 44 | 42 | 42 | 6cff4aa84fda7cde6207445d3b75a054992116c2 | bigcode/the-stack | train |
1c91494a8de5b35dd2bdcc04 | train | function | def _hkdf_generator(ikm, salt, info):
# Using SHA-512 and truncating its output is explicitly endorsed by
# https://eprint.iacr.org/2010/264.pdf , pg. 27
# Appendix D, #4
prk = hmac(salt, ikm, func=hashlib.sha512)[:32]
t = b""
for i in range(0, 255):
t = hmac(prk, t + info + bytes([1 + i... | def _hkdf_generator(ikm, salt, info):
# Using SHA-512 and truncating its output is explicitly endorsed by
# https://eprint.iacr.org/2010/264.pdf , pg. 27
# Appendix D, #4
| prk = hmac(salt, ikm, func=hashlib.sha512)[:32]
t = b""
for i in range(0, 255):
t = hmac(prk, t + info + bytes([1 + i]), hashlib.sha256)
yield t
| data, func).digest()
def _hkdf_generator(ikm, salt, info):
# Using SHA-512 and truncating its output is explicitly endorsed by
# https://eprint.iacr.org/2010/264.pdf , pg. 27
# Appendix D, #4
| 64 | 64 | 123 | 58 | 6 | hashbrowncipher/gcmpipe | keypipe/__init__.py | Python | _hkdf_generator | _hkdf_generator | 27 | 35 | 27 | 30 | 9e1afac253b665b9862f251097356418a2ebfc22 | bigcode/the-stack | train |
4f821c9a4171c967ede276fc | train | class | class InvalidKeyError(RuntimeError):
pass
| class InvalidKeyError(RuntimeError):
| pass
| ._aepipe import AEError
from .serialization import deserialize
from .serialization import serialize
providers = dict(
kms="keypipe.managers.kms",
vault="keypipe.managers.vault",
keyfile="keypipe.managers.keyfile",
)
class InvalidKeyError(RuntimeError):
| 64 | 64 | 10 | 7 | 57 | hashbrowncipher/gcmpipe | keypipe/__init__.py | Python | InvalidKeyError | InvalidKeyError | 19 | 20 | 19 | 19 | cb16f700adbcce8c152776e8ccdfba1695732d37 | bigcode/the-stack | train |
fd9c3819f06fbdb5ecbc2d76 | train | function | def derive_key(ikm, salt, context):
generator = _hkdf_generator(ikm, salt, context)
key = next(generator)
# Hugo Krawczyk. "Cryptographic Extraction and Key Derivation: The HKDF
# Scheme" https://eprint.iacr.org/2010/264.pdf p.21
# explicitly endorses disclosing other output from the KDF:
# "... | def derive_key(ikm, salt, context):
| generator = _hkdf_generator(ikm, salt, context)
key = next(generator)
# Hugo Krawczyk. "Cryptographic Extraction and Key Derivation: The HKDF
# Scheme" https://eprint.iacr.org/2010/264.pdf p.21
# explicitly endorses disclosing other output from the KDF:
# "Second, if the leakage of an output ... | + bytes([1 + i]), hashlib.sha256)
yield t
def get_provider_module(module_name):
return importlib.import_module(module_name)
def get_provider_by_name(name):
module_name = providers[name]
return get_provider_module(module_name)
def derive_key(ikm, salt, context):
| 64 | 64 | 184 | 11 | 53 | hashbrowncipher/gcmpipe | keypipe/__init__.py | Python | derive_key | derive_key | 47 | 61 | 47 | 47 | cbd598b93b3c134a5a3ae2373584879ae4eb3ba0 | bigcode/the-stack | train |
90bb9bc6fe00de457576faa9 | train | function | def unseal(provider_args, context, infile, outfile):
salt, checksum, providers = deserialize(infile)
for name, blob in providers:
if name not in provider_args:
continue
args = provider_args[name]
manager = get_provider_by_name(name)
plaintext = manager.read_blob(blob... | def unseal(provider_args, context, infile, outfile):
| salt, checksum, providers = deserialize(infile)
for name, blob in providers:
if name not in provider_args:
continue
args = provider_args[name]
manager = get_provider_by_name(name)
plaintext = manager.read_blob(blob, **args)
derived_checksum, key = derive_key(pla... | ()
_aepipe.seal(key, in_fileno, out_fileno)
@contextmanager
def closing_fd(fd):
try:
yield fd
finally:
os.close(fd)
class UnconfiguredProviderException(Exception):
pass
def unseal(provider_args, context, infile, outfile):
| 64 | 64 | 110 | 12 | 51 | hashbrowncipher/gcmpipe | keypipe/__init__.py | Python | unseal | unseal | 92 | 106 | 92 | 92 | fcfe468a413d198e494e7882a29eb632e79609f4 | bigcode/the-stack | train |
ddf30fe27d2420814cc87ce5 | train | function | def get_provider_module(module_name):
return importlib.import_module(module_name)
| def get_provider_module(module_name):
| return importlib.import_module(module_name)
| , ikm, func=hashlib.sha512)[:32]
t = b""
for i in range(0, 255):
t = hmac(prk, t + info + bytes([1 + i]), hashlib.sha256)
yield t
def get_provider_module(module_name):
| 64 | 64 | 16 | 7 | 56 | hashbrowncipher/gcmpipe | keypipe/__init__.py | Python | get_provider_module | get_provider_module | 38 | 39 | 38 | 38 | 2b9386312880427508da4a8d18e1822ba1f949ea | bigcode/the-stack | train |
98b1ec0943051b9deb74d6fa | train | function | @contextmanager
def closing_fd(fd):
try:
yield fd
finally:
os.close(fd)
| @contextmanager
def closing_fd(fd):
| try:
yield fd
finally:
os.close(fd)
| # a correct key, the checksum will match.
header = serialize(salt, checksum, {provider_name: blob})
out_fileno.write(header)
out_fileno.flush()
_aepipe.seal(key, in_fileno, out_fileno)
@contextmanager
def closing_fd(fd):
| 64 | 64 | 24 | 9 | 55 | hashbrowncipher/gcmpipe | keypipe/__init__.py | Python | closing_fd | closing_fd | 80 | 85 | 80 | 81 | 72473b63e6ff98642ea04c630c9f94608160c407 | bigcode/the-stack | train |
87ee8ef73ca5080c73e0c5c2 | train | function | def hmac(key, data, func):
return _hmac(key, data, func).digest()
| def hmac(key, data, func):
| return _hmac(key, data, func).digest()
| import deserialize
from .serialization import serialize
providers = dict(
kms="keypipe.managers.kms",
vault="keypipe.managers.vault",
keyfile="keypipe.managers.keyfile",
)
class InvalidKeyError(RuntimeError):
pass
def hmac(key, data, func):
| 64 | 64 | 22 | 9 | 54 | hashbrowncipher/gcmpipe | keypipe/__init__.py | Python | hmac | hmac | 23 | 24 | 23 | 23 | f7f3ac66f08a5d8f1e110842b19c76130e8a572e | bigcode/the-stack | train |
441e8492918236c26b4391be | train | class | class DictAverageMeter(object):
def __init__(self):
self.data = {}
self.count = 0
def update(self, new_input):
self.count += 1
if len(self.data) == 0:
for k, v in new_input.items():
if not isinstance(v, float):
raise NotImplemented... | class DictAverageMeter(object):
| def __init__(self):
self.data = {}
self.count = 0
def update(self, new_input):
self.count += 1
if len(self.data) == 0:
for k, v in new_input.items():
if not isinstance(v, float):
raise NotImplementedError("invalid data {}: {}".form... | (mode, key)
logger.add_image(name, preprocess(name, value), global_step)
else:
for idx in range(len(value)):
name = '{}/{}_{}'.format(mode, key, idx)
logger.add_image(name, preprocess(name, value[idx]), global_step)
class DictAverageMeter(object):
| 64 | 64 | 162 | 6 | 58 | Tangshengku/DDR-Net | utils.py | Python | DictAverageMeter | DictAverageMeter | 104 | 123 | 104 | 104 | 3974f2a237f83f60285cab2ebc2fbc2e0c27386a | bigcode/the-stack | train |
7ece2aad5911ecf6be6279e2 | train | function | def reduce_scalar_outputs(scalar_outputs):
world_size = get_world_size()
if world_size < 2:
return scalar_outputs
with torch.no_grad():
names = []
scalars = []
for k in sorted(scalar_outputs.keys()):
names.append(k)
scalars.append(scalar_outputs[k])
... | def reduce_scalar_outputs(scalar_outputs):
| world_size = get_world_size()
if world_size < 2:
return scalar_outputs
with torch.no_grad():
names = []
scalars = []
for k in sorted(scalar_outputs.keys()):
names.append(k)
scalars.append(scalar_outputs[k])
scalars = torch.stack(scalars, dim=0)... | .get_world_size()
if world_size == 1:
return
dist.barrier()
def get_world_size():
if not dist.is_available():
return 1
if not dist.is_initialized():
return 1
return dist.get_world_size()
def reduce_scalar_outputs(scalar_outputs):
| 64 | 64 | 157 | 8 | 56 | Tangshengku/DDR-Net | utils.py | Python | reduce_scalar_outputs | reduce_scalar_outputs | 184 | 202 | 184 | 184 | 37db2d427e604d96ffea4abfa65be0b8ea46fe5b | bigcode/the-stack | train |
581660f41ad01fae37be18ac | train | function | def set_random_seed(seed):
random.seed(seed)
np.random.seed(seed)
torch.manual_seed(seed)
torch.cuda.manual_seed_all(seed)
| def set_random_seed(seed):
| random.seed(seed)
np.random.seed(seed)
torch.manual_seed(seed)
torch.cuda.manual_seed_all(seed)
| up_factor, self.gamma, self.milestones, self.last_epoch))
return [
base_lr
* warmup_factor
* self.gamma ** bisect_right(self.milestones, self.last_epoch)
for base_lr in self.base_lrs
]
def set_random_seed(seed):
| 63 | 64 | 31 | 6 | 57 | Tangshengku/DDR-Net | utils.py | Python | set_random_seed | set_random_seed | 256 | 260 | 256 | 256 | 1108ed474cda2e554ec005fbdd949fa3edf36b99 | bigcode/the-stack | train |
59ae3a02e4510fd647f7e9d1 | train | function | def compute_metrics_for_each_image(metric_func):
def wrapper(depth_est, depth_gt, mask, *args):
batch_size = depth_gt.shape[0]
results = []
# compute result one by one
for idx in range(batch_size):
ret = metric_func(depth_est[idx], depth_gt[idx], mask[idx], *args)
... | def compute_metrics_for_each_image(metric_func):
| def wrapper(depth_est, depth_gt, mask, *args):
batch_size = depth_gt.shape[0]
results = []
# compute result one by one
for idx in range(batch_size):
ret = metric_func(depth_est[idx], depth_gt[idx], mask[idx], *args)
results.append(ret)
return torch.sta... | ("invalid data {}: {}".format(k, type(v)))
self.data[k] += v
def mean(self):
return {k: v / self.count for k, v in self.data.items()}
# a wrapper to compute metrics for each image individually
def compute_metrics_for_each_image(metric_func):
| 64 | 64 | 89 | 9 | 54 | Tangshengku/DDR-Net | utils.py | Python | compute_metrics_for_each_image | compute_metrics_for_each_image | 127 | 137 | 127 | 127 | a9713fff25daa5d25445b8baa5ec4a75965f1f6b | bigcode/the-stack | train |
381624aebdd27a6b117d0afe | train | function | def show_prob(depth_range,pro_volume,x,y):
depth=depth_range[0].detach().cpu().numpy()
prob=pro_volume[0].detach().cpu().numpy()
prob=prob[:,1,1]
depth=depth[:,1,1]
plt.plot(depth,prob)
plt.show()
plt.savefig('1.jpg')
| def show_prob(depth_range,pro_volume,x,y):
| depth=depth_range[0].detach().cpu().numpy()
prob=pro_volume[0].detach().cpu().numpy()
prob=prob[:,1,1]
depth=depth[:,1,1]
plt.plot(depth,prob)
plt.show()
plt.savefig('1.jpg')
|
end_header
%s
''' % (len(points), "".join(points)))
file.close()
print("save ply, fx:{}, fy:{}, cx:{}, cy:{}".format(fx, fy, cx, cy))
def show_prob(depth_range,pro_volume,x,y):
| 63 | 64 | 77 | 11 | 52 | Tangshengku/DDR-Net | utils.py | Python | show_prob | show_prob | 317 | 326 | 317 | 317 | 8ce28646ed6b5a79508f6408087a063759a25e16 | bigcode/the-stack | train |
e253e769b1e642fbb34d0776 | train | function | @make_recursive_func
def tensor2float(vars):
if isinstance(vars, float):
return vars
elif isinstance(vars, torch.Tensor):
return vars.data.item()
else:
raise NotImplementedError("invalid input type {} for tensor2float".format(type(vars)))
| @make_recursive_func
def tensor2float(vars):
| if isinstance(vars, float):
return vars
elif isinstance(vars, torch.Tensor):
return vars.data.item()
else:
raise NotImplementedError("invalid input type {} for tensor2float".format(type(vars)))
| elif isinstance(vars, tuple):
return tuple([wrapper(x) for x in vars])
elif isinstance(vars, dict):
return {k: wrapper(v) for k, v in vars.items()}
else:
return func(vars)
return wrapper
@make_recursive_func
def tensor2float(vars):
| 64 | 64 | 58 | 11 | 52 | Tangshengku/DDR-Net | utils.py | Python | tensor2float | tensor2float | 41 | 48 | 41 | 42 | 66d3c39bd34c1d6d207ae2fc581d7ce9474246b3 | bigcode/the-stack | train |
e48a9d88b5b588a2c74b8f80 | train | function | @make_recursive_func
def tocuda(vars):
if isinstance(vars, torch.Tensor):
return vars.to(torch.device("cuda"))
elif isinstance(vars, str):
return vars
else:
raise NotImplementedError("invalid input type {} for tensor2numpy".format(type(vars)))
| @make_recursive_func
def tocuda(vars):
| if isinstance(vars, torch.Tensor):
return vars.to(torch.device("cuda"))
elif isinstance(vars, str):
return vars
else:
raise NotImplementedError("invalid input type {} for tensor2numpy".format(type(vars)))
| if isinstance(vars, np.ndarray):
return vars
elif isinstance(vars, torch.Tensor):
return vars.detach().cpu().numpy().copy()
else:
raise NotImplementedError("invalid input type {} for tensor2numpy".format(type(vars)))
@make_recursive_func
def tocuda(vars):
| 63 | 64 | 60 | 10 | 53 | Tangshengku/DDR-Net | utils.py | Python | tocuda | tocuda | 61 | 68 | 61 | 62 | 49723a0276ab7e1a6057751b9c93b7d33ebddfa6 | bigcode/the-stack | train |
8451584b2086ff1792e0dcd9 | train | function | def get_world_size():
if not dist.is_available():
return 1
if not dist.is_initialized():
return 1
return dist.get_world_size()
| def get_world_size():
| if not dist.is_available():
return 1
if not dist.is_initialized():
return 1
return dist.get_world_size()
| rier) among all processes when
using distributed training
"""
if not dist.is_available():
return
if not dist.is_initialized():
return
world_size = dist.get_world_size()
if world_size == 1:
return
dist.barrier()
def get_world_size():
| 64 | 64 | 36 | 5 | 59 | Tangshengku/DDR-Net | utils.py | Python | get_world_size | get_world_size | 177 | 182 | 177 | 177 | e3a522da0c20c013eb6f3dca8fb2e0c47c620212 | bigcode/the-stack | train |
0f51f3699ee1157c12d76633 | train | function | def make_recursive_func(func):
def wrapper(vars):
if isinstance(vars, list):
return [wrapper(x) for x in vars]
elif isinstance(vars, tuple):
return tuple([wrapper(x) for x in vars])
elif isinstance(vars, dict):
return {k: wrapper(v) for k, v in vars.items(... | def make_recursive_func(func):
| def wrapper(vars):
if isinstance(vars, list):
return [wrapper(x) for x in vars]
elif isinstance(vars, tuple):
return tuple([wrapper(x) for x in vars])
elif isinstance(vars, dict):
return {k: wrapper(v) for k, v in vars.items()}
else:
re... | _nograd_func(func):
def wrapper(*f_args, **f_kwargs):
with torch.no_grad():
ret = func(*f_args, **f_kwargs)
return ret
return wrapper
# convert a function into recursive style to handle nested dict/list/tuple variables
def make_recursive_func(func):
| 64 | 64 | 83 | 6 | 57 | Tangshengku/DDR-Net | utils.py | Python | make_recursive_func | make_recursive_func | 27 | 38 | 27 | 27 | 42f8efb57a2963b60c53878e8cbb647b3f39725f | bigcode/the-stack | train |
eb97941fec1df753e8820289 | train | function | @make_recursive_func
def tensor2numpy(vars):
if isinstance(vars, np.ndarray):
return vars
elif isinstance(vars, torch.Tensor):
return vars.detach().cpu().numpy().copy()
else:
raise NotImplementedError("invalid input type {} for tensor2numpy".format(type(vars)))
| @make_recursive_func
def tensor2numpy(vars):
| if isinstance(vars, np.ndarray):
return vars
elif isinstance(vars, torch.Tensor):
return vars.detach().cpu().numpy().copy()
else:
raise NotImplementedError("invalid input type {} for tensor2numpy".format(type(vars)))
| tensor2float(vars):
if isinstance(vars, float):
return vars
elif isinstance(vars, torch.Tensor):
return vars.data.item()
else:
raise NotImplementedError("invalid input type {} for tensor2float".format(type(vars)))
@make_recursive_func
def tensor2numpy(vars):
| 63 | 64 | 64 | 11 | 52 | Tangshengku/DDR-Net | utils.py | Python | tensor2numpy | tensor2numpy | 51 | 58 | 51 | 52 | 8b7c70fe36d5b8c67280ad712ae773820845002d | bigcode/the-stack | train |
75b9f0cf7555502804193f00 | train | function | def synchronize():
"""
Helper function to synchronize (barrier) among all processes when
using distributed training
"""
if not dist.is_available():
return
if not dist.is_initialized():
return
world_size = dist.get_world_size()
if world_size == 1:
return
dist.b... | def synchronize():
| """
Helper function to synchronize (barrier) among all processes when
using distributed training
"""
if not dist.is_available():
return
if not dist.is_initialized():
return
world_size = dist.get_world_size()
if world_size == 1:
return
dist.barrier()
| [(error >= float(thres[0])) & (error <= float(thres[1]))]
if error.shape[0] == 0:
return torch.tensor(0, device=error.device, dtype=error.dtype)
return torch.mean(error)
import torch.distributed as dist
def synchronize():
| 64 | 64 | 71 | 3 | 60 | Tangshengku/DDR-Net | utils.py | Python | synchronize | synchronize | 163 | 175 | 163 | 163 | e6e3db153b5a0bad471cf9a93add277fa84402bc | bigcode/the-stack | train |
f9792416ee8f7297d7bb2346 | train | function | def save_images(logger, mode, images_dict, global_step):
images_dict = tensor2numpy(images_dict)
def preprocess(name, img):
if not (len(img.shape) == 3 or len(img.shape) == 4):
raise NotImplementedError("invalid img shape {}:{} in save_images".format(name, img.shape))
if len(img.sha... | def save_images(logger, mode, images_dict, global_step):
| images_dict = tensor2numpy(images_dict)
def preprocess(name, img):
if not (len(img.shape) == 3 or len(img.shape) == 4):
raise NotImplementedError("invalid img shape {}:{} in save_images".format(name, img.shape))
if len(img.shape) == 3:
img = img[:, np.newaxis, :, :]
... | , key)
logger.add_scalar(name, value, global_step)
else:
for idx in range(len(value)):
name = '{}/{}_{}'.format(mode, key, idx)
logger.add_scalar(name, value[idx], global_step)
def save_images(logger, mode, images_dict, global_step):
| 64 | 64 | 212 | 13 | 51 | Tangshengku/DDR-Net | utils.py | Python | save_images | save_images | 83 | 101 | 83 | 83 | 2ea0f0337ca563cc73adaeedc0e0436fb531cfe9 | bigcode/the-stack | train |
a67600459d70fa50c6c5249e | train | function | def generate_pointcloud(rgb, depth, ply_file, intr, scale=1.0):
"""
Generate a colored point cloud in PLY format from a color and a depth image.
Input:
rgb_file -- filename of color image
depth_file -- filename of depth image
ply_file -- filename of ply file
"""
fx, fy, cx, cy = intr[... | def generate_pointcloud(rgb, depth, ply_file, intr, scale=1.0):
| """
Generate a colored point cloud in PLY format from a color and a depth image.
Input:
rgb_file -- filename of color image
depth_file -- filename of depth image
ply_file -- filename of ply file
"""
fx, fy, cx, cy = intr[0, 0], intr[1, 1], intr[0, 2], intr[1, 2]
points = []
for... | np.ones_like(y)])
p3d = np.matmul(np.linalg.inv(intr), p2d)
depth = depth.reshape(1, nx * ny)
p3d *= depth
p3d = np.transpose(p3d, (1, 0))
p3d = p3d.reshape(ny, nx, 3).astype(np.float32)
return p3d
def generate_pointcloud(rgb, depth, ply_file, intr, scale=1.0):
| 105 | 105 | 352 | 19 | 85 | Tangshengku/DDR-Net | utils.py | Python | generate_pointcloud | generate_pointcloud | 277 | 313 | 277 | 278 | 9f90670b0b9c06e689d464906628ae5c2efc14ee | bigcode/the-stack | train |
cb8a7f23f70b7fe8c7f78aba | train | function | @make_nograd_func
@compute_metrics_for_each_image
def Thres_metrics(depth_est, depth_gt, mask, thres):
assert isinstance(thres, (int, float))
depth_est, depth_gt = depth_est[mask], depth_gt[mask]
errors = torch.abs(depth_est - depth_gt)
err_mask = errors > thres
return torch.mean(err_mask.float())
| @make_nograd_func
@compute_metrics_for_each_image
def Thres_metrics(depth_est, depth_gt, mask, thres):
| assert isinstance(thres, (int, float))
depth_est, depth_gt = depth_est[mask], depth_gt[mask]
errors = torch.abs(depth_est - depth_gt)
err_mask = errors > thres
return torch.mean(err_mask.float())
| ret = metric_func(depth_est[idx], depth_gt[idx], mask[idx], *args)
results.append(ret)
return torch.stack(results).mean()
return wrapper
@make_nograd_func
@compute_metrics_for_each_image
def Thres_metrics(depth_est, depth_gt, mask, thres):
| 64 | 64 | 84 | 28 | 35 | Tangshengku/DDR-Net | utils.py | Python | Thres_metrics | Thres_metrics | 140 | 147 | 140 | 142 | 3db46ad28aa8a886c6aae6ea924055081be8336c | bigcode/the-stack | train |
c810b5fe9f42b9db73f48317 | train | function | def save_scalars(logger, mode, scalar_dict, global_step):
scalar_dict = tensor2float(scalar_dict)
for key, value in scalar_dict.items():
if not isinstance(value, (list, tuple)):
name = '{}/{}'.format(mode, key)
logger.add_scalar(name, value, global_step)
else:
... | def save_scalars(logger, mode, scalar_dict, global_step):
| scalar_dict = tensor2float(scalar_dict)
for key, value in scalar_dict.items():
if not isinstance(value, (list, tuple)):
name = '{}/{}'.format(mode, key)
logger.add_scalar(name, value, global_step)
else:
for idx in range(len(value)):
name = '{}/... | if isinstance(vars, torch.Tensor):
return vars.to(torch.device("cuda"))
elif isinstance(vars, str):
return vars
else:
raise NotImplementedError("invalid input type {} for tensor2numpy".format(type(vars)))
def save_scalars(logger, mode, scalar_dict, global_step):
| 63 | 64 | 105 | 14 | 49 | Tangshengku/DDR-Net | utils.py | Python | save_scalars | save_scalars | 71 | 80 | 71 | 71 | dc9cc1b63db955a2d0f177a3e0e89f3d539a972b | bigcode/the-stack | train |
cab7ea385f1d19af1c203022 | train | class | class WarmupMultiStepLR(torch.optim.lr_scheduler._LRScheduler):
def __init__(
self,
optimizer,
milestones,
gamma=0.1,
warmup_factor=1.0 / 3,
warmup_iters=500,
warmup_method="linear",
last_epoch=-1,
):
if not list(milestones) == sorted(miles... | class WarmupMultiStepLR(torch.optim.lr_scheduler._LRScheduler):
| def __init__(
self,
optimizer,
milestones,
gamma=0.1,
warmup_factor=1.0 / 3,
warmup_iters=500,
warmup_method="linear",
last_epoch=-1,
):
if not list(milestones) == sorted(milestones):
raise ValueError(
"Milestone... | _rank() == 0:
# only main process gets accumulated, so only divide by
# world_size in this case
scalars /= world_size
reduced_scalars = {k: v for k, v in zip(names, scalars)}
return reduced_scalars
import torch
from bisect import bisect_right
# FIXME ideally this would ... | 122 | 122 | 408 | 15 | 106 | Tangshengku/DDR-Net | utils.py | Python | WarmupMultiStepLR | WarmupMultiStepLR | 209 | 253 | 209 | 209 | ff04de2ced1a538a2ccb20d51f81449f9c5f65f7 | bigcode/the-stack | train |
eb1e494e7c030b0c7dc3f240 | train | function | def print_args(args):
print("################################ args ################################")
for k, v in args.__dict__.items():
print("{0: <10}\t{1: <30}\t{2: <20}".format(k, str(v), str(type(v))))
print("########################################################################")
| def print_args(args):
| print("################################ args ################################")
for k, v in args.__dict__.items():
print("{0: <10}\t{1: <30}\t{2: <20}".format(k, str(v), str(type(v))))
print("########################################################################")
| import numpy as np
import torchvision.utils as vutils
import torch, random
import torch.nn.functional as F
import matplotlib.pyplot as plt
# print arguments
def print_args(args):
| 39 | 64 | 63 | 5 | 33 | Tangshengku/DDR-Net | utils.py | Python | print_args | print_args | 9 | 13 | 9 | 9 | 30b33a86336777c907d9b486abe11e0f417d8576 | bigcode/the-stack | train |
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