id int64 0 190k | prompt stringlengths 21 13.4M | docstring stringlengths 1 12k ⌀ |
|---|---|---|
187,782 | import math
import numbers
import random
from fractions import Fraction
from decimal import Decimal
from itertools import groupby, repeat
from bisect import bisect_left, bisect_right
from math import hypot, sqrt, fabs, exp, erf, tau, log, fsum
from operator import itemgetter
from collections import Counter, namedtuple
... | Return the high median of data. When the number of data points is odd, the middle value is returned. When it is even, the larger of the two middle values is returned. >>> median_high([1, 3, 5]) 3 >>> median_high([1, 3, 5, 7]) 5 |
187,783 | import math
import numbers
import random
from fractions import Fraction
from decimal import Decimal
from itertools import groupby, repeat
from bisect import bisect_left, bisect_right
from math import hypot, sqrt, fabs, exp, erf, tau, log, fsum
from operator import itemgetter
from collections import Counter, namedtuple
... | Return the 50th percentile (median) of grouped continuous data. >>> median_grouped([1, 2, 2, 3, 4, 4, 4, 4, 4, 5]) 3.7 >>> median_grouped([52, 52, 53, 54]) 52.5 This calculates the median as the 50th percentile, and should be used when your data is continuous and grouped. In the above example, the values 1, 2, 3, etc. ... |
187,784 | import math
import numbers
import random
from fractions import Fraction
from decimal import Decimal
from itertools import groupby, repeat
from bisect import bisect_left, bisect_right
from math import hypot, sqrt, fabs, exp, erf, tau, log, fsum
from operator import itemgetter
from collections import Counter, namedtuple
... | Return the most common data point from discrete or nominal data. ``mode`` assumes discrete data, and returns a single value. This is the standard treatment of the mode as commonly taught in schools: >>> mode([1, 1, 2, 3, 3, 3, 3, 4]) 3 This also works with nominal (non-numeric) data: >>> mode(["red", "blue", "blue", "r... |
187,785 | import math
import numbers
import random
from fractions import Fraction
from decimal import Decimal
from itertools import groupby, repeat
from bisect import bisect_left, bisect_right
from math import hypot, sqrt, fabs, exp, erf, tau, log, fsum
from operator import itemgetter
from collections import Counter, namedtuple
... | Return a list of the most frequently occurring values. Will return more than one result if there are multiple modes or an empty list if *data* is empty. >>> multimode('aabbbbbbbbcc') ['b'] >>> multimode('aabbbbccddddeeffffgg') ['b', 'd', 'f'] >>> multimode('') [] |
187,786 | import math
import numbers
import random
from fractions import Fraction
from decimal import Decimal
from itertools import groupby, repeat
from bisect import bisect_left, bisect_right
from math import hypot, sqrt, fabs, exp, erf, tau, log, fsum
from operator import itemgetter
from collections import Counter, namedtuple
... | Divide *data* into *n* continuous intervals with equal probability. Returns a list of (n - 1) cut points separating the intervals. Set *n* to 4 for quartiles (the default). Set *n* to 10 for deciles. Set *n* to 100 for percentiles which gives the 99 cuts points that separate *data* in to 100 equal sized groups. The *da... |
187,787 | import math
import numbers
import random
from fractions import Fraction
from decimal import Decimal
from itertools import groupby, repeat
from bisect import bisect_left, bisect_right
from math import hypot, sqrt, fabs, exp, erf, tau, log, fsum
from operator import itemgetter
from collections import Counter, namedtuple
... | Return the square root of the population variance. See ``pvariance`` for arguments and other details. >>> pstdev([1.5, 2.5, 2.5, 2.75, 3.25, 4.75]) 0.986893273527251 |
187,788 | import math
import numbers
import random
from fractions import Fraction
from decimal import Decimal
from itertools import groupby, repeat
from bisect import bisect_left, bisect_right
from math import hypot, sqrt, fabs, exp, erf, tau, log, fsum
from operator import itemgetter
from collections import Counter, namedtuple
... | Covariance Return the sample covariance of two inputs *x* and *y*. Covariance is a measure of the joint variability of two inputs. >>> x = [1, 2, 3, 4, 5, 6, 7, 8, 9] >>> y = [1, 2, 3, 1, 2, 3, 1, 2, 3] >>> covariance(x, y) 0.75 >>> z = [9, 8, 7, 6, 5, 4, 3, 2, 1] >>> covariance(x, z) -7.5 >>> covariance(z, x) -7.5 |
187,789 | import math
import numbers
import random
from fractions import Fraction
from decimal import Decimal
from itertools import groupby, repeat
from bisect import bisect_left, bisect_right
from math import hypot, sqrt, fabs, exp, erf, tau, log, fsum
from operator import itemgetter
from collections import Counter, namedtuple
... | Pearson's correlation coefficient Return the Pearson's correlation coefficient for two inputs. Pearson's correlation coefficient *r* takes values between -1 and +1. It measures the strength and direction of the linear relationship, where +1 means very strong, positive linear relationship, -1 very strong, negative linea... |
187,790 | import math
import numbers
import random
from fractions import Fraction
from decimal import Decimal
from itertools import groupby, repeat
from bisect import bisect_left, bisect_right
from math import hypot, sqrt, fabs, exp, erf, tau, log, fsum
from operator import itemgetter
from collections import Counter, namedtuple
... | Slope and intercept for simple linear regression. Return the slope and intercept of simple linear regression parameters estimated using ordinary least squares. Simple linear regression describes relationship between an independent variable *x* and a dependent variable *y* in terms of linear function: y = slope * x + in... |
187,791 | import math
import numbers
import random
from fractions import Fraction
from decimal import Decimal
from itertools import groupby, repeat
from bisect import bisect_left, bisect_right
from math import hypot, sqrt, fabs, exp, erf, tau, log, fsum
from operator import itemgetter
from collections import Counter, namedtuple
... | null |
187,812 | import os
import re
import time
import random
import socket
import datetime
import urllib.parse
from email._parseaddr import quote
from email._parseaddr import AddressList as _AddressList
from email._parseaddr import mktime_tz
from email._parseaddr import parsedate, parsedate_tz, _parsedate_tz
from email.charset import... | null |
187,823 | from base64 import b64encode
from binascii import b2a_base64, a2b_base64
NL = '\n'
EMPTYSTRING = ''
def decode(string):
"""Decode a raw base64 string, returning a bytes object.
This function does not parse a full MIME header value encoded with
base64 (like =?iso-8859-1?b?bmloISBuaWgh?=) -- please use the hi... | r"""Encode a string with base64. Each line will be wrapped at, at most, maxlinelen characters (defaults to 76 characters). Each line of encoded text will end with eol, which defaults to "\n". Set this to "\r\n" if you will be using the result of this function directly in an email. |
187,836 | import re
import base64
import binascii
import functools
from string import ascii_letters, digits
from email import errors
def decode(ew):
"""Decode encoded word and return (string, charset, lang, defects) tuple.
An RFC 2047/2243 encoded word has the form:
=?charset*lang?cte?encoded_string?=
where '... | null |
187,838 | import re
import sys
import urllib.parse
from string import hexdigits
from operator import itemgetter
from email import _encoded_words as _ew
from email import errors
from email import utils
CFWS_LEADER = WSP | set('(')
class AddressList(TokenList):
token_type = 'address-list'
def addresses(self):
ret... | address_list = (address *("," address)) / obs-addr-list obs-addr-list = *([CFWS] ",") address *("," [address / CFWS]) We depart from the formal grammar here by continuing to parse until the end of the input, assuming the input to be entirely composed of an address-list. This is always true in email parsing, and allows ... |
187,839 | import re
import sys
import urllib.parse
from string import hexdigits
from operator import itemgetter
from email import _encoded_words as _ew
from email import errors
from email import utils
class MessageID(MsgID):
token_type = 'message-id'
class InvalidMessageID(MessageID):
token_type = 'invalid-message-id'
... | message-id = "Message-ID:" msg-id CRLF |
187,840 | import re
import sys
import urllib.parse
from string import hexdigits
from operator import itemgetter
from email import _encoded_words as _ew
from email import errors
from email import utils
CFWS_LEADER = WSP | set('(')
class MIMEVersion(TokenList):
token_type = 'mime-version'
major = None
minor = None
cl... | mime-version = [CFWS] 1*digit [CFWS] "." [CFWS] 1*digit [CFWS] |
187,841 | import re
import sys
import urllib.parse
from string import hexdigits
from operator import itemgetter
from email import _encoded_words as _ew
from email import errors
from email import utils
class ContentType(ParameterizedHeaderValue):
token_type = 'content-type'
as_ew_allowed = False
maintype = 'text'
... | maintype "/" subtype *( ";" parameter ) The maintype and substype are tokens. Theoretically they could be checked against the official IANA list + x-token, but we don't do that. |
187,842 | import re
import sys
import urllib.parse
from string import hexdigits
from operator import itemgetter
from email import _encoded_words as _ew
from email import errors
from email import utils
class ContentDisposition(ParameterizedHeaderValue):
token_type = 'content-disposition'
as_ew_allowed = False
conten... | disposition-type *( ";" parameter ) |
187,843 | import re
import sys
import urllib.parse
from string import hexdigits
from operator import itemgetter
from email import _encoded_words as _ew
from email import errors
from email import utils
PHRASE_ENDS = SPECIALS - set('."(')
class ContentTransferEncoding(TokenList):
token_type = 'content-transfer-encoding'
... | mechanism |
187,844 | import re
import sys
import urllib.parse
from string import hexdigits
from operator import itemgetter
from email import _encoded_words as _ew
from email import errors
from email import utils
SPECIALS = set(r'()<>@,:;.\"[]')
class Terminal(str):
as_ew_allowed = True
ew_combine_allowed = True
syntactic_brea... | Return string of contents of parse_tree folded according to RFC rules. |
187,845 | import abc
from email import header
from email import charset as _charset
from email.utils import _has_surrogates
def _append_doc(doc, added_doc):
def _extend_docstrings(cls):
if cls.__doc__ and cls.__doc__.startswith('+'):
cls.__doc__ = _append_doc(cls.__bases__[0].__doc__, cls.__doc__)
for name, attr... | null |
187,859 | from builtins import open as _builtin_open
from codecs import lookup, BOM_UTF8
import collections
import functools
from io import TextIOWrapper
import itertools as _itertools
import re
import sys
from token import *
from token import EXACT_TOKEN_TYPES
import token
def group(*choices): return '(' + '|'.join(choices) + '... | null |
187,860 | from builtins import open as _builtin_open
from codecs import lookup, BOM_UTF8
import collections
import functools
from io import TextIOWrapper
import itertools as _itertools
import re
import sys
from token import *
from token import EXACT_TOKEN_TYPES
import token
for t in _all_string_prefixes():
for u in (t + '"',... | null |
187,861 | from builtins import open as _builtin_open
from codecs import lookup, BOM_UTF8
import collections
import functools
from io import TextIOWrapper
import itertools as _itertools
import re
import sys
from token import *
from token import EXACT_TOKEN_TYPES
import token
class Untokenizer:
def __init__(self):
self... | Transform tokens back into Python source code. It returns a bytes object, encoded using the ENCODING token, which is the first token sequence output by tokenize. Each element returned by the iterable must be a token sequence with at least two elements, a token number and token value. If only two tokens are passed, the ... |
187,876 | import re
from tkinter import StringVar, TclError
from idlelib.searchbase import SearchDialogBase
from idlelib import searchengine
def replace(text, insert_tags=None):
"""Create or reuse a singleton ReplaceDialog instance.
The singleton dialog saves user entries and preferences
across instances.
Args:
... | null |
187,877 | from idlelib.delegator import Delegator
from idlelib.redirector import WidgetRedirector
class Percolator:
def __init__(self, text):
# XXX would be nice to inherit from Delegator
self.text = text
self.redir = WidgetRedirector(text)
self.top = self.bottom = Delegator(text)
self... | null |
187,891 | import io
import os
import shlex
import sys
import tempfile
import tokenize
from tkinter import filedialog
from tkinter import messagebox
from tkinter.simpledialog import askstring
import idlelib
from idlelib.config import idleConf
from idlelib.util import py_extensions
class IOBinding:
# One instance per editor Window... | null |
187,892 | import importlib.abc
import importlib.util
import os
import platform
import re
import string
import sys
import tokenize
import traceback
import webbrowser
from tkinter import *
from tkinter.font import Font
from tkinter.ttk import Scrollbar
from tkinter import simpledialog
from tkinter import messagebox
from idlelib.co... | Format sys.version_info to produce the Sphinx version string used to install the chm docs |
187,893 | import importlib.abc
import importlib.util
import os
import platform
import re
import string
import sys
import tokenize
import traceback
import webbrowser
from tkinter import *
from tkinter.font import Font
from tkinter.ttk import Scrollbar
from tkinter import simpledialog
from tkinter import messagebox
from idlelib.co... | null |
187,894 | import importlib.abc
import importlib.util
import os
import platform
import re
import string
import sys
import tokenize
import traceback
import webbrowser
from tkinter import *
from tkinter.font import Font
from tkinter.ttk import Scrollbar
from tkinter import simpledialog
from tkinter import messagebox
from idlelib.co... | Return a line's indentation as (# chars, effective # of spaces). The effective # of spaces is the length after properly "expanding" the tabs into spaces, as done by str.expandtabs(tabwidth). |
187,895 | import importlib.abc
import importlib.util
import os
import platform
import re
import string
import sys
import tokenize
import traceback
import webbrowser
from tkinter import *
from tkinter.font import Font
from tkinter.ttk import Scrollbar
from tkinter import simpledialog
from tkinter import messagebox
from idlelib.co... | null |
187,896 | import importlib.abc
import importlib.util
import os
import platform
import re
import string
import sys
import tokenize
import traceback
import webbrowser
from tkinter import *
from tkinter.font import Font
from tkinter.ttk import Scrollbar
from tkinter import simpledialog
from tkinter import messagebox
from idlelib.co... | null |
187,897 | import importlib.abc
import importlib.util
import os
import platform
import re
import string
import sys
import tokenize
import traceback
import webbrowser
from tkinter import *
from tkinter.font import Font
from tkinter.ttk import Scrollbar
from tkinter import simpledialog
from tkinter import messagebox
from idlelib.co... | null |
187,898 | import contextlib
import functools
import io
import linecache
import queue
import sys
import textwrap
import time
import traceback
import _thread as thread
import threading
import warnings
import idlelib
from idlelib import autocomplete
from idlelib import calltip
from idlelib import debugger_r
from idlelib import ... | Process any tk events that are ready to be dispatched if tkinter has been imported, a tcl interpreter has been created and tk has been loaded. |
187,899 | import contextlib
import functools
import io
import linecache
import queue
import sys
import textwrap
import time
import traceback
import _thread as thread
import threading
import warnings
import idlelib
from idlelib import autocomplete
from idlelib import calltip
from idlelib import debugger_r
from idlelib import ... | null |
187,900 | import contextlib
import functools
import io
import linecache
import queue
import sys
import textwrap
import time
import traceback
import _thread as thread
import threading
import warnings
import idlelib
from idlelib import autocomplete
from idlelib import calltip
from idlelib import debugger_r
from idlelib import ... | null |
187,901 | import contextlib
import functools
import io
import linecache
import queue
import sys
import textwrap
import time
import traceback
import _thread as thread
import threading
import warnings
import idlelib
from idlelib import autocomplete
from idlelib import calltip
from idlelib import debugger_r
from idlelib import ... | Exit subprocess, possibly after first clearing exit functions. If config-main.cfg/.def 'General' 'delete-exitfunc' is True, then any functions registered with atexit will be removed before exiting. (VPython support) |
187,902 | import contextlib
import functools
import io
import linecache
import queue
import sys
import textwrap
import time
import traceback
import _thread as thread
import threading
import warnings
import idlelib
from idlelib import autocomplete
from idlelib import calltip
from idlelib import debugger_r
from idlelib import ... | Install wrappers to always add 30 to the recursion limit. |
187,903 | import contextlib
import functools
import io
import linecache
import queue
import sys
import textwrap
import time
import traceback
import _thread as thread
import threading
import warnings
import idlelib
from idlelib import autocomplete
from idlelib import calltip
from idlelib import debugger_r
from idlelib import ... | Uninstall the recursion limit wrappers from the sys module. IDLE only uses this for tests. Users can import run and call this to remove the wrapping. |
187,904 | import os
from tkinter import messagebox
class FileList:
def __init__(self, root):
def open(self, filename, action=None):
def gotofileline(self, filename, lineno=None):
def new(self, filename=None):
def close_all_callback(self, *args, **kwds):
def unregister_maybe_terminate(self, edit):
... | null |
187,905 | import contextlib
import functools
import itertools
import tkinter as tk
from tkinter.font import Font
from idlelib.config import idleConf
from idlelib.delegator import Delegator
from idlelib import macosx
def get_lineno(text, index):
"""Return the line number of an index in a Tk text widget."""
text_index = te... | Return the number of the last line in a Tk text widget. |
187,906 | import contextlib
import functools
import itertools
import tkinter as tk
from tkinter.font import Font
from idlelib.config import idleConf
from idlelib.delegator import Delegator
from idlelib import macosx
The provided code snippet includes necessary dependencies for implementing the `get_displaylines` function. Write... | Display height, in lines, of a logical line in a Tk text widget. |
187,907 | import contextlib
import functools
import itertools
import tkinter as tk
from tkinter.font import Font
from idlelib.config import idleConf
from idlelib.delegator import Delegator
from idlelib import macosx
The provided code snippet includes necessary dependencies for implementing the `get_widget_padding` function. Wri... | Get the total padding of a Tk widget, including its border. |
187,908 | import contextlib
import functools
import itertools
import tkinter as tk
from tkinter.font import Font
from idlelib.config import idleConf
from idlelib.delegator import Delegator
from idlelib import macosx
def temp_enable_text_widget(text):
text.configure(state=tk.NORMAL)
try:
yield
finally:
... | null |
187,909 | import contextlib
import functools
import itertools
import tkinter as tk
from tkinter.font import Font
from idlelib.config import idleConf
from idlelib.delegator import Delegator
from idlelib import macosx
class LineNumbers(BaseSideBar):
"""Line numbers support for editor windows."""
def __init__(self, editwin)... | null |
187,914 | import os
import sys
import webbrowser
from platform import python_version, architecture
from tkinter import Toplevel, Frame, Label, Button, PhotoImage
from tkinter import SUNKEN, TOP, BOTTOM, LEFT, X, BOTH, W, EW, NSEW, E
from idlelib import textview
def architecture(executable=sys.executable, bits='', linkage=''):
... | Return bits for platform. |
187,928 | import builtins
import keyword
import re
import time
from idlelib.config import idleConf
from idlelib.delegator import Delegator
def any(name, alternates):
prog = make_pat()
def make_pat():
kw = r"\b" + any("KEYWORD", keyword.kwlist) + r"\b"
match_softkw = (
r"^[ \t]*" + # at beginning of line + possi... | null |
187,929 | import builtins
import keyword
import re
import time
from idlelib.config import idleConf
from idlelib.delegator import Delegator
The provided code snippet includes necessary dependencies for implementing the `matched_named_groups` function. Write a Python function `def matched_named_groups(re_match)` to solve the foll... | Get only the non-empty named groups from an re.Match object. |
187,930 | import builtins
import keyword
import re
import time
from idlelib.config import idleConf
from idlelib.delegator import Delegator
def color_config(text):
"""Set color options of Text widget.
If ColorDelegator is used, this should be called first.
"""
# Called from htest, TextFrame, Editor, and Turtledemo... | null |
187,933 | import string
from idlelib.delegator import Delegator
class UndoDelegator(Delegator):
def __init__(self):
def setdelegate(self, delegate):
def dump_event(self, event):
def reset_undo(self):
def set_saved(self, flag):
def get_saved(self):
def set_saved_change_hook(self, hook):
def... | null |
187,948 | import os
import sys
import importlib.util
import py_compile
import struct
import filecmp
from functools import partial
from pathlib import Path
def compile_dir(dir, maxlevels=None, ddir=None, force=False,
rx=None, quiet=0, legacy=False, optimize=-1, workers=1,
invalidation_mode=None, *,... | Byte-compile all module on sys.path. Arguments (all optional): skip_curdir: if true, skip current directory (default True) maxlevels: max recursion level (default 0) force: as for compile_dir() (default False) quiet: as for compile_dir() (default 0) legacy: as for compile_dir() (default False) optimize: as for compile_... |
187,949 | import io
import math
import mmap
import os
import re
import struct
import sys
import time
from collections import deque, OrderedDict
from importlib.util import spec_from_file_location, decode_source
from os import path
from types import CodeType
def _float_equals(a, b):
if math.isnan(a) and math.isnan(b):
... | null |
187,950 | import io
import math
import mmap
import os
import re
import struct
import sys
import time
from collections import deque, OrderedDict
from importlib.util import spec_from_file_location, decode_source
from os import path
from types import CodeType
def _align_file(file, align=8):
len = file.tell()
padding = (((l... | null |
187,951 | import io
import math
import mmap
import os
import re
import struct
import sys
import time
from collections import deque, OrderedDict
from importlib.util import spec_from_file_location, decode_source
from os import path
from types import CodeType
class PyIceImporter:
def __init__(self, import_path):
self.pa... | null |
187,952 | import io
import math
import mmap
import os
import re
import struct
import sys
import time
from collections import deque, OrderedDict
from importlib.util import spec_from_file_location, decode_source
from os import path
from types import CodeType
class PyIceImporter:
def __init__(self, import_path):
def find_... | null |
187,964 | from datetime import tzinfo, timedelta, datetime
import time as _time
def first_sunday_on_or_after(dt):
days_to_go = 6 - dt.weekday()
if days_to_go:
dt += timedelta(days_to_go)
return dt
DSTSTART_2007 = datetime(1, 3, 8, 2)
DSTEND_2007 = datetime(1, 11, 1, 2)
DSTSTART_1987_2006 = datetime(1, 4, 1, 2... | null |
187,974 | import os
import re
import sys
import getopt
from string import ascii_letters
from os.path import join, splitext, abspath, exists
from collections import defaultdict
checkers = {}
checker_props = {'severity': 1, 'falsepositives': False}
The provided code snippet includes necessary dependencies for implementing the `ch... | Decorator to register a function as a checker. |
187,975 | import os
import re
import sys
import getopt
from string import ascii_letters
from os.path import join, splitext, abspath, exists
from collections import defaultdict
The provided code snippet includes necessary dependencies for implementing the `check_syntax` function. Write a Python function `def check_syntax(fn, lin... | Check Python examples for valid syntax. |
187,976 | import os
import re
import sys
import getopt
from string import ascii_letters
from os.path import join, splitext, abspath, exists
from collections import defaultdict
seems_directive_re = re.compile(r'(?<!\.)\.\. %s([^a-z:]|:(?!:))' % all_directives)
default_role_re = re.compile(r'(^| )`\w([^`]*?\w)?`($| )')
The provid... | Check for suspicious reST constructs. |
187,977 | import os
import re
import sys
import getopt
from string import ascii_letters
from os.path import join, splitext, abspath, exists
from collections import defaultdict
The provided code snippet includes necessary dependencies for implementing the `check_whitespace` function. Write a Python function `def check_whitespace... | Check for whitespace and line length issues. |
187,978 | import os
import re
import sys
import getopt
from string import ascii_letters
from os.path import join, splitext, abspath, exists
from collections import defaultdict
The provided code snippet includes necessary dependencies for implementing the `check_line_length` function. Write a Python function `def check_line_leng... | Check for line length; this checker is not run by default. |
187,979 | import os
import re
import sys
import getopt
from string import ascii_letters
from os.path import join, splitext, abspath, exists
from collections import defaultdict
leaked_markup_re = re.compile(r'[a-z]::\s|`|\.\.\s*\w+:')
The provided code snippet includes necessary dependencies for implementing the `check_leaked_ma... | Check HTML files for leaked reST markup; this only works if the HTML files have been built. |
187,980 | import os
import re
import sys
import getopt
from string import ascii_letters
from os.path import join, splitext, abspath, exists
from collections import defaultdict
def hide_literal_blocks(lines):
"""Tool to remove literal blocks from given lines.
It yields empty lines in place of blocks, so line numbers are
... | r"""Check for missing 'backslash-space' between a code sample a letter. Good: ``Point``\ s Bad: ``Point``s |
187,981 | from pygments.lexer import RegexLexer, bygroups, include
from pygments.token import Comment, Generic, Keyword, Name, Operator, Punctuation, Text
from sphinx.highlighting import lexers
class PEGLexer(RegexLexer):
"""Pygments Lexer for PEG grammar (.gram) files
This lexer strips the following elements from the gr... | null |
187,982 | import re
import io
from os import getenv, path
from time import asctime
from pprint import pformat
from docutils.io import StringOutput
from docutils.parsers.rst import Directive
from docutils.utils import new_document
from docutils import nodes, utils
from sphinx import addnodes
from sphinx.builders import Builder
fr... | null |
187,986 | import json
import os.path
from docutils.nodes import definition_list_item
from sphinx.addnodes import glossary
from sphinx.util import logging
def process_glossary_nodes(app, doctree, fromdocname):
if app.builder.format != 'html':
return
terms = {}
for node in doctree.traverse(glossary):
fo... | null |
187,987 | from os import path
from docutils import nodes
from docutils.parsers.rst import directives
from docutils.parsers.rst import Directive
from docutils.statemachine import StringList
import csv
from sphinx import addnodes
from sphinx.domains.c import CObject
def init_annotations(app):
def setup(app):
app.add_config_va... | null |
187,988 | import pathlib
import re
from html.entities import codepoint2name
from sphinx.util.logging import getLogger
def escape_for_chm(app, pagename, templatename, context, doctree):
# only works for .chm output
if getattr(app.builder, 'name', '') != 'htmlhelp':
return
# escape the `body` part to 7-bit ASCI... | null |
187,989 | import os
import sys
from pathlib import Path
from pygments.lexer import RegexLexer, bygroups, include, words
from pygments.token import (Comment, Generic, Keyword, Name, Operator,
Punctuation, Text)
from asdl import builtin_types
from sphinx.highlighting import lexers
class ASDLLexer(RegexL... | null |
187,995 | import copy
import math
import torch
import torch.nn as nn
import torch.nn.functional as F
from torch.distributions import Normal
def create_masks(
input_size, hidden_size, n_hidden, input_order="sequential", input_degrees=None
):
# MADE paper sec 4:
# degrees of connections between layers -- ensure at mos... | null |
187,996 | from functools import partial
from inspect import isfunction
import numpy as np
import torch
from torch import nn, einsum
import torch.nn.functional as F
def default(val, d):
if val is not None:
return val
return d() if isfunction(d) else d | null |
187,997 | from functools import partial
from inspect import isfunction
import numpy as np
import torch
from torch import nn, einsum
import torch.nn.functional as F
def extract(a, t, x_shape):
b, *_ = t.shape
out = a.gather(-1, t)
return out.reshape(b, *((1,) * (len(x_shape) - 1))) | null |
187,998 | from functools import partial
from inspect import isfunction
import numpy as np
import torch
from torch import nn, einsum
import torch.nn.functional as F
def noise_like(shape, device, repeat=False):
repeat_noise = lambda: torch.randn((1, *shape[1:]), device=device).repeat(
shape[0], *((1,) * (len(shape) - ... | null |
187,999 | from functools import partial
from inspect import isfunction
import numpy as np
import torch
from torch import nn, einsum
import torch.nn.functional as F
The provided code snippet includes necessary dependencies for implementing the `cosine_beta_schedule` function. Write a Python function `def cosine_beta_schedule(tim... | cosine schedule as proposed in https://openreview.net/forum?id=-NEXDKk8gZ |
188,000 | import json
import os
from pathlib import Path
from functools import lru_cache
import numpy as np
import pandas as pd
from gluonts.dataset.field_names import FieldName
from gluonts.dataset.repository._util import metadata, save_to_file
from gluonts.time_feature.holiday import squared_exponential_kernel
from pts.feature... | null |
188,001 | from typing import List
import numpy as np
import pandas as pd
from pandas.tseries.frequencies import to_offset
from gluonts.core.component import validated
from gluonts.time_feature import TimeFeature, norm_freq_str
class FourierDateFeatures(TimeFeature):
def __init__(self, freq: str) -> None:
super().__in... | null |
188,002 | from typing import List, Optional
from pandas.tseries.frequencies import to_offset
def lags_for_fourier_time_features_from_frequency(
freq_str: str, num_lags: Optional[int] = None
) -> List[int]:
offset = to_offset(freq_str)
multiple, granularity = offset.n, offset.name
if granularity == "M":
... | null |
188,003 |
The provided code snippet includes necessary dependencies for implementing the `broadcast_shape` function. Write a Python function `def broadcast_shape(*shapes, **kwargs)` to solve the following problem:
Similar to ``np.broadcast()`` but for shapes. Equivalent to ``np.broadcast(*map(np.empty, shapes)).shape``. :param... | Similar to ``np.broadcast()`` but for shapes. Equivalent to ``np.broadcast(*map(np.empty, shapes)).shape``. :param tuple shapes: shapes of tensors. :param bool strict: whether to use extend-but-not-resize broadcasting. :returns: broadcasted shape :rtype: tuple :raises: ValueError |
188,004 | import inspect
from typing import Optional
import torch
import torch.nn as nn
def get_module_forward_input_names(module: nn.Module):
params = inspect.signature(module.forward).parameters
param_names = [k for k, v in params.items() if not str(v).startswith("*")]
return param_names | null |
188,005 | import inspect
from typing import Optional
import torch
import torch.nn as nn
The provided code snippet includes necessary dependencies for implementing the `weighted_average` function. Write a Python function `def weighted_average( x: torch.Tensor, weights: Optional[torch.Tensor] = None, dim=None ) -> torch.Tenso... | Computes the weighted average of a given tensor across a given dim, masking values associated with weight zero, meaning instead of `nan * 0 = nan` you will get `0 * 0 = 0`. Parameters ---------- x Input tensor, of which the average must be computed. weights Weights tensor, of the same shape as `x`. dim The dim along wh... |
188,006 | from typing import List, Tuple
import numpy as np
import torch
import torch.nn as nn
import torch.nn.functional as F
from gluonts.time_feature import get_seasonality
def linspace(
backcast_length: int, forecast_length: int
) -> Tuple[np.ndarray, np.ndarray]:
lin_space = np.linspace(
-backcast_length,
... | null |
188,007 | from typing import List, Optional, Tuple, Union
import numpy as np
import torch
import torch.nn as nn
from torch.distributions import Distribution
from gluonts.core.component import validated
from gluonts.torch.distributions.distribution_output import DistributionOutput
from pts.model import weighted_average
from pts.m... | null |
188,008 | from typing import List, Optional, Tuple, Union
import numpy as np
import torch
import torch.nn as nn
from torch.distributions import Distribution
from gluonts.core.component import validated
from gluonts.torch.modules.distribution_output import DistributionOutput
from pts.model import weighted_average
from pts.modules... | null |
188,009 | from typing import List, Optional, Tuple
import torch
import torch.nn as nn
from gluonts.core.component import validated
from gluonts.torch.modules.distribution_output import DistributionOutput
from pts.modules import MeanScaler, NOPScaler, FeatureEmbedder
def prod(xs):
p = 1
for x in xs:
p *= x
re... | null |
188,010 | from itertools import chain
from typing import List, Optional, Dict
import numpy as np
import torch
from gluonts.core.component import validated
from gluonts.dataset.field_names import FieldName
from gluonts.model.forecast_generator import QuantileForecastGenerator
from gluonts.model.predictor import Predictor
from glu... | null |
188,011 | import os
import subprocess
from os.path import join
import yaml
import tempfile
import argparse
from skimage.io import imread
import numpy as np
import librosa
from util import util
from tqdm import tqdm
import torch
from collections import OrderedDict
import cv2
from moviepy.video.io.ffmpeg_tools import ffmpeg_extrac... | null |
188,012 | import os
import subprocess
from os.path import join
from tqdm import tqdm
import numpy as np
import torch
from collections import OrderedDict
import librosa
from skimage.io import imread
import cv2
import scipy.io as sio
import argparse
import yaml
import albumentations as A
import albumentations.pytorch
from pathlib ... | null |
188,013 | import sys
from . import audio_funcs
import numpy as np
from math import cos, sin
import torch
from numpy.linalg import solve
from scipy.ndimage import gaussian_filter1d
from sklearn.neighbors import KDTree
import time
from tqdm import tqdm
The provided code snippet includes necessary dependencies for implementing the... | compute mel for an audio sequence. |
188,014 | import sys
from . import audio_funcs
import numpy as np
from math import cos, sin
import torch
from numpy.linalg import solve
from scipy.ndimage import gaussian_filter1d
from sklearn.neighbors import KDTree
import time
from tqdm import tqdm
The provided code snippet includes necessary dependencies for implementing the... | compute KNN for feat in feat base |
188,015 | import sys
from . import audio_funcs
import numpy as np
from math import cos, sin
import torch
from numpy.linalg import solve
from scipy.ndimage import gaussian_filter1d
from sklearn.neighbors import KDTree
import time
from tqdm import tqdm
def KNN_with_torch(feats, feat_database, K=10):
feats = torch.from_numpy(f... | null |
188,016 | import sys
from . import audio_funcs
import numpy as np
from math import cos, sin
import torch
from numpy.linalg import solve
from scipy.ndimage import gaussian_filter1d
from sklearn.neighbors import KDTree
import time
from tqdm import tqdm
def solve_LLE_projection(feat, feat_base):
'''find LLE projection weights g... | null |
188,017 | import sys
from . import audio_funcs
import numpy as np
from math import cos, sin
import torch
from numpy.linalg import solve
from scipy.ndimage import gaussian_filter1d
from sklearn.neighbors import KDTree
import time
from tqdm import tqdm
def solve_LLE_projection(feat, feat_base):
def compute_LLE_projection_all_fram... | null |
188,018 | import sys
from . import audio_funcs
import numpy as np
from math import cos, sin
import torch
from numpy.linalg import solve
from scipy.ndimage import gaussian_filter1d
from sklearn.neighbors import KDTree
import time
from tqdm import tqdm
def angle2matrix(angles, gradient='false'):
''' get rotation matrix from th... | project 2d landmarks given predicted 3d landmarks & headposes and user-defined camera & viewpoint parameters |
188,019 | import sys
from . import audio_funcs
import numpy as np
from math import cos, sin
import torch
from numpy.linalg import solve
from scipy.ndimage import gaussian_filter1d
from sklearn.neighbors import KDTree
import time
from tqdm import tqdm
The provided code snippet includes necessary dependencies for implementing the... | smooth the input 3d landmarks using gaussian filters on each dimension. Args: pts3d: [N, 73, 3] |
188,020 | import sys
from . import audio_funcs
import numpy as np
from math import cos, sin
import torch
from numpy.linalg import solve
from scipy.ndimage import gaussian_filter1d
from sklearn.neighbors import KDTree
import time
from tqdm import tqdm
lower_mouth = [53, 54, 55, 56, 57, 58, 59, 60]
upper_mouth = [46, 47, 48, 49, 5... | mouth region AMP to control the reaction amplitude. method: 'XY', 'delta', 'XYZ', 'LowerMore' or 'CloseSmall' |
188,021 | import sys
from . import audio_funcs
import numpy as np
from math import cos, sin
import torch
from numpy.linalg import solve
from scipy.ndimage import gaussian_filter1d
from sklearn.neighbors import KDTree
import time
from tqdm import tqdm
upper_outer_lip = list(range(47, 52))
upper_inner_lip = [63, 62, 61]
lower_inne... | solve the generated intersec lips, usually happens in mouth AMP usage. Args: pts3d: [N, 73, 3] |
188,022 | import sys
from . import audio_funcs
import numpy as np
from math import cos, sin
import torch
from numpy.linalg import solve
from scipy.ndimage import gaussian_filter1d
from sklearn.neighbors import KDTree
import time
from tqdm import tqdm
def headpose_smooth(headpose, smooth_sigmas=[0,0], method='gaussian'):
rot... | null |
188,023 | import os
import os.path
import math
import torch
import torch.utils.data
import numpy as np
import librosa
from librosa.filters import mel as librosa_mel_fn
import torch.nn.functional as F
The provided code snippet includes necessary dependencies for implementing the `mu_law_encoding` function. Write a Python functio... | encode the original audio via mu-law companding and mu-bits quantization |
188,024 | import os
import os.path
import math
import torch
import torch.utils.data
import numpy as np
import librosa
from librosa.filters import mel as librosa_mel_fn
import torch.nn.functional as F
The provided code snippet includes necessary dependencies for implementing the `mu_law_decoding` function. Write a Python functio... | inverse the mu-law compressed and quantized data. |
188,025 | import os
import os.path
import math
import torch
import torch.utils.data
import numpy as np
import librosa
from librosa.filters import mel as librosa_mel_fn
import torch.nn.functional as F
The provided code snippet includes necessary dependencies for implementing the `inject_gaussian_noise` function. Write a Python f... | inject random gaussian noise (mean=0, std=1) to audio clip In my test, a reasonable factor region could be [0, 0.01] larger will be too large and smaller could be ignored. Args: data: [n,] original audio sequence noise_factor(float): scaled factor use_torch(bool): optional, if use_torch=True, input data and implementat... |
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