


import os
import string
import sys


lowercase_	   =     1 << 8

lowercase_	   =     {
    'tab': ord('\t'),
    'newline': ord('\r'),
    'esc': 2_7,
    'up': 6_5 + ARROW_KEY_FLAG,
    'down': 6_6 + ARROW_KEY_FLAG,
    'right': 6_7 + ARROW_KEY_FLAG,
    'left': 6_8 + ARROW_KEY_FLAG,
    'mod_int': 9_1,
    'undefined': sys.maxsize,
    'interrupt': 3,
    'insert': 5_0,
    'delete': 5_1,
    'pg_up': 5_3,
    'pg_down': 5_4,
}

lowercase_	   =     KEYMAP['up']
lowercase_	   =     KEYMAP['left']

if sys.platform == "win32":
       lowercase_	   =     []
       lowercase_	   =     {
           b'\xe0H': KEYMAP['up'] - ARROW_KEY_FLAG,
           b'\x00H': KEYMAP['up'] - ARROW_KEY_FLAG,
           b'\xe0P': KEYMAP['down'] - ARROW_KEY_FLAG,
           b'\x00P': KEYMAP['down'] - ARROW_KEY_FLAG,
           b'\xe0M': KEYMAP['right'] - ARROW_KEY_FLAG,
           b'\x00M': KEYMAP['right'] - ARROW_KEY_FLAG,
           b'\xe0K': KEYMAP['left'] - ARROW_KEY_FLAG,
           b'\x00K': KEYMAP['left'] - ARROW_KEY_FLAG,
       }

for i in range(1_0):
       lowercase_	   =     ord(str(i))
def 				UpperCamelCase__					(  ):
 if os.name == "nt":
  import msvcrt

  __lowerCamelCase		:							Dict		 =						'mbcs'
  # Flush the keyboard buffer
  while msvcrt.kbhit():
   msvcrt.getch()
  if len(SCREAMING_SNAKE_CASE__						) == 0:
   # Read the keystroke
   __lowerCamelCase		:							Tuple		 =						msvcrt.getch()

   # If it is a prefix char, get second part
   if ch in (b"\x00", b"\xe0"):
    __lowerCamelCase		:							Tuple		 =						ch + msvcrt.getch()
    # Translate actual Win chars to bullet char types
    try:
     __lowerCamelCase		:							Tuple		 =						chr(WIN_KEYMAP[cha]						)
     WIN_CH_BUFFER.append(chr(KEYMAP['mod_int']						)						)
     WIN_CH_BUFFER.append(SCREAMING_SNAKE_CASE__						)
     if ord(SCREAMING_SNAKE_CASE__						) in (
         KEYMAP["insert"] - 1 << 9,
         KEYMAP["delete"] - 1 << 9,
         KEYMAP["pg_up"] - 1 << 9,
         KEYMAP["pg_down"] - 1 << 9,
     ):
      WIN_CH_BUFFER.append(chr(126						)						)
     __lowerCamelCase		:							Optional[int]		 =						chr(KEYMAP['esc']						)
    except KeyError:
     __lowerCamelCase		:							Tuple		 =						cha[1]
   else:
    __lowerCamelCase		:							str		 =						ch.decode(SCREAMING_SNAKE_CASE__						)
  else:
   __lowerCamelCase		:							Optional[Any]		 =						WIN_CH_BUFFER.pop(0						)
 elif os.name == "posix":
  import termios
  import tty

  __lowerCamelCase		:							List[str]		 =						sys.stdin.fileno()
  __lowerCamelCase		:							Dict		 =						termios.tcgetattr(SCREAMING_SNAKE_CASE__						)
  try:
   tty.setraw(SCREAMING_SNAKE_CASE__						)
   __lowerCamelCase		:							Dict		 =						sys.stdin.read(1						)
  finally:
   termios.tcsetattr(SCREAMING_SNAKE_CASE__      ,	termios.TCSADRAIN      ,	SCREAMING_SNAKE_CASE__						)
 return ch



def 				UpperCamelCase__					(  ):
 __lowerCamelCase		:							Any		 =						get_raw_chars()
 if ord(SCREAMING_SNAKE_CASE__						) in [KEYMAP["interrupt"], KEYMAP["newline"]]:
  return char

 elif ord(SCREAMING_SNAKE_CASE__						) == KEYMAP["esc"]:
  __lowerCamelCase		:							str		 =						get_raw_chars()
  if ord(SCREAMING_SNAKE_CASE__						) == KEYMAP["mod_int"]:
   __lowerCamelCase		:							Optional[int]		 =						get_raw_chars()
   if ord(SCREAMING_SNAKE_CASE__						) >= KEYMAP["arrow_begin"] - ARROW_KEY_FLAG and ord(SCREAMING_SNAKE_CASE__						) <= KEYMAP["arrow_end"] - ARROW_KEY_FLAG:
    return chr(ord(SCREAMING_SNAKE_CASE__						) + ARROW_KEY_FLAG						)
   else:
    return KEYMAP["undefined"]
  else:
   return get_raw_chars()

 else:
  if char in string.printable:
   return char
  else:
   return KEYMAP["undefined"]





import json
import os
import tempfile

import transformers

import datasets
from utils import generate_example_dataset, get_duration


lowercase_	   =     5_0_0_0_0_0

lowercase_   ,lowercase_	   =     os.path.split(__file__)
lowercase_	   =     os.path.join(RESULTS_BASEPATH, 'results', RESULTS_FILENAME.replace('.py', '.json'))
@get_duration
def 				UpperCamelCase__					(  SCREAMING_SNAKE_CASE__      ,	**SCREAMING_SNAKE_CASE__						):
 __lowerCamelCase		:							Optional[int]		 =						dataset.map(**SCREAMING_SNAKE_CASE__						)
@get_duration
def 				UpperCamelCase__					(  SCREAMING_SNAKE_CASE__      ,	**SCREAMING_SNAKE_CASE__						):
 __lowerCamelCase		:							Tuple		 =						dataset.filter(**SCREAMING_SNAKE_CASE__						)
def 				UpperCamelCase__					(  ):
 __lowerCamelCase		:							str		 =						{'num examples': SPEED_TEST_N_EXAMPLES}
 with tempfile.TemporaryDirectory() as tmp_dir:
  __lowerCamelCase		:							Any		 =						datasets.Features({'text': datasets.Value('string'						), 'numbers': datasets.Value('float32'						)}						)
  __lowerCamelCase		:							Any		 =						generate_example_dataset(
      os.path.join(SCREAMING_SNAKE_CASE__      ,	'dataset.arrow'						)      ,	SCREAMING_SNAKE_CASE__      ,	num_examples=SCREAMING_SNAKE_CASE__						)

  __lowerCamelCase		:							List[Any]		 =						transformers.AutoTokenizer.from_pretrained('bert-base-cased'      ,	use_fast=SCREAMING_SNAKE_CASE__						)

  def tokenize(SCREAMING_SNAKE_CASE__						):
   return tokenizer(examples['text']						)

  __lowerCamelCase		:							str		 =						map(SCREAMING_SNAKE_CASE__						)

  __lowerCamelCase		:							int		 =						map(SCREAMING_SNAKE_CASE__      ,	batched=SCREAMING_SNAKE_CASE__						)

  __lowerCamelCase		:							Optional[int]		 =						map(SCREAMING_SNAKE_CASE__      ,	function=lambda SCREAMING_SNAKE_CASE__						: None      ,	batched=SCREAMING_SNAKE_CASE__						)

  with dataset.formatted_as(type='numpy'						):
   __lowerCamelCase		:							Union[str, Any]		 =						map(SCREAMING_SNAKE_CASE__      ,	function=lambda SCREAMING_SNAKE_CASE__						: None      ,	batched=SCREAMING_SNAKE_CASE__						)

  with dataset.formatted_as(type='pandas'						):
   __lowerCamelCase		:							Any		 =						map(SCREAMING_SNAKE_CASE__      ,	function=lambda SCREAMING_SNAKE_CASE__						: None      ,	batched=SCREAMING_SNAKE_CASE__						)

  with dataset.formatted_as(type='torch'      ,	columns='numbers'						):
   __lowerCamelCase		:							List[str]		 =						map(SCREAMING_SNAKE_CASE__      ,	function=lambda SCREAMING_SNAKE_CASE__						: None      ,	batched=SCREAMING_SNAKE_CASE__						)

  with dataset.formatted_as(type='tensorflow'      ,	columns='numbers'						):
   __lowerCamelCase		:							List[Any]		 =						map(SCREAMING_SNAKE_CASE__      ,	function=lambda SCREAMING_SNAKE_CASE__						: None      ,	batched=SCREAMING_SNAKE_CASE__						)

  __lowerCamelCase		:							Optional[Any]		 =						map(SCREAMING_SNAKE_CASE__      ,	function=SCREAMING_SNAKE_CASE__      ,	batched=SCREAMING_SNAKE_CASE__						)

  __lowerCamelCase		:							Optional[int]		 =						filter(SCREAMING_SNAKE_CASE__						)

  # Activate later when tokenizer support batched inputs
  # with dataset.formatted_as(type='numpy'):
  #     times[func.__name__ + " fast-tokenizer batched numpy"] = func(dataset, function=tokenize, batched=True)

 with open(SCREAMING_SNAKE_CASE__      ,	'wb'						) as f:
  f.write(json.dumps(SCREAMING_SNAKE_CASE__						).encode('utf-8'						)						)


if __name__ == "__main__":  # useful to run the profiler
       benchmark_map_filter()

