



import math
import sys







def      SCREAMING_SNAKE_CASE				(				lowercase_    :      str						):
						lowercase        =							""""""
						try:
												with open(lowercase_ ,  """rb"""						) as binary_file:
																		lowercase        =							binary_file.read()
												for dat in data:
																		lowercase        =							F"""{dat:08b}"""
																		result += curr_byte
												return result
						except OSError:
												print("""File not accessible"""						)
												sys.exit()







def      SCREAMING_SNAKE_CASE				(				lowercase_    :      str						):
						lowercase        =							{"""0""": """0""", """1""": """1"""}
						lowercase     ,   lowercase        =							"""""", """"""
						lowercase        =							len(lowercase_						)

						for i in range(len(lowercase_						)						):
												curr_string += data_bits[i]
												if curr_string not in lexicon:
																		continue

												lowercase        =							lexicon[curr_string]
												result += last_match_id
												lowercase        =							last_match_id + """0"""

												if math.loga(lowercase_						).is_integer():
																		lowercase        =							{}
																		for curr_key in list(lowercase_						):
																								lowercase        =							lexicon.pop(lowercase_						)
																		lowercase        =							new_lex

												lowercase        =							last_match_id + """1"""
												index += 1
												lowercase        =							""""""
						return result







def      SCREAMING_SNAKE_CASE				(				lowercase_    :      str ,  lowercase_    :      str						):
						lowercase        =							8
						try:
												with open(lowercase_ ,  """wb"""						) as opened_file:
																		lowercase        =							[
																		    to_write[i : i + byte_length]
																		    for i in range(0 ,  len(lowercase_						) ,  lowercase_						)
																		]

																		if len(result_byte_array[-1]						) % byte_length == 0:
																								result_byte_array.append("""10000000"""						)
																		else:
																								result_byte_array[-1] += "1" + "0" * (
																								    byte_length - len(result_byte_array[-1]						) - 1
																								)

																		for elem in result_byte_array[:-1]:
																								opened_file.write(int(lowercase_ ,  2						).to_bytes(1 ,  byteorder="""big"""						)						)
						except OSError:
												print("""File not accessible"""						)
												sys.exit()







def      SCREAMING_SNAKE_CASE				(				lowercase_    :      str						):
						lowercase        =							0
						for letter in data_bits:
												if letter == "1":
																		break
												counter += 1

						lowercase        =							data_bits[counter:]
						lowercase        =							data_bits[counter + 1 :]
						return data_bits







def      SCREAMING_SNAKE_CASE				(				lowercase_    :      str ,  lowercase_    :      str						):
						lowercase        =							read_file_binary(lowercase_						)
						lowercase        =							remove_prefix(lowercase_						)
						lowercase        =							decompress_data(lowercase_						)
						write_file_binary(lowercase_ ,  lowercase_						)


if __name__ == "__main__":
						compress(sys.argv[1], sys.argv[2])







'''simple docstring'''


import json
import os
import tempfile

import transformers

import datasets
from utils import generate_example_dataset, get_duration


lowercase_      :				int   					=    50_0000

lowercase_					,       lowercase_      :				Union[str, Any]   					=    os.path.split(__file__)
lowercase_      :				Optional[Any]   					=    os.path.join(RESULTS_BASEPATH, '''results''', RESULTS_FILENAME.replace('''.py''', '''.json'''))







@get_duration
def      SCREAMING_SNAKE_CASE				(				lowercase_    :      datasets.Dataset ,  **lowercase_    :      Dict						):
						lowercase        =							dataset.map(**lowercase_						)







@get_duration
def      SCREAMING_SNAKE_CASE				(				lowercase_    :      datasets.Dataset ,  **lowercase_    :      Optional[int]						):
						lowercase        =							dataset.filter(**lowercase_						)







def      SCREAMING_SNAKE_CASE				(				):
						lowercase        =							{"""num examples""": SPEED_TEST_N_EXAMPLES}
						with tempfile.TemporaryDirectory() as tmp_dir:
												lowercase        =							datasets.Features({"""text""": datasets.Value("""string"""						), """numbers""": datasets.Value("""float32"""						)}						)
												lowercase        =							generate_example_dataset(
												    os.path.join(lowercase_ ,  """dataset.arrow"""						) ,  lowercase_ ,  num_examples=lowercase_						)

												lowercase        =							transformers.AutoTokenizer.from_pretrained("""bert-base-cased""" ,  use_fast=lowercase_						)

												def tokenize(lowercase_    :      Dict						):
																		return tokenizer(examples["""text"""]						)

												lowercase        =							map(lowercase_						)

												lowercase        =							map(lowercase_ ,  batched=lowercase_						)

												lowercase        =							map(lowercase_ ,  function=lambda lowercase_						: None ,  batched=lowercase_						)

												with dataset.formatted_as(type="""numpy"""						):
																		lowercase        =							map(lowercase_ ,  function=lambda lowercase_						: None ,  batched=lowercase_						)

												with dataset.formatted_as(type="""pandas"""						):
																		lowercase        =							map(lowercase_ ,  function=lambda lowercase_						: None ,  batched=lowercase_						)

												with dataset.formatted_as(type="""torch""" ,  columns="""numbers"""						):
																		lowercase        =							map(lowercase_ ,  function=lambda lowercase_						: None ,  batched=lowercase_						)

												with dataset.formatted_as(type="""tensorflow""" ,  columns="""numbers"""						):
																		lowercase        =							map(lowercase_ ,  function=lambda lowercase_						: None ,  batched=lowercase_						)

												lowercase        =							map(lowercase_ ,  function=lowercase_ ,  batched=lowercase_						)

												lowercase        =							filter(lowercase_						)

												# 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(lowercase_ ,  """wb"""						) as f:
												f.write(json.dumps(lowercase_						).encode("""utf-8"""						)						)


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


