
import math
import sys


def    A (      lowercase				)     ->						str:
		'''simple docstring'''

		UpperCamelCase						=  ''
		try:
				with open(lowercase					, 'rb'				) as binary_file:
						UpperCamelCase						=  binary_file.read()
				for dat in data:
						UpperCamelCase						=  f'''{dat:08b}'''
						result += curr_byte
				return result
		except OSError:
				print('File not accessible'				)
				sys.exit()


def    A (      lowercase				)     ->						str:
		'''simple docstring'''

		UpperCamelCase						=  {'0': '0', '1': '1'}
		UpperCamelCase			,						UpperCamelCase						=  '', ''
		UpperCamelCase						=  len(lowercase				)

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

				UpperCamelCase						=  lexicon[curr_string]
				result += last_match_id
				UpperCamelCase						=  last_match_id + '0'

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

				UpperCamelCase						=  last_match_id + '1'
				index += 1
				UpperCamelCase						=  ''
		return result


def    A (      lowercase					, lowercase				)     ->						None:
		'''simple docstring'''

		UpperCamelCase						=  8
		try:
				with open(lowercase					, 'wb'				) as opened_file:
						UpperCamelCase						=  [
						    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    A (      lowercase				)     ->						str:
		'''simple docstring'''

		UpperCamelCase						=  0
		for letter in data_bits:
				if letter == "1":
						break
				counter += 1

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


def    A (      lowercase					, lowercase				)     ->						None:
		'''simple docstring'''

		UpperCamelCase						=  read_file_binary(lowercase				)
		UpperCamelCase						=  remove_prefix(lowercase				)
		UpperCamelCase						=  decompress_data(lowercase				)
		write_file_binary(lowercase					, lowercase				)


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


from collections import OrderedDict
from typing import Mapping

from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging


_UpperCAmelCase      :				Tuple          = logging.get_logger(__name__)

_UpperCAmelCase      :				Union[str, Any]          = {
    "facebook/data2vec-text-base": "https://huggingface.co/data2vec/resolve/main/config.json",
}


class        lowercase      (	_SCREAMING_SNAKE_CASE     ):
		__lowercase : Dict			  =       "data2vec-text"



		def __init__(				self       ,   A_=30_522       ,   A_=768       ,   A_=12       ,   A_=12       ,   A_=3_072       ,   A_="gelu"       ,   A_=0.1       ,   A_=0.1       ,   A_=512       ,   A_=2       ,   A_=0.02       ,   A_=1e-12       ,   A_=1       ,   A_=0       ,   A_=2       ,   A_="absolute"       ,   A_=True       ,   A_=None       ,   **A_       ,   )						->      Any:
				"""simple docstring"""
				super().__init__(pad_token_id=A_       ,   bos_token_id=A_       ,   eos_token_id=A_       ,   **A_ )

				UpperCamelCase						=  vocab_size
				UpperCamelCase						=  hidden_size
				UpperCamelCase						=  num_hidden_layers
				UpperCamelCase						=  num_attention_heads
				UpperCamelCase						=  hidden_act
				UpperCamelCase						=  intermediate_size
				UpperCamelCase						=  hidden_dropout_prob
				UpperCamelCase						=  attention_probs_dropout_prob
				UpperCamelCase						=  max_position_embeddings
				UpperCamelCase						=  type_vocab_size
				UpperCamelCase						=  initializer_range
				UpperCamelCase						=  layer_norm_eps
				UpperCamelCase						=  position_embedding_type
				UpperCamelCase						=  use_cache
				UpperCamelCase						=  classifier_dropout






class        lowercase      (	_SCREAMING_SNAKE_CASE     ):



		@property
		def __UpperCamelCase				(				self )						->      Mapping[str, Mapping[int, str]]:
				"""simple docstring"""
				if self.task == "multiple-choice":
						UpperCamelCase						=  {0: 'batch', 1: 'choice', 2: 'sequence'}
				else:
						UpperCamelCase						=  {0: 'batch', 1: 'sequence'}
				return OrderedDict(
				    [
				        ('input_ids', dynamic_axis),
				        ('attention_mask', dynamic_axis),
				    ] )
