



'''simple docstring'''


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'''


from ...configuration_utils import PretrainedConfig
from ...utils import logging


lowercase_      :				Optional[Any]   					=    logging.get_logger(__name__)

lowercase_      :				int   					=    {
    '''bigcode/gpt_bigcode-santacoder''': '''https://huggingface.co/bigcode/gpt_bigcode-santacoder/resolve/main/config.json''',
}




class      __UpperCamelCase       (_UpperCAmelCase			):
	__A			  =					'''gpt_bigcode'''
	__A			  =					['''past_key_values''']
	__A			  =					{
	    '''hidden_size''': '''n_embd''',
	    '''max_position_embeddings''': '''n_positions''',
	    '''num_attention_heads''': '''n_head''',
	    '''num_hidden_layers''': '''n_layer''',
	}







	def __init__(    self ,				_lowerCAmelCase=5_0257 ,				_lowerCAmelCase=1024 ,				_lowerCAmelCase=768 ,				_lowerCAmelCase=12 ,				_lowerCAmelCase=12 ,				_lowerCAmelCase=None ,				_lowerCAmelCase="gelu_pytorch_tanh" ,				_lowerCAmelCase=0.1 ,				_lowerCAmelCase=0.1 ,				_lowerCAmelCase=0.1 ,				_lowerCAmelCase=1E-5 ,				_lowerCAmelCase=0.02 ,				_lowerCAmelCase=True ,				_lowerCAmelCase=True ,				_lowerCAmelCase=5_0256 ,				_lowerCAmelCase=5_0256 ,				_lowerCAmelCase=True ,				_lowerCAmelCase=True ,				_lowerCAmelCase=True ,				**_lowerCAmelCase ,				)    ->    Optional[int]:
							'''simple docstring'''






							lowercase        =							vocab_size
							lowercase        =							n_positions
							lowercase        =							n_embd
							lowercase        =							n_layer
							lowercase        =							n_head
							lowercase        =							n_inner
							lowercase        =							activation_function
							lowercase        =							resid_pdrop
							lowercase        =							embd_pdrop
							lowercase        =							attn_pdrop
							lowercase        =							layer_norm_epsilon
							lowercase        =							initializer_range
							lowercase        =							scale_attn_weights
							lowercase        =							use_cache
							lowercase        =							attention_softmax_in_fpaa
							lowercase        =							scale_attention_softmax_in_fpaa
							lowercase        =							multi_query

							lowercase        =							bos_token_id
							lowercase        =							eos_token_id

							super().__init__(bos_token_id=_lowerCAmelCase ,				eos_token_id=_lowerCAmelCase ,				**_lowerCAmelCase						)


