'''simple docstring'''




import numpy as np






def     snake_case__							(      _A: Optional[int]				,       _A: str="utf-8"				,       _A: Union[str, Any]="surrogatepass"			)   ->     Dict:

		'''simple docstring'''


		lowerCAmelCase        =  bin(int.from_bytes(text.encode(_A				,       _A			)				,       """big"""			)			)[2:]
		return bits.zfill(8 * ((len(_A			) + 7) // 8)			)






def     snake_case__							(      _A: List[str]				,       _A: List[Any]="utf-8"				,       _A: Tuple="surrogatepass"			)   ->     int:

		'''simple docstring'''


		lowerCAmelCase        =  int(_A				,       2			)
		return n.to_bytes((n.bit_length() + 7) // 8				,       """big"""			).decode(_A				,       _A			) or "\0"






def     snake_case__							(      _A: Tuple				,       _A: Union[str, Any]			)   ->     int:

		'''simple docstring'''


		if size_par + len(_A			) <= 2**size_par - (len(_A			) - 1):
				raise ValueError("""size of parity don't match with size of data"""			)

		lowerCAmelCase        =  []
		lowerCAmelCase        =  []
		lowerCAmelCase        =  [bin(_A			)[2:] for x in range(1				,       size_par + len(_A			) + 1			)]

		# sorted information data for the size of the output data
		lowerCAmelCase        =  []
		# data position template + parity
		lowerCAmelCase        =  []
		# parity bit counter
		lowerCAmelCase        =  0
		# counter position of data bits
		lowerCAmelCase        =  0

		for x in range(1				,       size_par + len(_A			) + 1			):
				# Performs a template of bit positions - who should be given,
				# and who should be parity
				if qtd_bp < size_par:
						if (np.log(_A			) / np.log(2			)).is_integer():
								data_out_gab.append("""P"""			)
								lowerCAmelCase        =  qtd_bp + 1
						else:
								data_out_gab.append("""D"""			)
				else:
						data_out_gab.append("""D"""			)

				# Sorts the data to the new output size
				if data_out_gab[-1] == "D":
						data_ord.append(data[cont_data]			)
						cont_data += 1
				else:
						data_ord.append(_A			)

    # Calculates parity
		lowerCAmelCase        =  0  # parity bit counter
		for bp in range(1				,       size_par + 1			):
				# Bit counter one for a given parity
				lowerCAmelCase        =  0
				# counter to control the loop reading
				lowerCAmelCase        =  0
				for x in data_ord:
						if x is not None:
								try:
										lowerCAmelCase        =  (bin_pos[cont_loop])[-1 * (bp)]
								except IndexError:
										lowerCAmelCase        =  """0"""
								if aux == "1" and x == "1":
										cont_bo += 1
						cont_loop += 1
				parity.append(cont_bo % 2			)

				qtd_bp += 1

		# Mount the message
		lowerCAmelCase        =  0  # parity bit counter
		for x in range(0				,       size_par + len(_A			)			):
				if data_ord[x] is None:
						data_out.append(str(parity[cont_bp]			)			)
						cont_bp += 1
				else:
						data_out.append(data_ord[x]			)

		return data_out






def     snake_case__							(      _A: Union[str, Any]				,       _A: Optional[Any]			)   ->     Tuple:

		'''simple docstring'''


		lowerCAmelCase        =  []
		# Parity bit counter
		lowerCAmelCase        =  0
		# Counter p data bit reading
		lowerCAmelCase        =  0
		# list of parity received
		lowerCAmelCase        =  []
		lowerCAmelCase        =  []

		for x in range(1				,       len(_A			) + 1			):
				# Performs a template of bit positions - who should be given,
				#  and who should be parity
				if qtd_bp < size_par and (np.log(_A			) / np.log(2			)).is_integer():
						data_out_gab.append("""P"""			)
						lowerCAmelCase        =  qtd_bp + 1
				else:
						data_out_gab.append("""D"""			)

				# Sorts the data to the new output size
				if data_out_gab[-1] == "D":
						data_output.append(data[cont_data]			)
				else:
						parity_received.append(data[cont_data]			)
				cont_data += 1

		# -----------calculates the parity with the data
		lowerCAmelCase        =  []
		lowerCAmelCase        =  []
		lowerCAmelCase        =  [bin(_A			)[2:] for x in range(1				,       size_par + len(_A			) + 1			)]

		#  sorted information data for the size of the output data
		lowerCAmelCase        =  []
		# Data position feedback + parity
		lowerCAmelCase        =  []
		# Parity bit counter
		lowerCAmelCase        =  0
		# Counter p data bit reading
		lowerCAmelCase        =  0

		for x in range(1				,       size_par + len(_A			) + 1			):
				# Performs a template position of bits - who should be given,
				# and who should be parity
				if qtd_bp < size_par and (np.log(_A			) / np.log(2			)).is_integer():
						data_out_gab.append("""P"""			)
						lowerCAmelCase        =  qtd_bp + 1
				else:
						data_out_gab.append("""D"""			)

				# Sorts the data to the new output size
				if data_out_gab[-1] == "D":
						data_ord.append(data_output[cont_data]			)
						cont_data += 1
				else:
						data_ord.append(_A			)

    # Calculates parity
		lowerCAmelCase        =  0  # parity bit counter
		for bp in range(1				,       size_par + 1			):
				# Bit counter one for a certain parity
				lowerCAmelCase        =  0
				# Counter to control loop reading
				lowerCAmelCase        =  0
				for x in data_ord:
						if x is not None:
								try:
										lowerCAmelCase        =  (bin_pos[cont_loop])[-1 * (bp)]
								except IndexError:
										lowerCAmelCase        =  """0"""
								if aux == "1" and x == "1":
										cont_bo += 1
						cont_loop += 1
				parity.append(str(cont_bo % 2			)			)

				qtd_bp += 1

		# Mount the message
		lowerCAmelCase        =  0  # Parity bit counter
		for x in range(0				,       size_par + len(_A			)			):
				if data_ord[x] is None:
						data_out.append(str(parity[cont_bp]			)			)
						cont_bp += 1
				else:
						data_out.append(data_ord[x]			)

		lowerCAmelCase        =  parity_received == parity
		return data_output, ack





'''simple docstring'''




from collections import OrderedDict
from typing import Mapping

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


__lowercase				   =  logging.get_logger(__name__)

__lowercase				   =  {
    '''flaubert/flaubert_small_cased''': '''https://huggingface.co/flaubert/flaubert_small_cased/resolve/main/config.json''',
    '''flaubert/flaubert_base_uncased''': '''https://huggingface.co/flaubert/flaubert_base_uncased/resolve/main/config.json''',
    '''flaubert/flaubert_base_cased''': '''https://huggingface.co/flaubert/flaubert_base_cased/resolve/main/config.json''',
    '''flaubert/flaubert_large_cased''': '''https://huggingface.co/flaubert/flaubert_large_cased/resolve/main/config.json''',
}






class     a__( lowerCAmelCase__     ):


			'''simple docstring'''






			UpperCAmelCase_      :					int								=	'''flaubert'''
			UpperCAmelCase_      :					Optional[Any]								=	{
			    '''hidden_size''': '''emb_dim''',
			    '''num_attention_heads''': '''n_heads''',
			    '''num_hidden_layers''': '''n_layers''',
			    '''n_words''': '''vocab_size''',  # For backward compatibility
			}



			def __init__(       self	,   __lowerCAmelCase=False	,   __lowerCAmelCase=0.0	,   __lowerCAmelCase=30145	,   __lowerCAmelCase=2048	,   __lowerCAmelCase=12	,   __lowerCAmelCase=16	,   __lowerCAmelCase=0.1	,   __lowerCAmelCase=0.1	,   __lowerCAmelCase=True	,   __lowerCAmelCase=False	,   __lowerCAmelCase=False	,   __lowerCAmelCase=False	,   __lowerCAmelCase=1	,   __lowerCAmelCase=True	,   __lowerCAmelCase=512	,   __lowerCAmelCase=2048**-0.5	,   __lowerCAmelCase=1E-1_2	,   __lowerCAmelCase=0.02	,   __lowerCAmelCase=0	,   __lowerCAmelCase=1	,   __lowerCAmelCase=2	,   __lowerCAmelCase=3	,   __lowerCAmelCase=5	,   __lowerCAmelCase=True	,   __lowerCAmelCase="first"	,   __lowerCAmelCase=True	,   __lowerCAmelCase=None	,   __lowerCAmelCase=True	,   __lowerCAmelCase=0.1	,   __lowerCAmelCase=5	,   __lowerCAmelCase=5	,   __lowerCAmelCase=0	,   __lowerCAmelCase=0	,   __lowerCAmelCase=2	,   __lowerCAmelCase=0	,   **__lowerCAmelCase	,   ):




					"""simple docstring"""


					lowerCAmelCase        =  pre_norm
					lowerCAmelCase        =  layerdrop
					lowerCAmelCase        =  vocab_size
					lowerCAmelCase        =  emb_dim
					lowerCAmelCase        =  n_layers
					lowerCAmelCase        =  n_heads
					lowerCAmelCase        =  dropout
					lowerCAmelCase        =  attention_dropout
					lowerCAmelCase        =  gelu_activation
					lowerCAmelCase        =  sinusoidal_embeddings
					lowerCAmelCase        =  causal
					lowerCAmelCase        =  asm
					lowerCAmelCase        =  n_langs
					lowerCAmelCase        =  use_lang_emb
					lowerCAmelCase        =  layer_norm_eps
					lowerCAmelCase        =  bos_index
					lowerCAmelCase        =  eos_index
					lowerCAmelCase        =  pad_index
					lowerCAmelCase        =  unk_index
					lowerCAmelCase        =  mask_index
					lowerCAmelCase        =  is_encoder
					lowerCAmelCase        =  max_position_embeddings
					lowerCAmelCase        =  embed_init_std
					lowerCAmelCase        =  init_std
					lowerCAmelCase        =  summary_type
					lowerCAmelCase        =  summary_use_proj
					lowerCAmelCase        =  summary_activation
					lowerCAmelCase        =  summary_proj_to_labels
					lowerCAmelCase        =  summary_first_dropout
					lowerCAmelCase        =  start_n_top
					lowerCAmelCase        =  end_n_top
					lowerCAmelCase        =  mask_token_id
					lowerCAmelCase        =  lang_id

					if "n_words" in kwargs:
							lowerCAmelCase        =  kwargs["""n_words"""]

					super().__init__(pad_token_id=__lowerCAmelCase	,   bos_token_id=__lowerCAmelCase	,   **__lowerCAmelCase)







class     a__( lowerCAmelCase__     ):


			'''simple docstring'''






			@property
			def 							a_	(       self):




					"""simple docstring"""


					if self.task == "multiple-choice":
							lowerCAmelCase        =  {0: """batch""", 1: """choice""", 2: """sequence"""}
					else:
							lowerCAmelCase        =  {0: """batch""", 1: """sequence"""}
					return OrderedDict(
					    [
					        ("""input_ids""", dynamic_axis),
					        ("""attention_mask""", dynamic_axis),
					    ])




