





import numpy as np
def  __UpperCamelCase    (						snake_case							,			snake_case="utf-8"							,			snake_case="surrogatepass"      )    ->		Optional[int]:


   '''simple docstring'''







   __A    =  bin(int.from_bytes(text.encode(lowerCAmelCase__							,			lowerCAmelCase__      )							,			'''big'''      )      )[2:]
   return bits.zfill(8 * ((len(lowerCAmelCase__      ) + 7) // 8)      )
def  __UpperCamelCase    (						snake_case							,			snake_case="utf-8"							,			snake_case="surrogatepass"      )    ->		Tuple:


   '''simple docstring'''







   __A    =  int(lowerCAmelCase__							,			2      )
   return n.to_bytes((n.bit_length() + 7) // 8							,			'''big'''      ).decode(lowerCAmelCase__							,			lowerCAmelCase__      ) or "\0"
def  __UpperCamelCase    (						snake_case							,			snake_case      )    ->		List[str]:


   '''simple docstring'''







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

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

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

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

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

      qtd_bp += 1

   # Mount the message
   __A    =  0  # parity bit counter
   for x in range(0							,			size_par + len(lowerCAmelCase__      )      ):
      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  __UpperCamelCase    (						snake_case							,			snake_case      )    ->		List[Any]:


   '''simple docstring'''







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

   for x in range(1							,			len(lowerCAmelCase__      ) + 1      ):
      # Performs a template of bit positions - who should be given,
      #  and who should be parity
      if qtd_bp < size_par and (np.log(lowerCAmelCase__      ) / np.log(2      )).is_integer():
         data_out_gab.append('''P'''      )
         __A    =  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
   __A    =  []
   __A    =  []
   __A    =  [bin(lowerCAmelCase__      )[2:] for x in range(1							,			size_par + len(lowerCAmelCase__      ) + 1      )]

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

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

    # Calculates parity
   __A    =  0  # parity bit counter
   for bp in range(1							,			size_par + 1      ):
      # Bit counter one for a certain parity
      __A    =  0
      # Counter to control loop reading
      __A    =  0
      for x in data_ord:
         if x is not None:
            try:
               __A    =  (bin_pos[cont_loop])[-1 * (bp)]
            except IndexError:
               __A    =  '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
   __A    =  0  # Parity bit counter
   for x in range(0							,			size_par + len(lowerCAmelCase__      )      ):
      if data_ord[x] is None:
         data_out.append(str(parity[cont_bp]      )      )
         cont_bp += 1
      else:
         data_out.append(data_ord[x]      )

   __A    =  parity_received == parity
   return data_output, ack









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


A										=      logging.get_logger(__name__)

A										=      {
    'ZinengTang/tvlt-base': 'https://huggingface.co/ZinengTang/tvlt-base/blob/main/config.json',
}


class 				__a				(	__A    ):





		'''simple docstring'''



		UpperCAmelCase__   :					str					     =    """tvlt"""


		def __init__(    self			,     UpperCamelCase__=224			,     UpperCamelCase__=2048			,     UpperCamelCase__=128			,     UpperCamelCase__=[16, 16]			,     UpperCamelCase__=[16, 16]			,     UpperCamelCase__=3			,     UpperCamelCase__=1			,     UpperCamelCase__=8			,     UpperCamelCase__=768			,     UpperCamelCase__=12			,     UpperCamelCase__=12			,     UpperCamelCase__=3072			,     UpperCamelCase__="gelu"			,     UpperCamelCase__=0.0			,     UpperCamelCase__=0.0			,     UpperCamelCase__=0.02			,     UpperCamelCase__=1E-6			,     UpperCamelCase__=True			,     UpperCamelCase__=False			,     UpperCamelCase__=16			,     UpperCamelCase__=512			,     UpperCamelCase__=8			,     UpperCamelCase__=2048			,     UpperCamelCase__=0.75			,     UpperCamelCase__=0.15			,     UpperCamelCase__="frame-level"			,     UpperCamelCase__=True			,     UpperCamelCase__=True			,     UpperCamelCase__="classification"			,     **UpperCamelCase__			,     ):
						super().__init__(**UpperCamelCase__							)

						if audio_mask_type not in ("frame-level", "patch_level"):
										raise ValueError(
										    'audio_mask_type must be one of two acceptable strategies - {\'frame_level\', \'patch-level\') '
										    F'''got {audio_mask_type}'''							)

						SCREAMING_SNAKE_CASE_ :						Tuple    				= image_size
						SCREAMING_SNAKE_CASE_ :						int    				= spectrogram_length
						SCREAMING_SNAKE_CASE_ :						Optional[Any]    				= frequency_length
						SCREAMING_SNAKE_CASE_ :						Any    				= image_patch_size
						SCREAMING_SNAKE_CASE_ :						List[Any]    				= audio_patch_size
						SCREAMING_SNAKE_CASE_ :						int    				= num_image_channels
						SCREAMING_SNAKE_CASE_ :						Any    				= num_audio_channels
						SCREAMING_SNAKE_CASE_ :						Any    				= num_frames

						SCREAMING_SNAKE_CASE_ :						Optional[int]    				= hidden_size
						SCREAMING_SNAKE_CASE_ :						str    				= num_hidden_layers
						SCREAMING_SNAKE_CASE_ :						Optional[Any]    				= num_attention_heads
						SCREAMING_SNAKE_CASE_ :						str    				= intermediate_size
						SCREAMING_SNAKE_CASE_ :						Optional[Any]    				= hidden_act
						SCREAMING_SNAKE_CASE_ :						Optional[int]    				= hidden_dropout_prob
						SCREAMING_SNAKE_CASE_ :						int    				= attention_probs_dropout_prob
						SCREAMING_SNAKE_CASE_ :						Dict    				= initializer_range
						SCREAMING_SNAKE_CASE_ :						Dict    				= layer_norm_eps
						SCREAMING_SNAKE_CASE_ :						Union[str, Any]    				= qkv_bias
						SCREAMING_SNAKE_CASE_ :						List[str]    				= use_mean_pooling

						SCREAMING_SNAKE_CASE_ :						str    				= decoder_num_attention_heads
						SCREAMING_SNAKE_CASE_ :						Optional[int]    				= decoder_hidden_size
						SCREAMING_SNAKE_CASE_ :						Any    				= decoder_num_hidden_layers
						SCREAMING_SNAKE_CASE_ :						List[Any]    				= decoder_intermediate_size
						SCREAMING_SNAKE_CASE_ :						List[str]    				= pixel_mask_ratio
						SCREAMING_SNAKE_CASE_ :						Optional[int]    				= audio_mask_ratio
						SCREAMING_SNAKE_CASE_ :						Optional[Any]    				= audio_mask_type

						SCREAMING_SNAKE_CASE_ :						Any    				= task_matching
						SCREAMING_SNAKE_CASE_ :						Any    				= task_mae
						SCREAMING_SNAKE_CASE_ :						int    				= loss_type