code: import argparse
  
  from tax import checkpoints
  
  from transformers import FlaxTaForConditionalGeneration, TaConfig
  def 		snake_case__  (		lowercase       ,							lowercase       ,							lowercase				):
     lowerCAmelCase_:       Optional[int]         =  TaConfig.from_pretrained(__a				)
     lowerCAmelCase_:       Dict         =  FlaxTaForConditionalGeneration(config=__a				)
     lowerCAmelCase_:       List[Any]         =  checkpoints.load_tax_checkpoint(__a				)
  
     lowerCAmelCase_:       List[str]         =  '''wi_0''' in tax_model['''target''']['''encoder''']['''layers_0''']['''mlp''']
  
     # Encoder
     for layer_index in range(config.num_layers				):
        lowerCAmelCase_:       str         =  F'''layers_{str(__a				)}'''
  
        # Self-Attention
        lowerCAmelCase_:       Dict         =  tax_model['''target''']['''encoder'''][layer_name]['''attention''']['''key''']['''kernel''']
        lowerCAmelCase_:       int         =  tax_model['''target''']['''encoder'''][layer_name]['''attention''']['''out''']['''kernel''']
        lowerCAmelCase_:       int         =  tax_model['''target''']['''encoder'''][layer_name]['''attention''']['''query''']['''kernel''']
        lowerCAmelCase_:       Tuple         =  tax_model['''target''']['''encoder'''][layer_name]['''attention''']['''value''']['''kernel''']
  
        # Layer Normalization
        lowerCAmelCase_:       Optional[int]         =  tax_model['''target''']['''encoder'''][layer_name]['''pre_attention_layer_norm''']['''scale''']
  
        if split_mlp_wi:
           lowerCAmelCase_:       Optional[int]         =  tax_model['''target''']['''encoder'''][layer_name]['''mlp''']['''wi_0''']['''kernel''']
           lowerCAmelCase_:       Tuple         =  tax_model['''target''']['''encoder'''][layer_name]['''mlp''']['''wi_1''']['''kernel''']
        else:
           lowerCAmelCase_:       int         =  tax_model['''target''']['''encoder'''][layer_name]['''mlp''']['''wi''']['''kernel''']
  
        lowerCAmelCase_:       int         =  tax_model['''target''']['''encoder'''][layer_name]['''mlp''']['''wo''']['''kernel''']
  
        # Layer Normalization
        lowerCAmelCase_:       Optional[Any]         =  tax_model['''target''']['''encoder'''][layer_name]['''pre_mlp_layer_norm''']['''scale''']
  
        # Assigning
        lowerCAmelCase_:       Dict         =  tax_attention_key
        lowerCAmelCase_:       str         =  tax_attention_out
        lowerCAmelCase_:       Any         =  tax_attention_query
        lowerCAmelCase_:       str         =  tax_attention_value
  
        lowerCAmelCase_:       List[Any]         =  tax_attention_layer_norm
  
        if split_mlp_wi:
           lowerCAmelCase_:       int         =  tax_mlp_wi_a
           lowerCAmelCase_:       Dict         =  tax_mlp_wi_a
        else:
           lowerCAmelCase_:       Tuple         =  tax_mlp_wi
  
        lowerCAmelCase_:       List[str]         =  tax_mlp_wo
        lowerCAmelCase_:       Union[str, Any]         =  tax_mlp_layer_norm
  
     # Only for layer 0:
     lowerCAmelCase_:       Optional[Any]         =  tax_model['''target''']['''encoder''']['''relpos_bias''']['''rel_embedding'''].T
     lowerCAmelCase_:       Union[str, Any]         =  tax_encoder_rel_embedding
  
     # Assigning
     lowerCAmelCase_:       List[str]         =  tax_model['''target''']['''encoder''']['''encoder_norm''']['''scale''']
     lowerCAmelCase_:       Union[str, Any]         =  tax_encoder_norm
  
     # Decoder
     for layer_index in range(config.num_decoder_layers				):
        lowerCAmelCase_:       Optional[int]         =  F'''layers_{str(__a				)}'''
  
        # Self-Attention
        lowerCAmelCase_:       Optional[Any]         =  tax_model['''target''']['''decoder'''][layer_name]['''self_attention''']['''key''']['''kernel''']
        lowerCAmelCase_:       str         =  tax_model['''target''']['''decoder'''][layer_name]['''self_attention''']['''out''']['''kernel''']
        lowerCAmelCase_:       Dict         =  tax_model['''target''']['''decoder'''][layer_name]['''self_attention''']['''query''']['''kernel''']
        lowerCAmelCase_:       int         =  tax_model['''target''']['''decoder'''][layer_name]['''self_attention''']['''value''']['''kernel''']
  
        # Layer Normalization
        lowerCAmelCase_:       Tuple         =  tax_model['''target''']['''decoder'''][layer_name]['''pre_self_attention_layer_norm'''][
            '''scale'''
        ]
  
        # Encoder-Decoder-Attention
        lowerCAmelCase_:       List[str]         =  tax_model['''target''']['''decoder'''][layer_name]['''encoder_decoder_attention''']['''key'''][
            '''kernel'''
        ]
        lowerCAmelCase_:       List[str]         =  tax_model['''target''']['''decoder'''][layer_name]['''encoder_decoder_attention''']['''out'''][
            '''kernel'''
        ]
        lowerCAmelCase_:       Optional[Any]         =  tax_model['''target''']['''decoder'''][layer_name]['''encoder_decoder_attention''']['''query'''][
            '''kernel'''
        ]
        lowerCAmelCase_:       List[Any]         =  tax_model['''target''']['''decoder'''][layer_name]['''encoder_decoder_attention''']['''value'''][
            '''kernel'''
        ]
  
        # Layer Normalization
        lowerCAmelCase_:       Any         =  tax_model['''target''']['''decoder'''][layer_name]['''pre_cross_attention_layer_norm''']['''scale''']
  
        # MLP
        if split_mlp_wi:
           lowerCAmelCase_:       List[Any]         =  tax_model['''target''']['''decoder'''][layer_name]['''mlp''']['''wi_0''']['''kernel''']
           lowerCAmelCase_:       Any         =  tax_model['''target''']['''decoder'''][layer_name]['''mlp''']['''wi_1''']['''kernel''']
        else:
           lowerCAmelCase_:       Union[str, Any]         =  tax_model['''target''']['''decoder'''][layer_name]['''mlp''']['''wi''']['''kernel''']
  
        lowerCAmelCase_:       Dict         =  tax_model['''target''']['''decoder'''][layer_name]['''mlp''']['''wo''']['''kernel''']
  
        # Layer Normalization
        lowerCAmelCase_:       Optional[int]         =  tax_model['''target''']['''decoder'''][layer_name]['''pre_mlp_layer_norm''']['''scale''']
  
        # Assigning
        lowerCAmelCase_:       Optional[int]         =  tax_attention_key
        lowerCAmelCase_:       Tuple         =  tax_attention_out
        lowerCAmelCase_:       Optional[int]         =  tax_attention_query
        lowerCAmelCase_:       Dict         =  tax_attention_value
  
        lowerCAmelCase_:       List[Any]         =  tax_pre_attention_layer_norm
  
        lowerCAmelCase_:       Optional[int]         =  tax_enc_dec_attention_key
        lowerCAmelCase_:       Optional[int]         =  tax_enc_dec_attention_out
        lowerCAmelCase_:       Optional[Any]         =  tax_enc_dec_attention_query
        lowerCAmelCase_:       List[Any]         =  tax_enc_dec_attention_value
  
        lowerCAmelCase_:       List[Any]         =  tax_cross_layer_norm
  
        if split_mlp_wi:
           lowerCAmelCase_:       Tuple         =  tax_mlp_wi_a
           lowerCAmelCase_:       Tuple         =  tax_mlp_wi_a
        else:
           lowerCAmelCase_:       Any         =  tax_mlp_wi
  
        lowerCAmelCase_:       int         =  tax_mlp_wo
  
        lowerCAmelCase_:       Dict         =  txa_mlp_layer_norm
  
     # Decoder Normalization
     lowerCAmelCase_:       int         =  tax_model['''target''']['''decoder''']['''decoder_norm''']['''scale''']
     lowerCAmelCase_:       Tuple         =  txa_decoder_norm
  
     # Only for layer 0:
     lowerCAmelCase_:       List[str]         =  tax_model['''target''']['''decoder''']['''relpos_bias''']['''rel_embedding'''].T
     lowerCAmelCase_:       Tuple         =  tax_decoder_rel_embedding
  
     # Token Embeddings
     lowerCAmelCase_:       List[str]         =  tax_model['''target''']['''token_embedder''']['''embedding''']
     lowerCAmelCase_:       Union[str, Any]         =  txa_token_embeddings
  
     # LM Head (only in v1.1 checkpoints)
     if "logits_dense" in tax_model["target"]["decoder"]:
        lowerCAmelCase_:       str         =  tax_model['''target''']['''decoder''']['''logits_dense''']['''kernel''']
  
     flax_model.save_pretrained(__a				)
     print("T5X Model was sucessfully converted!"				)
  
  
  if __name__ == "__main__":
       a     :			Tuple					    =						argparse.ArgumentParser()
       # Required parameters
       parser.add_argument(
           """--t5x_checkpoint_path""", default=None, type=str, required=True, help="""Path the TX5 checkpoint."""
       )
       parser.add_argument("""--config_name""", default=None, type=str, required=True, help="""Config name of T5 model.""")
       parser.add_argument(
           """--flax_dump_folder_path""", default=None, type=str, required=True, help="""Path to the output FLAX model."""
       )
       a     :			Any					    =						parser.parse_args()
       convert_tax_checkpoint_to_flax(args.tax_checkpoint_path, args.config_name, args.flax_dump_folder_path)
style_context: from .balanced_parentheses import balanced_parentheses
  from .stack import Stack
  def 		snake_case__  (		lowercase				):
     return {"+": 1, "-": 1, "*": 2, "/": 2, "^": 3}.get(lowercase       ,							-1				)
  def 		snake_case__  (		lowercase				):
     if not balanced_parentheses(lowercase				):
        raise ValueError("Mismatched parentheses"				)
     lowerCAmelCase_:       Stack[str]         =  Stack()
     lowerCAmelCase_:       Union[str, Any]         =  []
     for char in expression_str:
        if char.isalpha() or char.isdigit():
           postfix.append(lowercase				)
        elif char == "(":
           stack.push(lowercase				)
        elif char == ")":
           while not stack.is_empty() and stack.peek() != "(":
              postfix.append(stack.pop()				)
           stack.pop()
        else:
           while not stack.is_empty() and precedence(lowercase				) <= precedence(stack.peek()				):
              postfix.append(stack.pop()				)
           stack.push(lowercase				)
     while not stack.is_empty():
        postfix.append(stack.pop()				)
     return " ".join(lowercase				)
  
  
  if __name__ == "__main__":
   from doctest import testmod
  
   testmod()
   a     :			int					    =						"""a+b*(c^d-e)^(f+g*h)-i"""
  
   print("""Infix to Postfix Notation demonstration:\n""")
   print("""Infix notation: """ + expression)
   print("""Postfix notation: """ + infix_to_postfix(expression))