





from __future__ import annotations






def lowerCamelCase__    (							snake_case_	:  list[int | str]       )      ->				None:
   create_state_space_tree(snake_case_       ,      []       ,      0       ,      [0 for i in range(len(snake_case_       )       )]       )






def lowerCamelCase__    (							snake_case_	:  list[int | str]       ,      snake_case_	:  list[int | str]       ,      snake_case_	:  int       ,      snake_case_	:  list[int]       ,      )      ->				None:

   if index == len(snake_case_       ):
      print(snake_case_       )
      return

   for i in range(len(snake_case_       )       ):
      if not index_used[i]:
         current_sequence.append(sequence[i]       )
         __snake_case							       =   True
         create_state_space_tree(snake_case_       ,      snake_case_       ,      index + 1       ,      snake_case_       )
         current_sequence.pop()
         __snake_case							       =   False
snake_case_				=			[3, 1, 2, 4]
generate_all_permutations(sequence)

snake_case_				=			["A", "B", "C"]







generate_all_permutations(sequence_a)


'''simple docstring'''




from __future__ import annotations

from typing import Dict

from ...configuration_utils import PretrainedConfig


__lowercase          =  {
    '''susnato/ernie-m-base_pytorch''': '''https://huggingface.co/susnato/ernie-m-base_pytorch/blob/main/config.json''',
    '''susnato/ernie-m-large_pytorch''': '''https://huggingface.co/susnato/ernie-m-large_pytorch/blob/main/config.json''',
}






class 				a__(					lowerCAmelCase__	):


			'''simple docstring'''






			UpperCAmelCase_			:     List[str]      =       '''ernie_m'''
			UpperCAmelCase_			:     Dict[str, str]      =       {"dropout": "classifier_dropout", "num_classes": "num_labels"}



			def __init__(   self       ,    __lowerCAmelCase = 250002       ,    __lowerCAmelCase = 768       ,    __lowerCAmelCase = 12       ,    __lowerCAmelCase = 12       ,    __lowerCAmelCase = 3072       ,    __lowerCAmelCase = "gelu"       ,    __lowerCAmelCase = 0.1       ,    __lowerCAmelCase = 0.1       ,    __lowerCAmelCase = 514       ,    __lowerCAmelCase = 0.02       ,    __lowerCAmelCase = 1       ,    __lowerCAmelCase = 1E-0_5       ,    __lowerCAmelCase=None       ,    __lowerCAmelCase=False       ,    __lowerCAmelCase=0.0       ,    **__lowerCAmelCase       ,    ):




					"""simple docstring"""


					super().__init__(pad_token_id=__lowerCAmelCase       ,    **__lowerCAmelCase)
					lowerCAmelCase   					=  vocab_size
					lowerCAmelCase   					=  hidden_size
					lowerCAmelCase   					=  num_hidden_layers
					lowerCAmelCase   					=  num_attention_heads
					lowerCAmelCase   					=  intermediate_size
					lowerCAmelCase   					=  hidden_act
					lowerCAmelCase   					=  hidden_dropout_prob
					lowerCAmelCase   					=  attention_probs_dropout_prob
					lowerCAmelCase   					=  max_position_embeddings
					lowerCAmelCase   					=  initializer_range
					lowerCAmelCase   					=  layer_norm_eps
					lowerCAmelCase   					=  classifier_dropout
					lowerCAmelCase   					=  is_decoder
					lowerCAmelCase   					=  act_dropout




