



from collections import OrderedDict
from typing import Mapping

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


__SCREAMING_SNAKE_CASE  :						Dict    							=      logging.get_logger(__name__)

__SCREAMING_SNAKE_CASE  :						Dict    							=      {
    '''kssteven/ibert-roberta-base''': '''https://huggingface.co/kssteven/ibert-roberta-base/resolve/main/config.json''',
    '''kssteven/ibert-roberta-large''': '''https://huggingface.co/kssteven/ibert-roberta-large/resolve/main/config.json''',
    '''kssteven/ibert-roberta-large-mnli''': (
        '''https://huggingface.co/kssteven/ibert-roberta-large-mnli/resolve/main/config.json'''
    ),
}


class 							lowerCamelCase_(   __lowercase    ):





					'''simple docstring'''



					lowercase__   :       List[str]										= 'ibert'

					def __init__(    self				,       lowerCamelCase__=3_0_5_2_2				,       lowerCamelCase__=7_6_8				,       lowerCamelCase__=1_2				,       lowerCamelCase__=1_2				,       lowerCamelCase__=3_0_7_2				,       lowerCamelCase__="gelu"				,       lowerCamelCase__=0.1				,       lowerCamelCase__=0.1				,       lowerCamelCase__=5_1_2				,       lowerCamelCase__=2				,       lowerCamelCase__=0.0_2				,       lowerCamelCase__=1e-12				,       lowerCamelCase__=1				,       lowerCamelCase__=0				,       lowerCamelCase__=2				,       lowerCamelCase__="absolute"				,       lowerCamelCase__=False				,       lowerCamelCase__="none"				,       **lowerCamelCase__				,       ):
									super().__init__(pad_token_id=__A				,       bos_token_id=__A				,       eos_token_id=__A				,       **__A   )

									_lowerCamelCase        =				vocab_size
									_lowerCamelCase        =				hidden_size
									_lowerCamelCase        =				num_hidden_layers
									_lowerCamelCase        =				num_attention_heads
									_lowerCamelCase        =				hidden_act
									_lowerCamelCase        =				intermediate_size
									_lowerCamelCase        =				hidden_dropout_prob
									_lowerCamelCase        =				attention_probs_dropout_prob
									_lowerCamelCase        =				max_position_embeddings
									_lowerCamelCase        =				type_vocab_size
									_lowerCamelCase        =				initializer_range
									_lowerCamelCase        =				layer_norm_eps
									_lowerCamelCase        =				position_embedding_type
									_lowerCamelCase        =				quant_mode
									_lowerCamelCase        =				force_dequant


class 							lowerCamelCase_(   __lowercase    ):





					'''simple docstring'''



					@property
					def 			snake_case__      (    self   ):
									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),
									    ]   )





"""simple docstring"""
from __future__ import annotations

from typing import Any



def        lowerCAmelCase_(   lowercase_     :							list[Any]							)	->       None:
				create_state_space_tree(lowercase_						,   []						,   0							)



def        lowerCAmelCase_(   lowercase_     :							list[Any]						,   lowercase_     :							list[Any]						,   lowercase_     :							int							)	->       None:

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

				create_state_space_tree(lowercase_						,   lowercase_						,   index + 1							)
				current_subsequence.append(sequence[index]							)
				create_state_space_tree(lowercase_						,   lowercase_						,   index + 1							)
				current_subsequence.pop()


if __name__ == "__main__":
			__SCREAMING_SNAKE_CASE  :						list[Any]    							=      [3, 1, 2, 4]
			generate_all_subsequences(seq)

			seq.clear()
			seq.extend(['''A''', '''B''', '''C'''])
			generate_all_subsequences(seq)
