





from collections import OrderedDict
from typing import Mapping

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


_A				:							Tuple							= logging.get_logger(__name__)

_A				:							Union[str, Any]							= {
    """nghuyong/ernie-1.0-base-zh""": """https://huggingface.co/nghuyong/ernie-1.0-base-zh/resolve/main/config.json""",
    """nghuyong/ernie-2.0-base-en""": """https://huggingface.co/nghuyong/ernie-2.0-base-en/resolve/main/config.json""",
    """nghuyong/ernie-2.0-large-en""": """https://huggingface.co/nghuyong/ernie-2.0-large-en/resolve/main/config.json""",
    """nghuyong/ernie-3.0-base-zh""": """https://huggingface.co/nghuyong/ernie-3.0-base-zh/resolve/main/config.json""",
    """nghuyong/ernie-3.0-medium-zh""": """https://huggingface.co/nghuyong/ernie-3.0-medium-zh/resolve/main/config.json""",
    """nghuyong/ernie-3.0-mini-zh""": """https://huggingface.co/nghuyong/ernie-3.0-mini-zh/resolve/main/config.json""",
    """nghuyong/ernie-3.0-micro-zh""": """https://huggingface.co/nghuyong/ernie-3.0-micro-zh/resolve/main/config.json""",
    """nghuyong/ernie-3.0-nano-zh""": """https://huggingface.co/nghuyong/ernie-3.0-nano-zh/resolve/main/config.json""",
    """nghuyong/ernie-gram-zh""": """https://huggingface.co/nghuyong/ernie-gram-zh/resolve/main/config.json""",
    """nghuyong/ernie-health-zh""": """https://huggingface.co/nghuyong/ernie-health-zh/resolve/main/config.json""",
}



class 				__snake_case  (     __SCREAMING_SNAKE_CASE						):


    '''simple docstring'''







    lowerCamelCase__						:		int							=  """ernie"""



    def __init__(					self      ,							A_=3_05_22      ,							A_=7_68      ,							A_=12      ,							A_=12      ,							A_=30_72      ,							A_="gelu"      ,							A_=0.1      ,							A_=0.1      ,							A_=5_12      ,							A_=2      ,							A_=3      ,							A_=False      ,							A_=0.02      ,							A_=1E-12      ,							A_=0      ,							A_="absolute"      ,							A_=True      ,							A_=None      ,							**A_      ,							):





        '''simple docstring'''

        super().__init__(pad_token_id=A_      ,							**A_    )

        SCREAMING_SNAKE_CASE__       							= vocab_size
        SCREAMING_SNAKE_CASE__       							= hidden_size
        SCREAMING_SNAKE_CASE__       							= num_hidden_layers
        SCREAMING_SNAKE_CASE__       							= num_attention_heads
        SCREAMING_SNAKE_CASE__       							= hidden_act
        SCREAMING_SNAKE_CASE__       							= intermediate_size
        SCREAMING_SNAKE_CASE__       							= hidden_dropout_prob
        SCREAMING_SNAKE_CASE__       							= attention_probs_dropout_prob
        SCREAMING_SNAKE_CASE__       							= max_position_embeddings
        SCREAMING_SNAKE_CASE__       							= type_vocab_size
        SCREAMING_SNAKE_CASE__       							= task_type_vocab_size
        SCREAMING_SNAKE_CASE__       							= use_task_id
        SCREAMING_SNAKE_CASE__       							= initializer_range
        SCREAMING_SNAKE_CASE__       							= layer_norm_eps
        SCREAMING_SNAKE_CASE__       							= position_embedding_type
        SCREAMING_SNAKE_CASE__       							= use_cache
        SCREAMING_SNAKE_CASE__       							= classifier_dropout





class 				__snake_case  (     __SCREAMING_SNAKE_CASE						):


    '''simple docstring'''







    @property
    def    lowercase_				(					self    ):





        '''simple docstring'''

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







from __future__ import annotations

from collections.abc import Generator


def        __snake_case       (						lowerCAmelCase_  )							->	Generator[int, None, None]:
    if not isinstance(lowerCAmelCase_   ,       lowerCAmelCase_  ) or n < 1:
        raise Exception('''Sequence only defined for positive integers'''  )

    yield n
    while n != 1:
        if n % 2 == 0:
            n //= 2
        else:
            SCREAMING_SNAKE_CASE__       							= 3 * n + 1
        yield n


def        __snake_case       (						)							->	str:
    SCREAMING_SNAKE_CASE__       							= 4_3
    SCREAMING_SNAKE_CASE__       							= tuple(collatz_sequence(lowerCAmelCase_  )  )
    print(lowerCAmelCase_  )
    print(f'''Collatz sequence from {n} took {len(lowerCAmelCase_  )} steps.'''  )


if __name__ == "__main__":
  main()
