
from __future__ import annotations

from typing import Dict

from ...configuration_utils import PretrainedConfig


UpperCamelCase			:       List[str]									=				{
    "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 __lowerCAmelCase	(   __lowerCamelCase    ):
     lowercase		     =		"ernie_m"
     lowercase		     =		{"dropout": "classifier_dropout", "num_classes": "num_labels"}





     def __init__(			self			,  __UpperCAmelCase = 25_0002			,  __UpperCAmelCase = 768			,  __UpperCAmelCase = 12			,  __UpperCAmelCase = 12			,  __UpperCAmelCase = 3072			,  __UpperCAmelCase = "gelu"			,  __UpperCAmelCase = 0.1			,  __UpperCAmelCase = 0.1			,  __UpperCAmelCase = 514			,  __UpperCAmelCase = 0.0_2			,  __UpperCAmelCase = 1			,  __UpperCAmelCase = 1E-05			,  __UpperCAmelCase=None			,  __UpperCAmelCase=False			,  __UpperCAmelCase=0.0			,  **__UpperCAmelCase			,  ):

      '''simple docstring'''




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





"""simple docstring"""

import re

from filelock import FileLock


try:
      import nltk

      UpperCamelCase			:       int									=				True
except (ImportError, ModuleNotFoundError):
      UpperCamelCase			:       List[str]									=				False

if NLTK_AVAILABLE:
      with FileLock(".lock") as lock:
            nltk.download("punkt", quiet=True)






def 							A		(       snake_case   :str	)   ->			str:
 re.sub('<n>'       ,      ''       ,      snake_case	)  # remove pegasus newline char
 assert NLTK_AVAILABLE, "nltk must be installed to separate newlines between sentences. (pip install nltk)"
 return "\n".join(nltk.sent_tokenize(snake_case	)	)



