


from __future__ import annotations

from typing import Dict

from ...configuration_utils import PretrainedConfig


__UpperCAmelCase : Tuple 			=				{
    "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    UpperCAmelCase_	(							_a):
       '''simple docstring'''
       __UpperCamelCase      :     List[str]							=					"ernie_m"
       __UpperCamelCase      :     Dict[str, str]							=					{"dropout": "classifier_dropout", "num_classes": "num_labels"}






       def __init__(     self ,					__SCREAMING_SNAKE_CASE = 250_002 ,					__SCREAMING_SNAKE_CASE = 768 ,					__SCREAMING_SNAKE_CASE = 12 ,					__SCREAMING_SNAKE_CASE = 12 ,					__SCREAMING_SNAKE_CASE = 3_072 ,					__SCREAMING_SNAKE_CASE = "gelu" ,					__SCREAMING_SNAKE_CASE = 0.1 ,					__SCREAMING_SNAKE_CASE = 0.1 ,					__SCREAMING_SNAKE_CASE = 514 ,					__SCREAMING_SNAKE_CASE = 0.02 ,					__SCREAMING_SNAKE_CASE = 1 ,					__SCREAMING_SNAKE_CASE = 1e-05 ,					__SCREAMING_SNAKE_CASE=None ,					__SCREAMING_SNAKE_CASE=False ,					__SCREAMING_SNAKE_CASE=0.0 ,					**__SCREAMING_SNAKE_CASE ,					):




              """simple docstring"""




              super().__init__(pad_token_id=__SCREAMING_SNAKE_CASE ,					**__SCREAMING_SNAKE_CASE						)
              UpperCamelCase    :	List[Any]   	=		vocab_size
              UpperCamelCase    :	List[Any]   	=		hidden_size
              UpperCamelCase    :	Dict   	=		num_hidden_layers
              UpperCamelCase    :	Optional[int]   	=		num_attention_heads
              UpperCamelCase    :	Tuple   	=		intermediate_size
              UpperCamelCase    :	List[Any]   	=		hidden_act
              UpperCamelCase    :	Optional[Any]   	=		hidden_dropout_prob
              UpperCamelCase    :	List[str]   	=		attention_probs_dropout_prob
              UpperCamelCase    :	int   	=		max_position_embeddings
              UpperCamelCase    :	Optional[Any]   	=		initializer_range
              UpperCamelCase    :	Union[str, Any]   	=		layer_norm_eps
              UpperCamelCase    :	Any   	=		classifier_dropout
              UpperCamelCase    :	List[Any]   	=		is_decoder
              UpperCamelCase    :	Union[str, Any]   	=		act_dropout





import re
from pathlib import Path
from unittest import TestCase

import pytest



@pytest.mark.integration
class    UpperCAmelCase_	(							_a):
       '''simple docstring'''






       def  _lowercase   (     self ,					__SCREAMING_SNAKE_CASE						):




              """simple docstring"""




              with open(__SCREAMING_SNAKE_CASE ,					encoding='''utf-8'''						) as input_file:
                     UpperCamelCase    :	str   	=		re.compile(R'''(?!.*\b(?:encoding|rb|w|wb|w+|wb+|ab|ab+)\b)(?<=\s)(open)\((.*)\)'''						)
                     UpperCamelCase    :	Optional[int]   	=		input_file.read()
                     UpperCamelCase    :	Union[str, Any]   	=		regexp.search(__SCREAMING_SNAKE_CASE						)

              return match






       def  _lowercase   (     self ,					__SCREAMING_SNAKE_CASE						):




              """simple docstring"""




              with open(__SCREAMING_SNAKE_CASE ,					encoding='''utf-8'''						) as input_file:
                     UpperCamelCase    :	Optional[int]   	=		re.compile(R'''#[^\r\n]*print\(|\"[^\r\n]*print\(|\"\"\".*?print\(.*?\"\"\"|(print\()''' ,					re.DOTALL						)
                     UpperCamelCase    :	Tuple   	=		input_file.read()
                     # use `re.finditer` to handle the case where the ignored groups would be matched first by `re.search`
                     UpperCamelCase    :	Dict   	=		regexp.finditer(__SCREAMING_SNAKE_CASE						)

              UpperCamelCase    :	int   	=		[match for match in matches if match is not None and match.group(1						) is not None]
              return matches[0] if matches else None






       def  _lowercase   (     self						):




              """simple docstring"""




              UpperCamelCase    :	int   	=		Path('''./datasets'''						)
              UpperCamelCase    :	Tuple   	=		list(dataset_paths.absolute().glob('''**/*.py'''						)						)

              for dataset in dataset_files:
                     if self._no_encoding_on_file_open(str(__SCREAMING_SNAKE_CASE						)						):
                            raise AssertionError(f"""open(...) must use utf-8 encoding in {dataset}"""						)






       def  _lowercase   (     self						):




              """simple docstring"""




              UpperCamelCase    :	Optional[int]   	=		Path('''./datasets'''						)
              UpperCamelCase    :	Tuple   	=		list(dataset_paths.absolute().glob('''**/*.py'''						)						)

              for dataset in dataset_files:
                     if self._no_print_statements(str(__SCREAMING_SNAKE_CASE						)						):
                            raise AssertionError(f"""print statement found in {dataset}. Use datasets.logger/logging instead."""						)

