


from collections import OrderedDict
from typing import Mapping

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


__lowerCAmelCase		       =							logging.get_logger(__name__)

__lowerCAmelCase		       =							{
    '''facebook/xlm-roberta-xl''': '''https://huggingface.co/facebook/xlm-roberta-xl/resolve/main/config.json''',
    '''facebook/xlm-roberta-xxl''': '''https://huggingface.co/facebook/xlm-roberta-xxl/resolve/main/config.json''',
    # See all XLM-RoBERTa-XL models at https://huggingface.co/models?filter=xlm-roberta-xl
}





class   __a			(    __UpperCamelCase      ):
 __lowercase :							Any        = '''xlm-roberta-xl'''
 def __init__(   self				, lowerCAmelCase__=250_880				, lowerCAmelCase__=2_560				, lowerCAmelCase__=36				, lowerCAmelCase__=32				, lowerCAmelCase__=10_240				, lowerCAmelCase__="gelu"				, lowerCAmelCase__=0.1				, lowerCAmelCase__=0.1				, lowerCAmelCase__=514				, lowerCAmelCase__=1				, lowerCAmelCase__=0.0_2				, lowerCAmelCase__=1E-05				, lowerCAmelCase__=1				, lowerCAmelCase__=0				, lowerCAmelCase__=2				, lowerCAmelCase__="absolute"				, lowerCAmelCase__=True				, lowerCAmelCase__=None				, **lowerCAmelCase__				, )					->				str:




        '''simple docstring'''
        super().__init__(pad_token_id=SCREAMING_SNAKE_CASE__				, bos_token_id=SCREAMING_SNAKE_CASE__				, eos_token_id=SCREAMING_SNAKE_CASE__				, **SCREAMING_SNAKE_CASE__ )
        lowercase__:   Tuple  			=   vocab_size
        lowercase__:   Union[str, Any]  			=   hidden_size
        lowercase__:   List[str]  			=   num_hidden_layers
        lowercase__:   List[str]  			=   num_attention_heads
        lowercase__:   Any  			=   hidden_act
        lowercase__:   Any  			=   intermediate_size
        lowercase__:   Dict  			=   hidden_dropout_prob
        lowercase__:   Tuple  			=   attention_probs_dropout_prob
        lowercase__:   Dict  			=   max_position_embeddings
        lowercase__:   int  			=   type_vocab_size
        lowercase__:   str  			=   initializer_range
        lowercase__:   Tuple  			=   layer_norm_eps
        lowercase__:   Union[str, Any]  			=   position_embedding_type
        lowercase__:   str  			=   use_cache
        lowercase__:   List[str]  			=   classifier_dropout





class   __a			(    __UpperCamelCase      ):
 @property
 def 		SCREAMING_SNAKE_CASE__   (   self )					->				Mapping[str, Mapping[int, str]]:




        '''simple docstring'''






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









"""simple docstring"""
import pytest

from datasets.splits import SplitDict, SplitInfo
from datasets.utils.py_utils import asdict



@pytest.mark.parametrize(
    '''split_dict''' ,   [
        SplitDict(),
        SplitDict({'''train''': SplitInfo(name='''train''' ,   num_bytes=13_37 ,   num_examples=42 ,   dataset_name='''my_dataset'''							)}							),
        SplitDict({'''train''': SplitInfo(name='''train''' ,   num_bytes=13_37 ,   num_examples=42							)}							),
        SplitDict({'''train''': SplitInfo()}							),
    ] ,   )
def      __lowerCamelCase   (							a_     :		SplitDict							)			->      Optional[int]:
      __SCREAMING_SNAKE_CASE   :Tuple						=  split_dict._to_yaml_list()
      assert len(a_							) == len(a_							)
      __SCREAMING_SNAKE_CASE   :Union[str, Any]						=  SplitDict._from_yaml_list(a_							)
      for split_name, split_info in split_dict.items():
            # dataset_name field is deprecated, and is therefore not part of the YAML dump
            __SCREAMING_SNAKE_CASE   :int						=  None
            # the split name of split_dict takes over the name of the split info object
            __SCREAMING_SNAKE_CASE   :Union[str, Any]						=  split_name
      assert split_dict == reloaded







@pytest.mark.parametrize(
    '''split_info''' ,   [SplitInfo(), SplitInfo(dataset_name=a_							), SplitInfo(dataset_name='''my_dataset'''							)]							)
def      __lowerCamelCase   (							a_     :		Dict							)			->      Any:
      # For backward compatibility, we need asdict(split_dict) to return split info dictrionaries with the "dataset_name"
      # field even if it's deprecated. This way old versionso of `datasets` can still reload dataset_infos.json files
      __SCREAMING_SNAKE_CASE   :Union[str, Any]						=  asdict(SplitDict({'''train''': split_info}							)							)
      assert "dataset_name" in split_dict_asdict["train"]
      assert split_dict_asdict["train"]["dataset_name"] == split_info.dataset_name