





import pytest

from datasets.utils.sharding import _distribute_shards, _number_of_shards_in_gen_kwargs, _split_gen_kwargs







@pytest.mark.parametrize(
    """kwargs, expected"""   ,					[
        ({"""num_shards""": 0, """max_num_jobs""": 1}, []),
        ({"""num_shards""": 1_0, """max_num_jobs""": 1}, [range(1_0   )]),
        ({"""num_shards""": 1_0, """max_num_jobs""": 1_0}, [range(__a   ,					i + 1   ) for i in range(1_0   )]),
        ({"""num_shards""": 1, """max_num_jobs""": 1_0}, [range(1   )]),
        ({"""num_shards""": 1_0, """max_num_jobs""": 3}, [range(0   ,					4   ), range(4   ,					7   ), range(7   ,					1_0   )]),
        ({"""num_shards""": 3, """max_num_jobs""": 1_0}, [range(0   ,					1   ), range(1   ,					2   ), range(2   ,					3   )]),
    ]   ,					)
def        __lowerCamelCase (							__a       :int   ,					__a       :Dict   )		->    Union[str, Any]:






  """simple docstring"""

  A__  				=       _distribute_shards(**__a   )
  assert out == expected







@pytest.mark.parametrize(
    """gen_kwargs, max_num_jobs, expected"""   ,					[
        ({"""foo""": 0}, 1_0, [{"""foo""": 0}]),
        ({"""shards""": [0, 1, 2, 3]}, 1, [{"""shards""": [0, 1, 2, 3]}]),
        ({"""shards""": [0, 1, 2, 3]}, 4, [{"""shards""": [0]}, {"""shards""": [1]}, {"""shards""": [2]}, {"""shards""": [3]}]),
        ({"""shards""": [0, 1]}, 4, [{"""shards""": [0]}, {"""shards""": [1]}]),
        ({"""shards""": [0, 1, 2, 3]}, 2, [{"""shards""": [0, 1]}, {"""shards""": [2, 3]}]),
    ]   ,					)
def        __lowerCamelCase (							__a       :Optional[int]   ,					__a       :int   ,					__a       :str   )		->    Tuple:






  """simple docstring"""

  A__  				=       _split_gen_kwargs(__a   ,					__a   )
  assert out == expected







@pytest.mark.parametrize(
    """gen_kwargs, expected"""   ,					[
        ({"""foo""": 0}, 1),
        ({"""shards""": [0]}, 1),
        ({"""shards""": [0, 1, 2, 3]}, 4),
        ({"""shards""": [0, 1, 2, 3], """foo""": 0}, 4),
        ({"""shards""": [0, 1, 2, 3], """other""": (0, 1)}, 4),
        ({"""shards""": [0, 1, 2, 3], """shards2""": [0, 1]}, RuntimeError),
    ]   ,					)
def        __lowerCamelCase (							__a       :Optional[int]   ,					__a       :List[str]   )		->    Union[str, Any]:






  """simple docstring"""

  if expected is RuntimeError:
    with pytest.raises(__a   ):
      _number_of_shards_in_gen_kwargs(__a   )
  else:
    A__  				=       _number_of_shards_in_gen_kwargs(__a   )
    assert out == expected










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   : Optional[int]			=				{
    '''roberta-base''': '''https://huggingface.co/roberta-base/resolve/main/config.json''',
    '''roberta-large''': '''https://huggingface.co/roberta-large/resolve/main/config.json''',
    '''roberta-large-mnli''': '''https://huggingface.co/roberta-large-mnli/resolve/main/config.json''',
    '''distilroberta-base''': '''https://huggingface.co/distilroberta-base/resolve/main/config.json''',
    '''roberta-base-openai-detector''': '''https://huggingface.co/roberta-base-openai-detector/resolve/main/config.json''',
    '''roberta-large-openai-detector''': '''https://huggingface.co/roberta-large-openai-detector/resolve/main/config.json''',
}


class   A      (SCREAMING_SNAKE_CASE   ):
			'''simple docstring'''




			__lowerCamelCase     :	Union[str, Any]          =   '''roberta'''






			def __init__(      self       :   Any							,     __lowerCAmelCase       :   Tuple=5_02_65							,     __lowerCAmelCase       :   Optional[int]=7_68							,     __lowerCAmelCase       :   Union[str, Any]=12							,     __lowerCAmelCase       :   Dict=12							,     __lowerCAmelCase       :   Optional[Any]=30_72							,     __lowerCAmelCase       :   Any="gelu"							,     __lowerCAmelCase       :   Optional[Any]=0.1							,     __lowerCAmelCase       :   Optional[int]=0.1							,     __lowerCAmelCase       :   Optional[Any]=5_12							,     __lowerCAmelCase       :   int=2							,     __lowerCAmelCase       :   List[str]=0.0_2							,     __lowerCAmelCase       :   Dict=1e-12							,     __lowerCAmelCase       :   Optional[int]=1							,     __lowerCAmelCase       :   Tuple=0							,     __lowerCAmelCase       :   int=2							,     __lowerCAmelCase       :   Dict="absolute"							,     __lowerCAmelCase       :   Optional[Any]=True							,     __lowerCAmelCase       :   Union[str, Any]=None							,     **__lowerCAmelCase       :   str							,     )     ->     str:







					"""simple docstring"""






					super().__init__(pad_token_id=__lowerCAmelCase							,     bos_token_id=__lowerCAmelCase							,     eos_token_id=__lowerCAmelCase							,     **__lowerCAmelCase       )

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


class   A      (SCREAMING_SNAKE_CASE   ):
			'''simple docstring'''




			@property
			def        a_	(      self       :   int       )     ->     Mapping[str, Mapping[int, str]]:







					"""simple docstring"""






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



