





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': 10, 'max_num_jobs': 1}, [range(10	)]),
        ({'num_shards': 10, 'max_num_jobs': 10}, [range(lowerCAmelCase_,	i + 1	) for i in range(10	)]),
        ({'num_shards': 1, 'max_num_jobs': 10}, [range(1	)]),
        ({'num_shards': 10, 'max_num_jobs': 3}, [range(0,	4	), range(4,	7	), range(7,	10	)]),
        ({'num_shards': 3, 'max_num_jobs': 10}, [range(0,	1	), range(1,	2	), range(2,	3	)]),
    ],	)
def   a_    ( lowerCAmelCase_      :			Optional[Any],	lowerCAmelCase_      :			Any	):
   __lowerCAmelCase								=	_distribute_shards(**lowerCAmelCase_	)
   assert out == expected

@pytest.mark.parametrize(
    'gen_kwargs, max_num_jobs, expected',	[
        ({'foo': 0}, 10, [{'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   a_    ( lowerCAmelCase_      :			Optional[Any],	lowerCAmelCase_      :			List[str],	lowerCAmelCase_      :			Optional[int]	):
   __lowerCAmelCase								=	_split_gen_kwargs(lowerCAmelCase_,	lowerCAmelCase_	)
   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   a_    ( lowerCAmelCase_      :			int,	lowerCAmelCase_      :			Any	):
   if expected is RuntimeError:
      with pytest.raises(lowerCAmelCase_	):
         _number_of_shards_in_gen_kwargs(lowerCAmelCase_	)
   else:
      __lowerCAmelCase								=	_number_of_shards_in_gen_kwargs(lowerCAmelCase_	)
      assert out == expected








from ...configuration_utils import PretrainedConfig
from ...utils import logging


_snake_case  :    List[Any]						    =  logging.get_logger(__name__)

_snake_case  :    Any						    =  {
    'google/pegasus-large': 'https://huggingface.co/google/pegasus-large/resolve/main/config.json',
    # See all PEGASUS models at https://huggingface.co/models?filter=pegasus
}



class 				_UpperCAmelCase    (    _UpperCamelCase    ):

  """simple docstring"""


  a_        = """pegasus"""
  a_        = ["""past_key_values"""]
  a_        = {"""num_attention_heads""": """encoder_attention_heads""", """hidden_size""": """d_model"""}






  def __init__(				self :		List[str]					,  lowerCAmelCase_ :		Union[str, Any]=5_0_2_6_5					,  lowerCAmelCase_ :		Union[str, Any]=1_0_2_4					,  lowerCAmelCase_ :		Union[str, Any]=1_2					,  lowerCAmelCase_ :		Dict=4_0_9_6					,  lowerCAmelCase_ :		str=1_6					,  lowerCAmelCase_ :		List[Any]=1_2					,  lowerCAmelCase_ :		Union[str, Any]=4_0_9_6					,  lowerCAmelCase_ :		Union[str, Any]=1_6					,  lowerCAmelCase_ :		Any=0.0					,  lowerCAmelCase_ :		Optional[int]=0.0					,  lowerCAmelCase_ :		List[Any]=True					,  lowerCAmelCase_ :		Any=True					,  lowerCAmelCase_ :		Dict="gelu"					,  lowerCAmelCase_ :		Optional[int]=1_0_2_4					,  lowerCAmelCase_ :		List[str]=0.1					,  lowerCAmelCase_ :		str=0.0					,  lowerCAmelCase_ :		Union[str, Any]=0.0					,  lowerCAmelCase_ :		Optional[int]=0.02					,  lowerCAmelCase_ :		Tuple=0					,  lowerCAmelCase_ :		Tuple=False					,  lowerCAmelCase_ :		Union[str, Any]=0					,  lowerCAmelCase_ :		int=1					,  lowerCAmelCase_ :		Tuple=1					,  **lowerCAmelCase_ :		Tuple					,  )							->						List[str]:
     __lowerCAmelCase								=	vocab_size
     __lowerCAmelCase								=	max_position_embeddings
     __lowerCAmelCase								=	d_model
     __lowerCAmelCase								=	encoder_ffn_dim
     __lowerCAmelCase								=	encoder_layers
     __lowerCAmelCase								=	encoder_attention_heads
     __lowerCAmelCase								=	decoder_ffn_dim
     __lowerCAmelCase								=	decoder_layers
     __lowerCAmelCase								=	decoder_attention_heads
     __lowerCAmelCase								=	dropout
     __lowerCAmelCase								=	attention_dropout
     __lowerCAmelCase								=	activation_dropout
     __lowerCAmelCase								=	activation_function
     __lowerCAmelCase								=	init_std
     __lowerCAmelCase								=	encoder_layerdrop
     __lowerCAmelCase								=	decoder_layerdrop
     __lowerCAmelCase								=	use_cache
     __lowerCAmelCase								=	encoder_layers
     __lowerCAmelCase								=	scale_embedding  # scale factor will be sqrt(d_model) if True
     super().__init__(
         pad_token_id=lowerCAmelCase_					,  eos_token_id=lowerCAmelCase_					,  is_encoder_decoder=lowerCAmelCase_					,  decoder_start_token_id=lowerCAmelCase_					,  forced_eos_token_id=lowerCAmelCase_					,  **lowerCAmelCase_					,  )






  @property
  def 				lowercase		(				self :		List[Any]     )							->						int:
     return self.encoder_attention_heads






  @property
  def 				lowercase		(				self :		Optional[Any]     )							->						int:
     return self.d_model

