





import os

import pytest

from datasets import (
    get_dataset_config_info,
    get_dataset_config_names,
    get_dataset_infos,
    get_dataset_split_names,
    inspect_dataset,
    inspect_metric,
)


A   : Tuple			=				pytest.mark.integration







@pytest.mark.parametrize("""path"""   ,					["""paws""", """csv"""]   )
def        __lowerCamelCase (							__a       :Union[str, Any]   ,					__a       :Optional[Any]   )		->    Optional[int]:






  """simple docstring"""

  inspect_dataset(__a   ,					__a   )
  A__  				=       path + """.py"""
  assert script_name in os.listdir(__a   )
  assert "__pycache__" not in os.listdir(__a   )







@pytest.mark.filterwarnings("""ignore:inspect_metric is deprecated:FutureWarning"""   )
@pytest.mark.filterwarnings("""ignore:metric_module_factory is deprecated:FutureWarning"""   )
@pytest.mark.parametrize("""path"""   ,					["""accuracy"""]   )
def        __lowerCamelCase (							__a       :Optional[int]   ,					__a       :Dict   )		->    List[str]:






  """simple docstring"""

  inspect_metric(__a   ,					__a   )
  A__  				=       path + """.py"""
  assert script_name in os.listdir(__a   )
  assert "__pycache__" not in os.listdir(__a   )







@pytest.mark.parametrize(
    """path, config_name, expected_splits"""   ,					[
        ("""squad""", """plain_text""", ["""train""", """validation"""]),
        ("""dalle-mini/wit""", """dalle-mini--wit""", ["""train"""]),
        ("""paws""", """labeled_final""", ["""train""", """test""", """validation"""]),
    ]   ,					)
def        __lowerCamelCase (							__a       :Optional[int]   ,					__a       :Optional[int]   ,					__a       :int   )		->    str:






  """simple docstring"""

  A__  				=       get_dataset_config_info(__a   ,					config_name=__a   )
  assert info.config_name == config_name
  assert list(info.splits.keys()   ) == expected_splits







@pytest.mark.parametrize(
    """path, config_name, expected_exception"""   ,					[
        ("""paws""", None, ValueError),
    ]   ,					)
def        __lowerCamelCase (							__a       :Optional[Any]   ,					__a       :Dict   ,					__a       :Optional[int]   )		->    List[Any]:






  """simple docstring"""

  with pytest.raises(__a   ):
    get_dataset_config_info(__a   ,					config_name=__a   )







@pytest.mark.parametrize(
    """path, expected"""   ,					[
        ("""squad""", """plain_text"""),
        ("""acronym_identification""", """default"""),
        ("""lhoestq/squad""", """plain_text"""),
        ("""lhoestq/test""", """default"""),
        ("""lhoestq/demo1""", """lhoestq--demo1"""),
        ("""dalle-mini/wit""", """dalle-mini--wit"""),
    ]   ,					)
def        __lowerCamelCase (							__a       :Dict   ,					__a       :List[str]   )		->    str:






  """simple docstring"""

  A__  				=       get_dataset_config_names(__a   )
  assert expected in config_names







@pytest.mark.parametrize(
    """path, expected_configs, expected_splits_in_first_config"""   ,					[
        ("""squad""", ["""plain_text"""], ["""train""", """validation"""]),
        ("""dalle-mini/wit""", ["""dalle-mini--wit"""], ["""train"""]),
        ("""paws""", ["""labeled_final""", """labeled_swap""", """unlabeled_final"""], ["""train""", """test""", """validation"""]),
    ]   ,					)
def        __lowerCamelCase (							__a       :str   ,					__a       :Any   ,					__a       :List[Any]   )		->    Any:






  """simple docstring"""

  A__  				=       get_dataset_infos(__a   )
  assert list(infos.keys()   ) == expected_configs
  A__  				=       expected_configs[0]
  assert expected_config in infos
  A__  				=       infos[expected_config]
  assert info.config_name == expected_config
  assert list(info.splits.keys()   ) == expected_splits_in_first_config







@pytest.mark.parametrize(
    """path, expected_config, expected_splits"""   ,					[
        ("""squad""", """plain_text""", ["""train""", """validation"""]),
        ("""dalle-mini/wit""", """dalle-mini--wit""", ["""train"""]),
        ("""paws""", """labeled_final""", ["""train""", """test""", """validation"""]),
    ]   ,					)
def        __lowerCamelCase (							__a       :Any   ,					__a       :int   ,					__a       :Union[str, Any]   )		->    Tuple:






  """simple docstring"""

  A__  				=       get_dataset_infos(__a   )
  assert expected_config in infos
  A__  				=       infos[expected_config]
  assert info.config_name == expected_config
  assert list(info.splits.keys()   ) == expected_splits







@pytest.mark.parametrize(
    """path, config_name, expected_exception"""   ,					[
        ("""paws""", None, ValueError),
    ]   ,					)
def        __lowerCamelCase (							__a       :Optional[int]   ,					__a       :Any   ,					__a       :Tuple   )		->    Dict:






  """simple docstring"""

  with pytest.raises(__a   ):
    get_dataset_split_names(__a   ,					config_name=__a   )










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


A   : Dict			=				logging.get_logger(__name__)

A   : Dict			=				{
    '''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   A      (SCREAMING_SNAKE_CASE   ):
			'''simple docstring'''




			__lowerCamelCase     :	Tuple          =   '''pegasus'''
			__lowerCamelCase     :	Any          =   ['''past_key_values''']
			__lowerCamelCase     :	List[str]          =   {'''num_attention_heads''': '''encoder_attention_heads''', '''hidden_size''': '''d_model'''}






			def __init__(      self       :   List[Any]							,     __lowerCAmelCase       :   str=5_02_65							,     __lowerCAmelCase       :   Dict=10_24							,     __lowerCAmelCase       :   Union[str, Any]=12							,     __lowerCAmelCase       :   Any=40_96							,     __lowerCAmelCase       :   Optional[Any]=16							,     __lowerCAmelCase       :   Dict=12							,     __lowerCAmelCase       :   Optional[int]=40_96							,     __lowerCAmelCase       :   Dict=16							,     __lowerCAmelCase       :   Optional[int]=0.0							,     __lowerCAmelCase       :   Optional[Any]=0.0							,     __lowerCAmelCase       :   Union[str, Any]=True							,     __lowerCAmelCase       :   List[str]=True							,     __lowerCAmelCase       :   str="gelu"							,     __lowerCAmelCase       :   Union[str, Any]=10_24							,     __lowerCAmelCase       :   Union[str, Any]=0.1							,     __lowerCAmelCase       :   Dict=0.0							,     __lowerCAmelCase       :   Union[str, Any]=0.0							,     __lowerCAmelCase       :   Union[str, Any]=0.0_2							,     __lowerCAmelCase       :   List[Any]=0							,     __lowerCAmelCase       :   str=False							,     __lowerCAmelCase       :   int=0							,     __lowerCAmelCase       :   Optional[Any]=1							,     __lowerCAmelCase       :   Optional[int]=1							,     **__lowerCAmelCase       :   Dict							,     )     ->     Dict:







					"""simple docstring"""






					A__  				=       vocab_size
					A__  				=       max_position_embeddings
					A__  				=       d_model
					A__  				=       encoder_ffn_dim
					A__  				=       encoder_layers
					A__  				=       encoder_attention_heads
					A__  				=       decoder_ffn_dim
					A__  				=       decoder_layers
					A__  				=       decoder_attention_heads
					A__  				=       dropout
					A__  				=       attention_dropout
					A__  				=       activation_dropout
					A__  				=       activation_function
					A__  				=       init_std
					A__  				=       encoder_layerdrop
					A__  				=       decoder_layerdrop
					A__  				=       use_cache
					A__  				=       encoder_layers
					A__  				=       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        a_	(      self       :   Dict       )     ->     int:







					"""simple docstring"""






					return self.encoder_attention_heads







			@property
			def        a_	(      self       :   Optional[Any]       )     ->     int:







					"""simple docstring"""






					return self.d_model



