

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,
)


_UpperCAmelCase		:       int									=	pytest.mark.integration





@pytest.mark.parametrize('path'       ,							['paws', 'csv']				)
def  __lowerCamelCase     (			UpperCamelCase__       ,							UpperCamelCase__				):







							'''simple docstring'''






							inspect_dataset(_UpperCAmelCase       ,							_UpperCAmelCase				)
							snake_case_          =   path + '.py'
							assert script_name in os.listdir(_UpperCAmelCase				)
							assert "__pycache__" not in os.listdir(_UpperCAmelCase				)





@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     (			UpperCamelCase__       ,							UpperCamelCase__				):







							'''simple docstring'''






							inspect_metric(_UpperCAmelCase       ,							_UpperCAmelCase				)
							snake_case_          =   path + '.py'
							assert script_name in os.listdir(_UpperCAmelCase				)
							assert "__pycache__" not in os.listdir(_UpperCAmelCase				)





@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     (			UpperCamelCase__       ,							UpperCamelCase__       ,							UpperCamelCase__				):







							'''simple docstring'''






							snake_case_          =   get_dataset_config_info(_UpperCAmelCase       ,							config_name=_UpperCAmelCase				)
							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     (			UpperCamelCase__       ,							UpperCamelCase__       ,							UpperCamelCase__				):







							'''simple docstring'''






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





@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     (			UpperCamelCase__       ,							UpperCamelCase__				):







							'''simple docstring'''






							snake_case_          =   get_dataset_config_names(_UpperCAmelCase				)
							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     (			UpperCamelCase__       ,							UpperCamelCase__       ,							UpperCamelCase__				):







							'''simple docstring'''






							snake_case_          =   get_dataset_infos(_UpperCAmelCase				)
							assert list(infos.keys()				) == expected_configs
							snake_case_          =   expected_configs[0]
							assert expected_config in infos
							snake_case_          =   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     (			UpperCamelCase__       ,							UpperCamelCase__       ,							UpperCamelCase__				):







							'''simple docstring'''






							snake_case_          =   get_dataset_infos(_UpperCAmelCase				)
							assert expected_config in infos
							snake_case_          =   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     (			UpperCamelCase__       ,							UpperCamelCase__       ,							UpperCamelCase__				):







							'''simple docstring'''






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







from collections import OrderedDict
from typing import Mapping

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


_UpperCAmelCase		:       int						    =	logging.get_logger(__name__)

_UpperCAmelCase		:       Optional[Any]						    =	{
    """junnyu/roformer_chinese_small""": """https://huggingface.co/junnyu/roformer_chinese_small/resolve/main/config.json""",
    """junnyu/roformer_chinese_base""": """https://huggingface.co/junnyu/roformer_chinese_base/resolve/main/config.json""",
    """junnyu/roformer_chinese_char_small""": (
        """https://huggingface.co/junnyu/roformer_chinese_char_small/resolve/main/config.json"""
    ),
    """junnyu/roformer_chinese_char_base""": (
        """https://huggingface.co/junnyu/roformer_chinese_char_base/resolve/main/config.json"""
    ),
    """junnyu/roformer_small_discriminator""": (
        """https://huggingface.co/junnyu/roformer_small_discriminator/resolve/main/config.json"""
    ),
    """junnyu/roformer_small_generator""": (
        """https://huggingface.co/junnyu/roformer_small_generator/resolve/main/config.json"""
    ),
    # See all RoFormer models at https://huggingface.co/models?filter=roformer
}







class 			lowercase    (	lowercase_      ):
				__SCREAMING_SNAKE_CASE :			List[Any]	      =      '''roformer'''




				def __init__( self				,       snake_case=5_0000				,       snake_case=None				,       snake_case=768				,       snake_case=12				,       snake_case=12				,       snake_case=3072				,       snake_case="gelu"				,       snake_case=0.1				,       snake_case=0.1				,       snake_case=1536				,       snake_case=2				,       snake_case=0.02				,       snake_case=1e-1_2				,       snake_case=0				,       snake_case=False				,       snake_case=True				,       **snake_case				,       ):
											super().__init__(pad_token_id=snake_case				,       **snake_case	)

											snake_case_          =   vocab_size
											snake_case_          =   hidden_size if embedding_size is None else embedding_size
											snake_case_          =   hidden_size
											snake_case_          =   num_hidden_layers
											snake_case_          =   num_attention_heads
											snake_case_          =   hidden_act
											snake_case_          =   intermediate_size
											snake_case_          =   hidden_dropout_prob
											snake_case_          =   attention_probs_dropout_prob
											snake_case_          =   max_position_embeddings
											snake_case_          =   type_vocab_size
											snake_case_          =   initializer_range
											snake_case_          =   layer_norm_eps
											snake_case_          =   rotary_value
											snake_case_          =   use_cache







class 			lowercase    (	lowercase_      ):




				@property
				def    a							( self	):
											if self.task == "multiple-choice":
																		snake_case_          =   {0: 'batch', 1: 'choice', 2: 'sequence'}
											else:
																		snake_case_          =   {0: 'batch', 1: 'sequence'}
											snake_case_          =   {0: 'batch', 1: 'sequence'}
											return OrderedDict(
											    [
											        ('input_ids', dynamic_axis),
											        ('attention_mask', dynamic_axis),
											        ('token_type_ids', dynamic_axis),
											    ]	)




