




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


a													=			logging.get_logger(__name__)

a													=			{
    "microsoft/biogpt": "https://huggingface.co/microsoft/biogpt/resolve/main/config.json",
    # See all BioGPT models at https://huggingface.co/models?filter=biogpt
}




class       lowerCamelCase				(		__lowercase     ):
		__a					    =       """biogpt"""






		def __init__(    self						,		_SCREAMING_SNAKE_CASE=4_2384						,		_SCREAMING_SNAKE_CASE=1024						,		_SCREAMING_SNAKE_CASE=24						,		_SCREAMING_SNAKE_CASE=16						,		_SCREAMING_SNAKE_CASE=4096						,		_SCREAMING_SNAKE_CASE="gelu"						,		_SCREAMING_SNAKE_CASE=0.1						,		_SCREAMING_SNAKE_CASE=0.1						,		_SCREAMING_SNAKE_CASE=1024						,		_SCREAMING_SNAKE_CASE=0.02						,		_SCREAMING_SNAKE_CASE=1e-12						,		_SCREAMING_SNAKE_CASE=True						,		_SCREAMING_SNAKE_CASE=True						,		_SCREAMING_SNAKE_CASE=0.0						,		_SCREAMING_SNAKE_CASE=0.0						,		_SCREAMING_SNAKE_CASE=1						,		_SCREAMING_SNAKE_CASE=0						,		_SCREAMING_SNAKE_CASE=2						,		**_SCREAMING_SNAKE_CASE						,		):
								_UpperCAmelCase      =			vocab_size
								_UpperCAmelCase      =			max_position_embeddings
								_UpperCAmelCase      =			hidden_size
								_UpperCAmelCase      =			num_hidden_layers
								_UpperCAmelCase      =			num_attention_heads
								_UpperCAmelCase      =			intermediate_size
								_UpperCAmelCase      =			hidden_act
								_UpperCAmelCase      =			hidden_dropout_prob
								_UpperCAmelCase      =			attention_probs_dropout_prob
								_UpperCAmelCase      =			initializer_range
								_UpperCAmelCase      =			layer_norm_eps
								_UpperCAmelCase      =			scale_embedding
								_UpperCAmelCase      =			use_cache
								_UpperCAmelCase      =			layerdrop
								_UpperCAmelCase      =			activation_dropout
								super().__init__(pad_token_id=_SCREAMING_SNAKE_CASE						,		bos_token_id=_SCREAMING_SNAKE_CASE						,		eos_token_id=_SCREAMING_SNAKE_CASE						,		**_SCREAMING_SNAKE_CASE			)





import io
import json

import fsspec
import pytest

from datasets import Dataset, DatasetDict, Features, NamedSplit, Value
from datasets.io.json import JsonDatasetReader, JsonDatasetWriter

from ..utils import assert_arrow_memory_doesnt_increase, assert_arrow_memory_increases




def        _SCREAMING_SNAKE_CASE      (		snake_case			,     snake_case       )						->				int:
						assert isinstance(snake_case			,     snake_case       )
						assert dataset.num_rows == 4
						assert dataset.num_columns == 3
						assert dataset.column_names == ["col_1", "col_2", "col_3"]
						for feature, expected_dtype in expected_features.items():
												assert dataset.features[feature].dtype == expected_dtype




@pytest.mark.parametrize("""keep_in_memory"""			,     [False, True]       )
def        _SCREAMING_SNAKE_CASE      (		snake_case			,     snake_case			,     snake_case       )						->				Optional[int]:
						_UpperCAmelCase      =			tmp_path / """cache"""
						_UpperCAmelCase      =			{"""col_1""": """string""", """col_2""": """int64""", """col_3""": """float64"""}
						with assert_arrow_memory_increases() if keep_in_memory else assert_arrow_memory_doesnt_increase():
												_UpperCAmelCase      =			JsonDatasetReader(snake_case			,     cache_dir=snake_case			,     keep_in_memory=snake_case       ).read()
						_check_json_dataset(snake_case			,     snake_case       )




@pytest.mark.parametrize(
    """features"""			,     [
        None,
        {"""col_1""": """string""", """col_2""": """int64""", """col_3""": """float64"""},
        {"""col_1""": """string""", """col_2""": """string""", """col_3""": """string"""},
        {"""col_1""": """int32""", """col_2""": """int32""", """col_3""": """int32"""},
        {"""col_1""": """float32""", """col_2""": """float32""", """col_3""": """float32"""},
    ]			,     )
def        _SCREAMING_SNAKE_CASE      (		snake_case			,     snake_case			,     snake_case       )						->				Optional[Any]:
						_UpperCAmelCase      =			tmp_path / """cache"""
						_UpperCAmelCase      =			{"""col_1""": """string""", """col_2""": """int64""", """col_3""": """float64"""}
						_UpperCAmelCase      =			features.copy() if features else default_expected_features
						_UpperCAmelCase      =			(
						    Features({feature: Value(snake_case       ) for feature, dtype in features.items()}       ) if features is not None else None
						)
						_UpperCAmelCase      =			JsonDatasetReader(snake_case			,     features=snake_case			,     cache_dir=snake_case       ).read()
						_check_json_dataset(snake_case			,     snake_case       )




@pytest.mark.parametrize(
    """features"""			,     [
        None,
        {"""col_3""": """float64""", """col_1""": """string""", """col_2""": """int64"""},
    ]			,     )
def        _SCREAMING_SNAKE_CASE      (		snake_case			,     snake_case			,     snake_case       )						->				int:
						_UpperCAmelCase      =			tmp_path / """cache"""
						_UpperCAmelCase      =			{"""col_3""": """float64""", """col_1""": """string""", """col_2""": """int64"""}
						_UpperCAmelCase      =			features.copy() if features else default_expected_features
						_UpperCAmelCase      =			(
						    Features({feature: Value(snake_case       ) for feature, dtype in features.items()}       ) if features is not None else None
						)
						_UpperCAmelCase      =			JsonDatasetReader(snake_case			,     features=snake_case			,     cache_dir=snake_case       ).read()
						assert isinstance(snake_case			,     snake_case       )
						assert dataset.num_rows == 2
						assert dataset.num_columns == 3
						assert dataset.column_names == ["col_3", "col_1", "col_2"]
						for feature, expected_dtype in expected_features.items():
												assert dataset.features[feature].dtype == expected_dtype




def        _SCREAMING_SNAKE_CASE      (		snake_case			,     snake_case       )						->				Optional[int]:
						# jsonl_312_path features are {"col_3": "float64", "col_1": "string", "col_2": "int64"}
						_UpperCAmelCase      =			{"""col_2""": """int64""", """col_3""": """float64""", """col_1""": """string"""}
						_UpperCAmelCase      =			features.copy()
						_UpperCAmelCase      =			(
						    Features({feature: Value(snake_case       ) for feature, dtype in features.items()}       ) if features is not None else None
						)
						_UpperCAmelCase      =			tmp_path / """cache"""
						_UpperCAmelCase      =			JsonDatasetReader(snake_case			,     features=snake_case			,     cache_dir=snake_case       ).read()
						assert isinstance(snake_case			,     snake_case       )
						assert dataset.num_rows == 2
						assert dataset.num_columns == 3
						assert dataset.column_names == ["col_2", "col_3", "col_1"]
						for feature, expected_dtype in expected_features.items():
												assert dataset.features[feature].dtype == expected_dtype




@pytest.mark.parametrize("""split"""			,     [None, NamedSplit("""train"""       ), """train""", """test"""]       )
def        _SCREAMING_SNAKE_CASE      (		snake_case			,     snake_case			,     snake_case       )						->				List[Any]:
						_UpperCAmelCase      =			tmp_path / """cache"""
						_UpperCAmelCase      =			{"""col_1""": """string""", """col_2""": """int64""", """col_3""": """float64"""}
						_UpperCAmelCase      =			JsonDatasetReader(snake_case			,     cache_dir=snake_case			,     split=snake_case       ).read()
						_check_json_dataset(snake_case			,     snake_case       )
						assert dataset.split == split if split else "train"




@pytest.mark.parametrize("""path_type"""			,     [str, list]       )
def        _SCREAMING_SNAKE_CASE      (		snake_case			,     snake_case			,     snake_case       )						->				Any:
						if issubclass(snake_case			,     snake_case       ):
												_UpperCAmelCase      =			jsonl_path
						elif issubclass(snake_case			,     snake_case       ):
												_UpperCAmelCase      =			[jsonl_path]
						_UpperCAmelCase      =			tmp_path / """cache"""
						_UpperCAmelCase      =			{"""col_1""": """string""", """col_2""": """int64""", """col_3""": """float64"""}
						_UpperCAmelCase      =			JsonDatasetReader(snake_case			,     cache_dir=snake_case       ).read()
						_check_json_dataset(snake_case			,     snake_case       )




def        _SCREAMING_SNAKE_CASE      (		snake_case			,     snake_case			,     snake_case=("train",)       )						->				str:
						assert isinstance(snake_case			,     snake_case       )
						for split in splits:
												_UpperCAmelCase      =			dataset_dict[split]
												assert dataset.num_rows == 4
												assert dataset.num_columns == 3
												assert dataset.column_names == ["col_1", "col_2", "col_3"]
												for feature, expected_dtype in expected_features.items():
																		assert dataset.features[feature].dtype == expected_dtype




@pytest.mark.parametrize("""keep_in_memory"""			,     [False, True]       )
def        _SCREAMING_SNAKE_CASE      (		snake_case			,     snake_case			,     snake_case       )						->				str:
						_UpperCAmelCase      =			tmp_path / """cache"""
						_UpperCAmelCase      =			{"""col_1""": """string""", """col_2""": """int64""", """col_3""": """float64"""}
						with assert_arrow_memory_increases() if keep_in_memory else assert_arrow_memory_doesnt_increase():
												_UpperCAmelCase      =			JsonDatasetReader({"""train""": jsonl_path}			,     cache_dir=snake_case			,     keep_in_memory=snake_case       ).read()
						_check_json_datasetdict(snake_case			,     snake_case       )




@pytest.mark.parametrize(
    """features"""			,     [
        None,
        {"""col_1""": """string""", """col_2""": """int64""", """col_3""": """float64"""},
        {"""col_1""": """string""", """col_2""": """string""", """col_3""": """string"""},
        {"""col_1""": """int32""", """col_2""": """int32""", """col_3""": """int32"""},
        {"""col_1""": """float32""", """col_2""": """float32""", """col_3""": """float32"""},
    ]			,     )
def        _SCREAMING_SNAKE_CASE      (		snake_case			,     snake_case			,     snake_case       )						->				Tuple:
						_UpperCAmelCase      =			tmp_path / """cache"""
						_UpperCAmelCase      =			{"""col_1""": """string""", """col_2""": """int64""", """col_3""": """float64"""}
						_UpperCAmelCase      =			features.copy() if features else default_expected_features
						_UpperCAmelCase      =			(
						    Features({feature: Value(snake_case       ) for feature, dtype in features.items()}       ) if features is not None else None
						)
						_UpperCAmelCase      =			JsonDatasetReader({"""train""": jsonl_path}			,     features=snake_case			,     cache_dir=snake_case       ).read()
						_check_json_datasetdict(snake_case			,     snake_case       )




@pytest.mark.parametrize("""split"""			,     [None, NamedSplit("""train"""       ), """train""", """test"""]       )
def        _SCREAMING_SNAKE_CASE      (		snake_case			,     snake_case			,     snake_case       )						->				Optional[Any]:
						if split:
												_UpperCAmelCase      =			{split: jsonl_path}
						else:
												_UpperCAmelCase      =			"""train"""
												_UpperCAmelCase      =			{"""train""": jsonl_path, """test""": jsonl_path}
						_UpperCAmelCase      =			tmp_path / """cache"""
						_UpperCAmelCase      =			{"""col_1""": """string""", """col_2""": """int64""", """col_3""": """float64"""}
						_UpperCAmelCase      =			JsonDatasetReader(snake_case			,     cache_dir=snake_case       ).read()
						_check_json_datasetdict(snake_case			,     snake_case			,     splits=list(path.keys()       )       )
						assert all(dataset[split].split == split for split in path.keys()       )




def        _SCREAMING_SNAKE_CASE      (		snake_case       )						->				List[Any]:
						return json.load(snake_case       )




def        _SCREAMING_SNAKE_CASE      (		snake_case       )						->				List[Any]:
						return [json.loads(snake_case       ) for line in buffer]




class       _A				:






		@pytest.mark.parametrize("""lines, load_json_function"""						,		[(True, load_json_lines), (False, load_json)]			)
		def 				UpperCAmelCase (    self						,		_SCREAMING_SNAKE_CASE						,		_SCREAMING_SNAKE_CASE						,		_SCREAMING_SNAKE_CASE			):
								with io.BytesIO() as buffer:
														JsonDatasetWriter(_SCREAMING_SNAKE_CASE						,		_SCREAMING_SNAKE_CASE						,		lines=_SCREAMING_SNAKE_CASE			).write()
														buffer.seek(0			)
														_UpperCAmelCase      =			load_json_function(_SCREAMING_SNAKE_CASE			)
								assert isinstance(_SCREAMING_SNAKE_CASE						,		_SCREAMING_SNAKE_CASE			)
								assert isinstance(exported_content[0]						,		_SCREAMING_SNAKE_CASE			)
								assert len(_SCREAMING_SNAKE_CASE			) == 10






		@pytest.mark.parametrize(
		    """orient, container, keys, len_at"""						,		[
		        ("""records""", list, {"""tokens""", """labels""", """answers""", """id"""}, None),
		        ("""split""", dict, {"""columns""", """data"""}, """data"""),
		        ("""index""", dict, set("""0123456789"""			), None),
		        ("""columns""", dict, {"""tokens""", """labels""", """answers""", """id"""}, """tokens"""),
		        ("""values""", list, None, None),
		        ("""table""", dict, {"""schema""", """data"""}, """data"""),
		    ]						,		)
		def 				UpperCAmelCase (    self						,		_SCREAMING_SNAKE_CASE						,		_SCREAMING_SNAKE_CASE						,		_SCREAMING_SNAKE_CASE						,		_SCREAMING_SNAKE_CASE						,		_SCREAMING_SNAKE_CASE			):
								with io.BytesIO() as buffer:
														JsonDatasetWriter(_SCREAMING_SNAKE_CASE						,		_SCREAMING_SNAKE_CASE						,		lines=_SCREAMING_SNAKE_CASE						,		orient=_SCREAMING_SNAKE_CASE			).write()
														buffer.seek(0			)
														_UpperCAmelCase      =			load_json(_SCREAMING_SNAKE_CASE			)
								assert isinstance(_SCREAMING_SNAKE_CASE						,		_SCREAMING_SNAKE_CASE			)
								if keys:
														if container is dict:
																				assert exported_content.keys() == keys
														else:
																				assert exported_content[0].keys() == keys
								else:
														assert not hasattr(_SCREAMING_SNAKE_CASE						,		"""keys"""			) and not hasattr(exported_content[0]						,		"""keys"""			)
								if len_at:
														assert len(exported_content[len_at]			) == 10
								else:
														assert len(_SCREAMING_SNAKE_CASE			) == 10






		@pytest.mark.parametrize("""lines, load_json_function"""						,		[(True, load_json_lines), (False, load_json)]			)
		def 				UpperCAmelCase (    self						,		_SCREAMING_SNAKE_CASE						,		_SCREAMING_SNAKE_CASE						,		_SCREAMING_SNAKE_CASE			):
								with io.BytesIO() as buffer:
														JsonDatasetWriter(_SCREAMING_SNAKE_CASE						,		_SCREAMING_SNAKE_CASE						,		lines=_SCREAMING_SNAKE_CASE						,		num_proc=2			).write()
														buffer.seek(0			)
														_UpperCAmelCase      =			load_json_function(_SCREAMING_SNAKE_CASE			)
								assert isinstance(_SCREAMING_SNAKE_CASE						,		_SCREAMING_SNAKE_CASE			)
								assert isinstance(exported_content[0]						,		_SCREAMING_SNAKE_CASE			)
								assert len(_SCREAMING_SNAKE_CASE			) == 10






		@pytest.mark.parametrize(
		    """orient, container, keys, len_at"""						,		[
		        ("""records""", list, {"""tokens""", """labels""", """answers""", """id"""}, None),
		        ("""split""", dict, {"""columns""", """data"""}, """data"""),
		        ("""index""", dict, set("""0123456789"""			), None),
		        ("""columns""", dict, {"""tokens""", """labels""", """answers""", """id"""}, """tokens"""),
		        ("""values""", list, None, None),
		        ("""table""", dict, {"""schema""", """data"""}, """data"""),
		    ]						,		)
		def 				UpperCAmelCase (    self						,		_SCREAMING_SNAKE_CASE						,		_SCREAMING_SNAKE_CASE						,		_SCREAMING_SNAKE_CASE						,		_SCREAMING_SNAKE_CASE						,		_SCREAMING_SNAKE_CASE			):
								with io.BytesIO() as buffer:
														JsonDatasetWriter(_SCREAMING_SNAKE_CASE						,		_SCREAMING_SNAKE_CASE						,		lines=_SCREAMING_SNAKE_CASE						,		orient=_SCREAMING_SNAKE_CASE						,		num_proc=2			).write()
														buffer.seek(0			)
														_UpperCAmelCase      =			load_json(_SCREAMING_SNAKE_CASE			)
								assert isinstance(_SCREAMING_SNAKE_CASE						,		_SCREAMING_SNAKE_CASE			)
								if keys:
														if container is dict:
																				assert exported_content.keys() == keys
														else:
																				assert exported_content[0].keys() == keys
								else:
														assert not hasattr(_SCREAMING_SNAKE_CASE						,		"""keys"""			) and not hasattr(exported_content[0]						,		"""keys"""			)
								if len_at:
														assert len(exported_content[len_at]			) == 10
								else:
														assert len(_SCREAMING_SNAKE_CASE			) == 10






		def 				UpperCAmelCase (    self						,		_SCREAMING_SNAKE_CASE			):
								with pytest.raises(_SCREAMING_SNAKE_CASE			):
														with io.BytesIO() as buffer:
																				JsonDatasetWriter(_SCREAMING_SNAKE_CASE						,		_SCREAMING_SNAKE_CASE						,		num_proc=0			)






		@pytest.mark.parametrize("""compression, extension"""						,		[("""gzip""", """gz"""), ("""bz2""", """bz2"""), ("""xz""", """xz""")]			)
		def 				UpperCAmelCase (    self						,		_SCREAMING_SNAKE_CASE						,		_SCREAMING_SNAKE_CASE						,		_SCREAMING_SNAKE_CASE						,		_SCREAMING_SNAKE_CASE						,		_SCREAMING_SNAKE_CASE			):
								_UpperCAmelCase      =			tmp_path_factory.mktemp("""data"""			) / F"test.json.{extension}"
								_UpperCAmelCase      =			str(shared_datadir / F"test_file.json.{extension}"			)
								JsonDatasetWriter(_SCREAMING_SNAKE_CASE						,		_SCREAMING_SNAKE_CASE						,		compression=_SCREAMING_SNAKE_CASE			).write()

								with fsspec.open(_SCREAMING_SNAKE_CASE						,		"""rb"""						,		compression="""infer"""			) as f:
														_UpperCAmelCase      =			f.read()
								with fsspec.open(_SCREAMING_SNAKE_CASE						,		"""rb"""						,		compression="""infer"""			) as f:
														_UpperCAmelCase      =			f.read()
								assert exported_content == original_content