



import textwrap

import pyarrow as pa
import pytest

from datasets import Features, Image
from datasets.packaged_modules.text.text import Text

from ..utils import require_pil





@pytest.fixture
def   __lowerCamelCase				(					__magic_name__		:     Union[str, Any]  ):
							a__:				List[Any] 							=tmp_path / 'text.txt'
							a__:				Optional[Any] 							=textwrap.dedent(
							    "\\n        Lorem ipsum dolor sit amet, consectetur adipiscing elit, sed do eiusmod tempor incididunt ut labore et dolore magna aliqua.\n        Ut enim ad minim veniam, quis nostrud exercitation ullamco laboris nisi ut aliquip ex ea commodo consequat.\n        Duis aute irure dolor in reprehenderit in voluptate velit esse cillum dolore eu fugiat nulla pariatur.\n        Excepteur sint occaecat cupidatat non proident, sunt in culpa qui officia deserunt mollit anim id est laborum.\n\n        Second paragraph:\n        Lorem ipsum dolor sit amet, consectetur adipiscing elit, sed do eiusmod tempor incididunt ut labore et dolore magna aliqua.\n        Ut enim ad minim veniam, quis nostrud exercitation ullamco laboris nisi ut aliquip ex ea commodo consequat.\n        Duis aute irure dolor in reprehenderit in voluptate velit esse cillum dolore eu fugiat nulla pariatur.\n        Excepteur sint occaecat cupidatat non proident, sunt in culpa qui officia deserunt mollit anim id est laborum.\n        "  )
							with open(A__   ,       "w"   ,       encoding="utf-8"  ) as f:
														f.write(A__  )
							return str(A__  )





@pytest.fixture
def   __lowerCamelCase				(					__magic_name__		:     Tuple   ,       __magic_name__		:     Optional[Any]  ):
							a__:				Dict 							=tmp_path / 'text_with_image.txt'
							with open(A__   ,       "w"   ,       encoding="utf-8"  ) as f:
														f.write(A__  )
							return str(A__  )





@pytest.mark.parametrize("keep_linebreaks"   ,       [True, False]  )
def   __lowerCamelCase				(					__magic_name__		:     str   ,       __magic_name__		:     int  ):
							with open(A__   ,       encoding="utf-8"  ) as f:
														a__:				Optional[Any] 							=f.read().splitlines(keepends=A__  )
							a__:				Dict 							=Text(keep_linebreaks=A__   ,       encoding="utf-8"  )
							a__:				Optional[Any] 							=text._generate_tables([[text_file]]  )
							a__:				Any 							=pa.concat_tables([table for _, table in generator]  ).to_pydict()['text']
							assert generated_content == expected_content





@require_pil
def   __lowerCamelCase				(					__magic_name__		:     Dict  ):
							with open(A__   ,       encoding="utf-8"  ) as f:
														a__:				int 							=f.read().splitlines()[0]
							a__:				Tuple 							=Text(encoding="utf-8"   ,       features=Features({"image": Image()}  )  )
							a__:				List[Any] 							=text._generate_tables([[text_file_with_image]]  )
							a__:				Optional[Any] 							=pa.concat_tables([table for _, table in generator]  )
							assert pa_table.schema.field("image"  ).type == Image()()
							a__:				Optional[Any] 							=pa_table.to_pydict()['image']
							assert generated_content == [{"path": image_file, "bytes": None}]







@pytest.mark.parametrize("sample_by"   ,       ["line", "paragraph", "document"]  )
def   __lowerCamelCase				(					__magic_name__		:     List[str]   ,       __magic_name__		:     Optional[int]  ):
							with open(A__   ,       encoding="utf-8"  ) as f:
														a__:				str 							=f.read()
							if sample_by == "line":
														a__:				Optional[int] 							=expected_content.splitlines()
							elif sample_by == "paragraph":
														a__:				List[Any] 							=expected_content.split("\n\n"  )
							elif sample_by == "document":
														a__:				Optional[Any] 							=[expected_content]
							a__:				Optional[Any] 							=Text(sample_by=A__   ,       encoding="utf-8"   ,       chunksize=100  )
							a__:				Dict 							=text._generate_tables([[text_file]]  )
							a__:				str 							=pa.concat_tables([table for _, table in generator]  ).to_pydict()['text']
							assert generated_content == expected_content









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


lowerCAmelCase__       :	Any     				=logging.get_logger(__name__)

lowerCAmelCase__       :	Union[str, Any]     				={
    'google/reformer-crime-and-punishment': (
        'https://huggingface.co/google/reformer-crime-and-punishment/resolve/main/config.json'
    ),
    'google/reformer-enwik8': 'https://huggingface.co/google/reformer-enwik8/resolve/main/config.json',
}







class      __lowercase  (__SCREAMING_SNAKE_CASE   ):





							"""simple docstring"""







							_UpperCAmelCase     =		"""reformer"""
							_UpperCAmelCase     =		["""past_buckets_states"""]
							_UpperCAmelCase     =		{}






							def __init__(	self       ,		lowerCAmelCase__=6_4       ,		lowerCAmelCase__=["local", "lsh", "local", "lsh", "local", "lsh"]       ,		lowerCAmelCase__=1.0       ,		lowerCAmelCase__=True       ,		lowerCAmelCase__=[6_4, 6_4]       ,		lowerCAmelCase__=[6_4, 1_9_2]       ,		lowerCAmelCase__=0       ,		lowerCAmelCase__=2       ,		lowerCAmelCase__=5_1_2       ,		lowerCAmelCase__=None       ,		lowerCAmelCase__="relu"       ,		lowerCAmelCase__=0.05       ,		lowerCAmelCase__=2_5_6       ,		lowerCAmelCase__=0.02       ,		lowerCAmelCase__=False       ,		lowerCAmelCase__=1E-12       ,		lowerCAmelCase__=1       ,		lowerCAmelCase__=0       ,		lowerCAmelCase__=0.05       ,		lowerCAmelCase__=6_4       ,		lowerCAmelCase__=6_4       ,		lowerCAmelCase__=0.0       ,		lowerCAmelCase__=1       ,		lowerCAmelCase__=0       ,		lowerCAmelCase__=4_0_9_6       ,		lowerCAmelCase__=1_2       ,		lowerCAmelCase__=None       ,		lowerCAmelCase__=1       ,		lowerCAmelCase__=0       ,		lowerCAmelCase__=3_2_0       ,		lowerCAmelCase__=False       ,		lowerCAmelCase__=True       ,		lowerCAmelCase__=None       ,		**lowerCAmelCase__       ,		):





										"""simple docstring"""




										SCREAMING_SNAKE_CASE_						:			str       						= hash_seed
										SCREAMING_SNAKE_CASE_						:			Union[str, Any]       						= vocab_size
										SCREAMING_SNAKE_CASE_						:			Any       						= attention_head_size
										SCREAMING_SNAKE_CASE_						:			List[Any]       						= hidden_size
										SCREAMING_SNAKE_CASE_						:			Optional[Any]       						= num_attention_heads
										SCREAMING_SNAKE_CASE_						:			Any       						= num_hashes
										SCREAMING_SNAKE_CASE_						:			int       						= len(lowerCAmelCase__    )
										SCREAMING_SNAKE_CASE_						:			str       						= tuple(lowerCAmelCase__    ) if isinstance(lowerCAmelCase__       ,		lowerCAmelCase__    ) else num_buckets
										SCREAMING_SNAKE_CASE_						:			int       						= lsh_attn_chunk_length
										SCREAMING_SNAKE_CASE_						:			List[str]       						= local_attn_chunk_length
										SCREAMING_SNAKE_CASE_						:			Tuple       						= lsh_num_chunks_after
										SCREAMING_SNAKE_CASE_						:			str       						= lsh_num_chunks_before
										SCREAMING_SNAKE_CASE_						:			List[Any]       						= local_num_chunks_after
										SCREAMING_SNAKE_CASE_						:			Any       						= local_num_chunks_before
										SCREAMING_SNAKE_CASE_						:			Any       						= hidden_act
										SCREAMING_SNAKE_CASE_						:			Dict       						= feed_forward_size
										SCREAMING_SNAKE_CASE_						:			Optional[int]       						= hidden_dropout_prob
										SCREAMING_SNAKE_CASE_						:			Tuple       						= lsh_attention_probs_dropout_prob
										SCREAMING_SNAKE_CASE_						:			Any       						= local_attention_probs_dropout_prob
										SCREAMING_SNAKE_CASE_						:			str       						= max_position_embeddings
										SCREAMING_SNAKE_CASE_						:			Optional[int]       						= initializer_range
										SCREAMING_SNAKE_CASE_						:			Optional[Any]       						= layer_norm_eps
										SCREAMING_SNAKE_CASE_						:			List[str]       						= axial_pos_embds
										SCREAMING_SNAKE_CASE_						:			List[str]       						= tuple(lowerCAmelCase__    )
										SCREAMING_SNAKE_CASE_						:			Tuple       						= tuple(lowerCAmelCase__    )
										SCREAMING_SNAKE_CASE_						:			Dict       						= axial_norm_std
										SCREAMING_SNAKE_CASE_						:			Any       						= chunk_size_lm_head
										SCREAMING_SNAKE_CASE_						:			int       						= attn_layers
										SCREAMING_SNAKE_CASE_						:			Union[str, Any]       						= use_cache
										SCREAMING_SNAKE_CASE_						:			Tuple       						= classifier_dropout
										super().__init__(
										    pad_token_id=lowerCAmelCase__       ,		eos_token_id=lowerCAmelCase__       ,		is_decoder=lowerCAmelCase__       ,		tie_word_embeddings=lowerCAmelCase__       ,		**lowerCAmelCase__       ,		)





