

from typing import Optional

import pyspark

from .. import Features, NamedSplit
from ..download import DownloadMode
from ..packaged_modules.spark.spark import Spark
from .abc import AbstractDatasetReader



class        lowercase		(			_a   ):



 '''simple docstring'''


 def __init__(self			,			__a			,			__a = None			,			__a = None			,			__a = True			,			__a = None			,			__a = False			,			__a = None			,			__a = True			,			__a = "arrow"			,			**__a			,			)					->   Optional[int]:






  """simple docstring"""





  super().__init__(
      split=lowerCAmelCase_			,			features=lowerCAmelCase_			,			cache_dir=lowerCAmelCase_			,			keep_in_memory=lowerCAmelCase_			,			streaming=lowerCAmelCase_			,			**lowerCAmelCase_			,			)
  UpperCAmelCase__     							=							load_from_cache_file
  UpperCAmelCase__     							=							file_format
  UpperCAmelCase__     							=							Spark(
      df=lowerCAmelCase_			,			features=lowerCAmelCase_			,			cache_dir=lowerCAmelCase_			,			working_dir=lowerCAmelCase_			,			**lowerCAmelCase_			,			)




 def     UpperCamelCase__				(self					)					->   List[Any]:






  """simple docstring"""





  if self.streaming:
   return self.builder.as_streaming_dataset(split=self.split					)
  UpperCAmelCase__     							=							None if self._load_from_cache_file else DownloadMode.FORCE_REDOWNLOAD
  self.builder.download_and_prepare(
      download_mode=lowerCAmelCase_			,			file_format=self._file_format			,			)
  return self.builder.as_dataset(split=self.split					)









'''simple docstring'''


import unittest

from transformers import is_flax_available
from transformers.testing_utils import require_flax, require_sentencepiece, require_tokenizers, require_torch, slow


if is_flax_available():
				import optax
				from flax.training.common_utils import onehot

				from transformers import AutoTokenizer, FlaxMTaForConditionalGeneration
				from transformers.models.ta.modeling_flax_ta import shift_tokens_right

@require_torch
@require_sentencepiece
@require_tokenizers
@require_flax
class      A       (						unittest.TestCase       ):







							@slow
							def   __lowerCAmelCase     (    self			:    List[Any]   )     ->				Union[str, Any]:


														"""simple docstring"""


														_a      	=							FlaxMTaForConditionalGeneration.from_pretrained('''google/mt5-small'''   )
														_a      	=							AutoTokenizer.from_pretrained('''google/mt5-small'''   )

														_a      	=							tokenizer('''Hello there'''				,     return_tensors='''np'''   ).input_ids
														_a      	=							tokenizer('''Hi I am'''				,     return_tensors='''np'''   ).input_ids

														_a      	=							shift_tokens_right(lowerCAmelCase_				,     model.config.pad_token_id				,     model.config.decoder_start_token_id   )

														_a      	=							model(lowerCAmelCase_				,     decoder_input_ids=lowerCAmelCase_   ).logits
														_a      	=							optax.softmax_cross_entropy(lowerCAmelCase_				,     onehot(lowerCAmelCase_				,     logits.shape[-1]   )   ).mean()

														_a      	=							-(labels.shape[-1] * loss.item())

														_a      	=							-8_4.9_1_2_7
														self.assertTrue(abs(mtf_score - EXPECTED_SCORE   ) < 1e-4   )

