






import tempfile
import unittest

from transformers import AutoModelForSeqaSeqLM, AutoTokenizer
from transformers.testing_utils import (
    is_torch_available,
    require_optimum,
    require_torch,
    slow,
)


if is_torch_available():
     import torch






@require_torch
@require_optimum
@slow
class 		lowercase_					(	unittest.TestCase   ):






      '''simple docstring'''




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




       """simple docstring"""


       a		  =      '''hf-internal-testing/tiny-random-t5'''
       a		  =      AutoTokenizer.from_pretrained(__UpperCAmelCase  )
       a		  =      AutoModelForSeqaSeqLM.from_pretrained(__UpperCAmelCase  )

       a		  =      tokenizer('''This is me''' ,					return_tensors='''pt'''  )

       a		  =      model.to_bettertransformer()

       self.assertTrue(any('''BetterTransformer''' in mod.__class__.__name__ for _, mod in model.named_modules()  )  )

       a		  =      model.generate(**__UpperCAmelCase  )

       a		  =      model.reverse_bettertransformer()

       self.assertFalse(any('''BetterTransformer''' in mod.__class__.__name__ for _, mod in model.named_modules()  )  )

       with tempfile.TemporaryDirectory() as tmpdirname:
        model.save_pretrained(__UpperCAmelCase  )

        a		  =      AutoModelForSeqaSeqLM.from_pretrained(__UpperCAmelCase  )

        self.assertFalse(
            any('''BetterTransformer''' in mod.__class__.__name__ for _, mod in model_reloaded.named_modules()  )  )

        a		  =      model_reloaded.generate(**__UpperCAmelCase  )
        self.assertTrue(torch.allclose(__UpperCAmelCase ,					__UpperCAmelCase  )  )







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




       """simple docstring"""


       a		  =      '''hf-internal-testing/tiny-random-t5'''
       a		  =      AutoModelForSeqaSeqLM.from_pretrained(__UpperCAmelCase  )

       a		  =      model.to_bettertransformer()

       with tempfile.TemporaryDirectory() as tmpdirname:
        with self.assertRaises(__UpperCAmelCase  ):
         model.save_pretrained(__UpperCAmelCase  )

        a		  =      model.reverse_bettertransformer()
        model.save_pretrained(__UpperCAmelCase  )




"""simple docstring"""





import pytest

from datasets.utils.sharding import _distribute_shards, _number_of_shards_in_gen_kwargs, _split_gen_kwargs



@pytest.mark.parametrize(
    """kwargs, expected"""  ,				[
        ({"""num_shards""": 0, """max_num_jobs""": 1}, []),
        ({"""num_shards""": 10, """max_num_jobs""": 1}, [range(10				)]),
        ({"""num_shards""": 10, """max_num_jobs""": 10}, [range(UpperCamelCase_  ,				i + 1				) for i in range(10				)]),
        ({"""num_shards""": 1, """max_num_jobs""": 10}, [range(1				)]),
        ({"""num_shards""": 10, """max_num_jobs""": 3}, [range(0  ,				4				), range(4  ,				7				), range(7  ,				10				)]),
        ({"""num_shards""": 3, """max_num_jobs""": 10}, [range(0  ,				1				), range(1  ,				2				), range(2  ,				3				)]),
    ]  ,				)
def 						_lowerCAmelCase				(				UpperCamelCase_  ,				UpperCamelCase_				):
		__SCREAMING_SNAKE_CASE            = _distribute_shards(**UpperCamelCase_				)
		assert out == expected



@pytest.mark.parametrize(
    """gen_kwargs, max_num_jobs, expected"""  ,				[
        ({"""foo""": 0}, 10, [{"""foo""": 0}]),
        ({"""shards""": [0, 1, 2, 3]}, 1, [{"""shards""": [0, 1, 2, 3]}]),
        ({"""shards""": [0, 1, 2, 3]}, 4, [{"""shards""": [0]}, {"""shards""": [1]}, {"""shards""": [2]}, {"""shards""": [3]}]),
        ({"""shards""": [0, 1]}, 4, [{"""shards""": [0]}, {"""shards""": [1]}]),
        ({"""shards""": [0, 1, 2, 3]}, 2, [{"""shards""": [0, 1]}, {"""shards""": [2, 3]}]),
    ]  ,				)
def 						_lowerCAmelCase				(				UpperCamelCase_  ,				UpperCamelCase_  ,				UpperCamelCase_				):
		__SCREAMING_SNAKE_CASE            = _split_gen_kwargs(UpperCamelCase_  ,				UpperCamelCase_				)
		assert out == expected



@pytest.mark.parametrize(
    """gen_kwargs, expected"""  ,				[
        ({"""foo""": 0}, 1),
        ({"""shards""": [0]}, 1),
        ({"""shards""": [0, 1, 2, 3]}, 4),
        ({"""shards""": [0, 1, 2, 3], """foo""": 0}, 4),
        ({"""shards""": [0, 1, 2, 3], """other""": (0, 1)}, 4),
        ({"""shards""": [0, 1, 2, 3], """shards2""": [0, 1]}, RuntimeError),
    ]  ,				)
def 						_lowerCAmelCase				(				UpperCamelCase_  ,				UpperCamelCase_				):
		if expected is RuntimeError:
				with pytest.raises(UpperCamelCase_				):
						_number_of_shards_in_gen_kwargs(UpperCamelCase_				)
		else:
				__SCREAMING_SNAKE_CASE            = _number_of_shards_in_gen_kwargs(UpperCamelCase_				)
				assert out == expected




