




'''simple docstring'''







import inspect

from diffusers.utils import is_flax_available
from diffusers.utils.testing_utils import require_flax


if is_flax_available():
						import jax





@require_flax
class   lowerCamelCase_							:




					'''simple docstring'''






					def        __SCREAMING_SNAKE_CASE			(					self				):
							_snake_case ,					_snake_case			 = self.prepare_init_args_and_inputs_for_common()

							_snake_case			 = self.model_class(**_lowerCAmelCase				)
							_snake_case			 = model.init(inputs_dict["prng_key"],						inputs_dict["sample"]				)
							jax.lax.stop_gradient(_lowerCAmelCase				)

							_snake_case			 = model.apply(_lowerCAmelCase,						inputs_dict["sample"]				)

							if isinstance(_lowerCAmelCase,						_lowerCAmelCase				):
									_snake_case			 = output.sample

							self.assertIsNotNone(_lowerCAmelCase				)
							_snake_case			 = inputs_dict["sample"].shape
							self.assertEqual(output.shape,						_lowerCAmelCase,						"Input and output shapes do not match"				)






					def        __SCREAMING_SNAKE_CASE			(					self				):
							_snake_case ,					_snake_case			 = self.prepare_init_args_and_inputs_for_common()

							_snake_case			 = 16
							_snake_case			 = (16, 32)

							_snake_case			 = self.model_class(**_lowerCAmelCase				)
							_snake_case			 = model.init(inputs_dict["prng_key"],						inputs_dict["sample"]				)
							jax.lax.stop_gradient(_lowerCAmelCase				)

							_snake_case			 = model.apply(_lowerCAmelCase,						inputs_dict["sample"]				)

							if isinstance(_lowerCAmelCase,						_lowerCAmelCase				):
									_snake_case			 = output.sample

							self.assertIsNotNone(_lowerCAmelCase				)
							_snake_case			 = inputs_dict["sample"].shape
							self.assertEqual(output.shape,						_lowerCAmelCase,						"Input and output shapes do not match"				)






					def        __SCREAMING_SNAKE_CASE			(					self				):
							_snake_case			 = "kwargs" in inspect.signature(self.model_class.__init__				).parameters
							_snake_case			 = len(self.model_class._deprecated_kwargs				) > 0

							if has_kwarg_in_model_class and not has_deprecated_kwarg:
									raise ValueError(
									    f'''{self.model_class} has `**kwargs` in its __init__ method but has not defined any deprecated kwargs'''
									    " under the `_deprecated_kwargs` class attribute. Make sure to either remove `**kwargs` if there are"
									    " no deprecated arguments or add the deprecated argument with `_deprecated_kwargs ="
									    " [<deprecated_argument>]`"				)

							if not has_kwarg_in_model_class and has_deprecated_kwarg:
									raise ValueError(
									    f'''{self.model_class} doesn\'t have `**kwargs` in its __init__ method but has defined deprecated kwargs'''
									    " under the `_deprecated_kwargs` class attribute. Make sure to either add the `**kwargs` argument to"
									    f''' {self.model_class}.__init__ if there are deprecated arguments or remove the deprecated argument'''
									    " from `_deprecated_kwargs = [<deprecated_argument>]`"				)











'''simple docstring'''







import unittest
import warnings
from dataclasses import dataclass

from transformers.convert_slow_tokenizer import SpmConverter
from transformers.testing_utils import get_tests_dir





@dataclass
class   lowerCamelCase_							:




					'''simple docstring'''






					lowercase__					=				42





class   lowerCamelCase_							( unittest.TestCase							):




					'''simple docstring'''






					def        __SCREAMING_SNAKE_CASE			(					self				):
							_snake_case			 = get_tests_dir("fixtures/test_sentencepiece.model"				)
							_snake_case			 = get_tests_dir("fixtures/test_sentencepiece_with_bytefallback.model"				)

							_snake_case			 = FakeOriginalTokenizer(vocab_file=__UpperCamelCase				)

							with warnings.catch_warnings(record=__UpperCamelCase				) as w:
									_snake_case			 = SpmConverter(__UpperCamelCase				)
							self.assertEqual(len(__UpperCamelCase				),						0				)

							_snake_case			 = FakeOriginalTokenizer(vocab_file=__UpperCamelCase				)

							with warnings.catch_warnings(record=__UpperCamelCase				) as w:
									_snake_case			 = SpmConverter(__UpperCamelCase				)
							self.assertEqual(len(__UpperCamelCase				),						1				)

							self.assertIn(
							    "The sentencepiece tokenizer that you are converting to a fast tokenizer uses the byte fallback option"
							    " which is not implemented in the fast tokenizers.",						str(w[0].message				),						)





