


'''simple docstring'''
from typing import TYPE_CHECKING

from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available, is_vision_available


__SCREAMING_SNAKE_CASE					:				Optional[Any]									=		{'''configuration_yolos''': ['''YOLOS_PRETRAINED_CONFIG_ARCHIVE_MAP''', '''YolosConfig''', '''YolosOnnxConfig''']}

try:
							if not is_vision_available():
														raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
							pass
else:
							__SCREAMING_SNAKE_CASE					:				Any									=		['''YolosFeatureExtractor''']
							__SCREAMING_SNAKE_CASE					:				Tuple									=		['''YolosImageProcessor''']

try:
							if not is_torch_available():
														raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
							pass
else:
							__SCREAMING_SNAKE_CASE					:				Optional[int]									=		[
							    '''YOLOS_PRETRAINED_MODEL_ARCHIVE_LIST''',
							    '''YolosForObjectDetection''',
							    '''YolosModel''',
							    '''YolosPreTrainedModel''',
							]


if TYPE_CHECKING:
							from .configuration_yolos import YOLOS_PRETRAINED_CONFIG_ARCHIVE_MAP, YolosConfig, YolosOnnxConfig

							try:
														if not is_vision_available():
																					raise OptionalDependencyNotAvailable()
							except OptionalDependencyNotAvailable:
														pass
							else:
														from .feature_extraction_yolos import YolosFeatureExtractor
														from .image_processing_yolos import YolosImageProcessor

							try:
														if not is_torch_available():
																					raise OptionalDependencyNotAvailable()
							except OptionalDependencyNotAvailable:
														pass
							else:
														from .modeling_yolos import (
														    YOLOS_PRETRAINED_MODEL_ARCHIVE_LIST,
														    YolosForObjectDetection,
														    YolosModel,
														    YolosPreTrainedModel,
														)


else:
							import sys

							__SCREAMING_SNAKE_CASE					:				Dict									=		_LazyModule(__name__, globals()['''__file__'''], _import_structure, module_spec=__spec__)









'''simple docstring'''
import unittest

from transformers import AutoConfig, AutoTokenizer, BertConfig, TensorType, is_flax_available
from transformers.testing_utils import DUMMY_UNKNOWN_IDENTIFIER, require_flax, slow


if is_flax_available():
							import jax

							from transformers.models.auto.modeling_flax_auto import FlaxAutoModel
							from transformers.models.bert.modeling_flax_bert import FlaxBertModel
							from transformers.models.roberta.modeling_flax_roberta import FlaxRobertaModel






@require_flax
class 					__lowerCAmelCase   (   unittest.TestCase						):

						"""simple docstring"""






						@slow
						def 				_UpperCAmelCase       (  self							:      Dict	):
													for model_name in ["bert-base-cased", "bert-large-uncased"]:
																				with self.subTest(lowerCAmelCase	):
																											A_			    =		AutoConfig.from_pretrained(lowerCAmelCase	)
																											self.assertIsNotNone(lowerCAmelCase	)
																											self.assertIsInstance(lowerCAmelCase ,  lowerCAmelCase	)

																											A_			    =		FlaxAutoModel.from_pretrained(lowerCAmelCase	)
																											self.assertIsNotNone(lowerCAmelCase	)
																											self.assertIsInstance(lowerCAmelCase ,  lowerCAmelCase	)






						@slow
						def 				_UpperCAmelCase       (  self							:      Union[str, Any]	):
													for model_name in ["roberta-base", "roberta-large"]:
																				with self.subTest(lowerCAmelCase	):
																											A_			    =		AutoConfig.from_pretrained(lowerCAmelCase	)
																											self.assertIsNotNone(lowerCAmelCase	)
																											self.assertIsInstance(lowerCAmelCase ,  lowerCAmelCase	)

																											A_			    =		FlaxAutoModel.from_pretrained(lowerCAmelCase	)
																											self.assertIsNotNone(lowerCAmelCase	)
																											self.assertIsInstance(lowerCAmelCase ,  lowerCAmelCase	)






						@slow
						def 				_UpperCAmelCase       (  self							:      List[Any]	):
													for model_name in ["bert-base-cased", "bert-large-uncased"]:
																				A_			    =		AutoTokenizer.from_pretrained(lowerCAmelCase	)
																				A_			    =		FlaxBertModel.from_pretrained(lowerCAmelCase	)
																				A_			    =		tokenizer("Do you support jax jitted function?" ,  return_tensors=TensorType.JAX	)

																				@jax.jit
																				def eval(**lowerCAmelCase							:      Tuple	):
																											return model(**lowerCAmelCase	)

																				eval(**lowerCAmelCase	).block_until_ready()






						@slow
						def 				_UpperCAmelCase       (  self							:      str	):
													for model_name in ["roberta-base", "roberta-large"]:
																				A_			    =		AutoTokenizer.from_pretrained(lowerCAmelCase	)
																				A_			    =		FlaxRobertaModel.from_pretrained(lowerCAmelCase	)
																				A_			    =		tokenizer("Do you support jax jitted function?" ,  return_tensors=TensorType.JAX	)

																				@jax.jit
																				def eval(**lowerCAmelCase							:      Any	):
																											return model(**lowerCAmelCase	)

																				eval(**lowerCAmelCase	).block_until_ready()






						def 				_UpperCAmelCase       (  self							:      List[Any]	):
													with self.assertRaisesRegex(
													    lowerCAmelCase ,  "bert-base is not a local folder and is not a valid model identifier"	):
																				A_			    =		FlaxAutoModel.from_pretrained("bert-base"	)






						def 				_UpperCAmelCase       (  self							:      Any	):
													with self.assertRaisesRegex(
													    lowerCAmelCase ,  r"aaaaaa is not a valid git identifier \(branch name, tag name or commit id\)"	):
																				A_			    =		FlaxAutoModel.from_pretrained(lowerCAmelCase ,  revision="aaaaaa"	)






						def 				_UpperCAmelCase       (  self							:      Dict	):
													with self.assertRaisesRegex(
													    lowerCAmelCase ,  "hf-internal-testing/config-no-model does not appear to have a file named flax_model.msgpack" ,  ):
																				A_			    =		FlaxAutoModel.from_pretrained("hf-internal-testing/config-no-model"	)






						def 				_UpperCAmelCase       (  self							:      Any	):
													with self.assertRaisesRegex(lowerCAmelCase ,  "Use `from_pt=True` to load this model"	):
																				A_			    =		FlaxAutoModel.from_pretrained("hf-internal-testing/tiny-bert-pt-only"	)





