

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 SCREAMING_SNAKE_CASE  (		unittest.TestCase							):






			"""simple docstring"""




			@slow
			def 			__lowerCAmelCase (    self							):

				"""simple docstring"""


				for model_name in ["bert-base-cased", "bert-large-uncased"]:
					with self.subTest(__UpperCamelCase							):
						snake_case_      		= AutoConfig.from_pretrained(__UpperCamelCase							)
						self.assertIsNotNone(__UpperCamelCase							)
						self.assertIsInstance(__UpperCamelCase ,				__UpperCamelCase							)

						snake_case_      		= FlaxAutoModel.from_pretrained(__UpperCamelCase							)
						self.assertIsNotNone(__UpperCamelCase							)
						self.assertIsInstance(__UpperCamelCase ,				__UpperCamelCase							)


			@slow
			def 			__lowerCAmelCase (    self							):

				"""simple docstring"""


				for model_name in ["roberta-base", "roberta-large"]:
					with self.subTest(__UpperCamelCase							):
						snake_case_      		= AutoConfig.from_pretrained(__UpperCamelCase							)
						self.assertIsNotNone(__UpperCamelCase							)
						self.assertIsInstance(__UpperCamelCase ,				__UpperCamelCase							)

						snake_case_      		= FlaxAutoModel.from_pretrained(__UpperCamelCase							)
						self.assertIsNotNone(__UpperCamelCase							)
						self.assertIsInstance(__UpperCamelCase ,				__UpperCamelCase							)


			@slow
			def 			__lowerCAmelCase (    self							):

				"""simple docstring"""


				for model_name in ["bert-base-cased", "bert-large-uncased"]:
					snake_case_      		= AutoTokenizer.from_pretrained(__UpperCamelCase							)
					snake_case_      		= FlaxBertModel.from_pretrained(__UpperCamelCase							)
					snake_case_      		= tokenizer('Do you support jax jitted function?' ,				return_tensors=TensorType.JAX							)

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

					eval(**__UpperCamelCase							).block_until_ready()


			@slow
			def 			__lowerCAmelCase (    self							):

				"""simple docstring"""


				for model_name in ["roberta-base", "roberta-large"]:
					snake_case_      		= AutoTokenizer.from_pretrained(__UpperCamelCase							)
					snake_case_      		= FlaxRobertaModel.from_pretrained(__UpperCamelCase							)
					snake_case_      		= tokenizer('Do you support jax jitted function?' ,				return_tensors=TensorType.JAX							)

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

					eval(**__UpperCamelCase							).block_until_ready()


			def 			__lowerCAmelCase (    self							):

				"""simple docstring"""


				with self.assertRaisesRegex(
				    __UpperCamelCase ,				'bert-base is not a local folder and is not a valid model identifier'							):
					snake_case_      		= FlaxAutoModel.from_pretrained('bert-base'							)


			def 			__lowerCAmelCase (    self							):

				"""simple docstring"""


				with self.assertRaisesRegex(
				    __UpperCamelCase ,				r'aaaaaa is not a valid git identifier \(branch name, tag name or commit id\)'							):
					snake_case_      		= FlaxAutoModel.from_pretrained(__UpperCamelCase ,				revision='aaaaaa'							)


			def 			__lowerCAmelCase (    self							):

				"""simple docstring"""


				with self.assertRaisesRegex(
				    __UpperCamelCase ,				'hf-internal-testing/config-no-model does not appear to have a file named flax_model.msgpack' ,				):
					snake_case_      		= FlaxAutoModel.from_pretrained('hf-internal-testing/config-no-model'							)







			def 			__lowerCAmelCase (    self							):

				"""simple docstring"""


				with self.assertRaisesRegex(__UpperCamelCase ,				'Use `from_pt=True` to load this model'							):
					snake_case_      		= FlaxAutoModel.from_pretrained('hf-internal-testing/tiny-bert-pt-only'							)



from typing import TYPE_CHECKING

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


A											=     {
    'configuration_audio_spectrogram_transformer': [
        'AUDIO_SPECTROGRAM_TRANSFORMER_PRETRAINED_CONFIG_ARCHIVE_MAP',
        'ASTConfig',
    ]
}

try:
		if not is_torch_available():
				raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
		pass
else:
		A											=     [
		    'AUDIO_SPECTROGRAM_TRANSFORMER_PRETRAINED_MODEL_ARCHIVE_LIST',
		    'ASTForAudioClassification',
		    'ASTModel',
		    'ASTPreTrainedModel',
		]

try:
		if not is_speech_available():
				raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
		pass
else:
		A											=     ['ASTFeatureExtractor']

if TYPE_CHECKING:
		from .configuration_audio_spectrogram_transformer import (
		    AUDIO_SPECTROGRAM_TRANSFORMER_PRETRAINED_CONFIG_ARCHIVE_MAP,
		    ASTConfig,
		)

		try:
				if not is_torch_available():
						raise OptionalDependencyNotAvailable()
		except OptionalDependencyNotAvailable:
				pass
		else:
				from .modeling_audio_spectrogram_transformer import (
				    AUDIO_SPECTROGRAM_TRANSFORMER_PRETRAINED_MODEL_ARCHIVE_LIST,
				    ASTForAudioClassification,
				    ASTModel,
				    ASTPreTrainedModel,
				)

		try:
				if not is_speech_available():
						raise OptionalDependencyNotAvailable()
		except OptionalDependencyNotAvailable:
				pass
		else:
				from .feature_extraction_audio_spectrogram_transformer import ASTFeatureExtractor


else:
		import sys

		A											=     _LazyModule(__name__, globals()['__file__'], _import_structure, module_spec=__spec__)
