




from typing import TYPE_CHECKING

from ...utils import (
    OptionalDependencyNotAvailable,
    _LazyModule,
    is_flax_available,
    is_sentencepiece_available,
    is_tf_available,
    is_tokenizers_available,
    is_torch_available,
)


if is_sentencepiece_available():
		from ..ta.tokenization_ta import TaTokenizer
else:
		from ...utils.dummy_sentencepiece_objects import TaTokenizer

__UpperCamelCase					:       List[Any]    					=      TaTokenizer

if is_tokenizers_available():
		from ..ta.tokenization_ta_fast import TaTokenizerFast
else:
		from ...utils.dummy_tokenizers_objects import TaTokenizerFast

__UpperCamelCase					:       Optional[int]    					=      TaTokenizerFast

__UpperCamelCase					:       str    					=      {"configuration_mt5": ["MT5Config", "MT5OnnxConfig"]}

try:
		if not is_torch_available():
				raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
		pass
else:
		__UpperCamelCase					:       Any    					=      [
		    "MT5EncoderModel",
		    "MT5ForConditionalGeneration",
		    "MT5ForQuestionAnswering",
		    "MT5Model",
		    "MT5PreTrainedModel",
		    "MT5Stack",
		]

try:
		if not is_tf_available():
				raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
		pass
else:
		__UpperCamelCase					:       Optional[Any]    					=      ["TFMT5EncoderModel", "TFMT5ForConditionalGeneration", "TFMT5Model"]

try:
		if not is_flax_available():
				raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
		pass
else:
		__UpperCamelCase					:       List[str]    					=      ["FlaxMT5EncoderModel", "FlaxMT5ForConditionalGeneration", "FlaxMT5Model"]


if TYPE_CHECKING:
		from .configuration_mta import MTaConfig, MTaOnnxConfig

		try:
				if not is_torch_available():
						raise OptionalDependencyNotAvailable()
		except OptionalDependencyNotAvailable:
				pass
		else:
				from .modeling_mta import (
				    MTaEncoderModel,
				    MTaForConditionalGeneration,
				    MTaForQuestionAnswering,
				    MTaModel,
				    MTaPreTrainedModel,
				    MTaStack,
				)

		try:
				if not is_tf_available():
						raise OptionalDependencyNotAvailable()
		except OptionalDependencyNotAvailable:
				pass
		else:
				from .modeling_tf_mta import TFMTaEncoderModel, TFMTaForConditionalGeneration, TFMTaModel

		try:
				if not is_flax_available():
						raise OptionalDependencyNotAvailable()
		except OptionalDependencyNotAvailable:
				pass
		else:
				from .modeling_flax_mta import FlaxMTaEncoderModel, FlaxMTaForConditionalGeneration, FlaxMTaModel

else:
		import sys

		__UpperCamelCase					:       Tuple    					=      _LazyModule(
		    __name__,
		    globals()["__file__"],
		    _import_structure,
		    extra_objects={"MT5Tokenizer": MTaTokenizer, "MT5TokenizerFast": MTaTokenizerFast},
		    module_spec=__spec__,
		)



"""simple docstring"""





import warnings

from ...utils import logging
from .image_processing_yolos import YolosImageProcessor


__magic_name__       =			logging.get_logger(__name__)
class 						SCREAMING_SNAKE_CASE_ (						__a ):




		"""simple docstring"""





		def __init__(     self							,  *lowerCAmelCase__							,  **lowerCAmelCase__):
				warnings.warn(
				    """The class YolosFeatureExtractor is deprecated and will be removed in version 5 of Transformers. Please"""
				    """ use YolosImageProcessor instead."""							,  lowerCAmelCase__							,  )
				super().__init__(*lowerCAmelCase__							,  **lowerCAmelCase__)




