
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      :				Tuple          = TaTokenizer

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

_UpperCAmelCase      :				List[str]          = TaTokenizerFast

_UpperCAmelCase      :				Tuple          = {"configuration_mt5": ["MT5Config", "MT5OnnxConfig"]}

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

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

try:
					if not is_flax_available():
										raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
					pass
else:
					_UpperCAmelCase      :				List[Any]          = ["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      :				Optional[Any]          = _LazyModule(
					    __name__,
					    globals()["__file__"],
					    _import_structure,
					    extra_objects={"MT5Tokenizer": MTaTokenizer, "MT5TokenizerFast": MTaTokenizerFast},
					    module_spec=__spec__,
					)


from typing import TYPE_CHECKING

from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available


_UpperCAmelCase      :				Union[str, Any]          = {
    "configuration_git": ["GIT_PRETRAINED_CONFIG_ARCHIVE_MAP", "GitConfig", "GitVisionConfig"],
    "processing_git": ["GitProcessor"],
}

try:
					if not is_torch_available():
										raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
					pass
else:
					_UpperCAmelCase      :				Dict          = [
					    "GIT_PRETRAINED_MODEL_ARCHIVE_LIST",
					    "GitForCausalLM",
					    "GitModel",
					    "GitPreTrainedModel",
					    "GitVisionModel",
					]

if TYPE_CHECKING:
					from .configuration_git import GIT_PRETRAINED_CONFIG_ARCHIVE_MAP, GitConfig, GitVisionConfig
					from .processing_git import GitProcessor

					try:
										if not is_torch_available():
															raise OptionalDependencyNotAvailable()
					except OptionalDependencyNotAvailable:
										pass
					else:
										from .modeling_git import (
										    GIT_PRETRAINED_MODEL_ARCHIVE_LIST,
										    GitForCausalLM,
										    GitModel,
										    GitPreTrainedModel,
										    GitVisionModel,
										)

else:
					import sys

					_UpperCAmelCase      :				int          = _LazyModule(__name__, globals()["__file__"], _import_structure, module_spec=__spec__)
