





# Copyright 2023 The HuggingFace Team. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
#     http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
from typing import TYPE_CHECKING

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


_lowercase		:     Optional[int] 					={
    """configuration_tvlt""": ["""TVLT_PRETRAINED_CONFIG_ARCHIVE_MAP""", """TvltConfig"""],
    """feature_extraction_tvlt""": ["""TvltFeatureExtractor"""],
    """processing_tvlt""": ["""TvltProcessor"""],
}

try:
		if not is_torch_available():
				raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
		pass
else:
		_lowercase		:     List[str] 					=[
		    """TVLT_PRETRAINED_MODEL_ARCHIVE_LIST""",
		    """TvltModel""",
		    """TvltForPreTraining""",
		    """TvltForAudioVisualClassification""",
		    """TvltPreTrainedModel""",
		]

try:
		if not is_vision_available():
				raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
		pass
else:
		_lowercase		:     List[Any] 					=["""TvltImageProcessor"""]


if TYPE_CHECKING:
		from .configuration_tvlt import TVLT_PRETRAINED_CONFIG_ARCHIVE_MAP, TvltConfig
		from .processing_tvlt import TvltProcessor
		from .feature_extraction_tvlt import TvltFeatureExtractor

		try:
				if not is_torch_available():
						raise OptionalDependencyNotAvailable()
		except OptionalDependencyNotAvailable:
				pass
		else:
				from .modeling_tvlt import (
				    TVLT_PRETRAINED_MODEL_ARCHIVE_LIST,
				    TvltForAudioVisualClassification,
				    TvltForPreTraining,
				    TvltModel,
				    TvltPreTrainedModel,
				)

		try:
				if not is_vision_available():
						raise OptionalDependencyNotAvailable()
		except OptionalDependencyNotAvailable:
				pass
		else:
				from .image_processing_tvlt import TvltImageProcessor


else:
		import sys

		_lowercase		:     Union[str, Any] 					=_LazyModule(__name__, globals()["""__file__"""], _import_structure, module_spec=__spec__)







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,
)


_lowercase		:     int 					={
    """configuration_marian""": ["""MARIAN_PRETRAINED_CONFIG_ARCHIVE_MAP""", """MarianConfig""", """MarianOnnxConfig"""],
}

try:
		if not is_sentencepiece_available():
				raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
		pass
else:
		_lowercase		:     Any 					=["""MarianTokenizer"""]

try:
		if not is_torch_available():
				raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
		pass
else:
		_lowercase		:     Any 					=[
		    """MARIAN_PRETRAINED_MODEL_ARCHIVE_LIST""",
		    """MarianForCausalLM""",
		    """MarianModel""",
		    """MarianMTModel""",
		    """MarianPreTrainedModel""",
		]

try:
		if not is_tf_available():
				raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
		pass
else:
		_lowercase		:     Dict 					=["""TFMarianModel""", """TFMarianMTModel""", """TFMarianPreTrainedModel"""]

try:
		if not is_flax_available():
				raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
		pass
else:
		_lowercase		:     Optional[Any] 					=["""FlaxMarianModel""", """FlaxMarianMTModel""", """FlaxMarianPreTrainedModel"""]

if TYPE_CHECKING:
		from .configuration_marian import MARIAN_PRETRAINED_CONFIG_ARCHIVE_MAP, MarianConfig, MarianOnnxConfig

		try:
				if not is_sentencepiece_available():
						raise OptionalDependencyNotAvailable()
		except OptionalDependencyNotAvailable:
				pass
		else:
				from .tokenization_marian import MarianTokenizer

		try:
				if not is_torch_available():
						raise OptionalDependencyNotAvailable()
		except OptionalDependencyNotAvailable:
				pass
		else:
				from .modeling_marian import (
				    MARIAN_PRETRAINED_MODEL_ARCHIVE_LIST,
				    MarianForCausalLM,
				    MarianModel,
				    MarianMTModel,
				    MarianPreTrainedModel,
				)

		try:
				if not is_tf_available():
						raise OptionalDependencyNotAvailable()
		except OptionalDependencyNotAvailable:
				pass
		else:
				from .modeling_tf_marian import TFMarianModel, TFMarianMTModel, TFMarianPreTrainedModel

		try:
				if not is_flax_available():
						raise OptionalDependencyNotAvailable()
		except OptionalDependencyNotAvailable:
				pass
		else:
				from .modeling_flax_marian import FlaxMarianModel, FlaxMarianMTModel, FlaxMarianPreTrainedModel

else:
		import sys

		_lowercase		:     List[str] 					=_LazyModule(__name__, globals()["""__file__"""], _import_structure, module_spec=__spec__)
