






from typing import TYPE_CHECKING

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


_UpperCAmelCase			:		int   				=    {
    "configuration_ctrl": ["CTRL_PRETRAINED_CONFIG_ARCHIVE_MAP", "CTRLConfig"],
    "tokenization_ctrl": ["CTRLTokenizer"],
}

try:
			if not is_torch_available():
						raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
			pass
else:
			_UpperCAmelCase			:		List[str]   				=    [
			    "CTRL_PRETRAINED_MODEL_ARCHIVE_LIST",
			    "CTRLForSequenceClassification",
			    "CTRLLMHeadModel",
			    "CTRLModel",
			    "CTRLPreTrainedModel",
			]

try:
			if not is_tf_available():
						raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
			pass
else:
			_UpperCAmelCase			:		str   				=    [
			    "TF_CTRL_PRETRAINED_MODEL_ARCHIVE_LIST",
			    "TFCTRLForSequenceClassification",
			    "TFCTRLLMHeadModel",
			    "TFCTRLModel",
			    "TFCTRLPreTrainedModel",
			]


if TYPE_CHECKING:
			from .configuration_ctrl import CTRL_PRETRAINED_CONFIG_ARCHIVE_MAP, CTRLConfig
			from .tokenization_ctrl import CTRLTokenizer

			try:
						if not is_torch_available():
									raise OptionalDependencyNotAvailable()
			except OptionalDependencyNotAvailable:
						pass
			else:
						from .modeling_ctrl import (
						    CTRL_PRETRAINED_MODEL_ARCHIVE_LIST,
						    CTRLForSequenceClassification,
						    CTRLLMHeadModel,
						    CTRLModel,
						    CTRLPreTrainedModel,
						)

			try:
						if not is_tf_available():
									raise OptionalDependencyNotAvailable()
			except OptionalDependencyNotAvailable:
						pass
			else:
						from .modeling_tf_ctrl import (
						    TF_CTRL_PRETRAINED_MODEL_ARCHIVE_LIST,
						    TFCTRLForSequenceClassification,
						    TFCTRLLMHeadModel,
						    TFCTRLModel,
						    TFCTRLPreTrainedModel,
						)

else:
			import sys

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













from typing import TYPE_CHECKING

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


_UpperCAmelCase			:		List[Any]   				=    {
    "configuration_mobilenet_v2": [
        "MOBILENET_V2_PRETRAINED_CONFIG_ARCHIVE_MAP",
        "MobileNetV2Config",
        "MobileNetV2OnnxConfig",
    ],
}

try:
			if not is_vision_available():
						raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
			pass
else:
			_UpperCAmelCase			:		str   				=    ["MobileNetV2FeatureExtractor"]
			_UpperCAmelCase			:		Union[str, Any]   				=    ["MobileNetV2ImageProcessor"]


try:
			if not is_torch_available():
						raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
			pass
else:
			_UpperCAmelCase			:		Any   				=    [
			    "MOBILENET_V2_PRETRAINED_MODEL_ARCHIVE_LIST",
			    "MobileNetV2ForImageClassification",
			    "MobileNetV2ForSemanticSegmentation",
			    "MobileNetV2Model",
			    "MobileNetV2PreTrainedModel",
			    "load_tf_weights_in_mobilenet_v2",
			]


if TYPE_CHECKING:
			from .configuration_mobilenet_va import (
			    MOBILENET_V2_PRETRAINED_CONFIG_ARCHIVE_MAP,
			    MobileNetVaConfig,
			    MobileNetVaOnnxConfig,
			)

			try:
						if not is_vision_available():
									raise OptionalDependencyNotAvailable()
			except OptionalDependencyNotAvailable:
						pass
			else:
						from .feature_extraction_mobilenet_va import MobileNetVaFeatureExtractor
						from .image_processing_mobilenet_va import MobileNetVaImageProcessor

			try:
						if not is_torch_available():
									raise OptionalDependencyNotAvailable()
			except OptionalDependencyNotAvailable:
						pass
			else:
						from .modeling_mobilenet_va import (
						    MOBILENET_V2_PRETRAINED_MODEL_ARCHIVE_LIST,
						    MobileNetVaForImageClassification,
						    MobileNetVaForSemanticSegmentation,
						    MobileNetVaModel,
						    MobileNetVaPreTrainedModel,
						    load_tf_weights_in_mobilenet_va,
						)


else:
			import sys

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





