



'''simple docstring'''
from typing import TYPE_CHECKING

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


snake_case_			:     str  	=  {'configuration_dpt': ['DPT_PRETRAINED_CONFIG_ARCHIVE_MAP', 'DPTConfig']}

try:
					if not is_vision_available():
										raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
					pass
else:
					snake_case_			:     str  	=  ['DPTFeatureExtractor']
					snake_case_			:     List[Any]  	=  ['DPTImageProcessor']

try:
					if not is_torch_available():
										raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
					pass
else:
					snake_case_			:     List[str]  	=  [
					    'DPT_PRETRAINED_MODEL_ARCHIVE_LIST',
					    'DPTForDepthEstimation',
					    'DPTForSemanticSegmentation',
					    'DPTModel',
					    'DPTPreTrainedModel',
					]


if TYPE_CHECKING:
					from .configuration_dpt import DPT_PRETRAINED_CONFIG_ARCHIVE_MAP, DPTConfig

					try:
										if not is_vision_available():
															raise OptionalDependencyNotAvailable()
					except OptionalDependencyNotAvailable:
										pass
					else:
										from .feature_extraction_dpt import DPTFeatureExtractor
										from .image_processing_dpt import DPTImageProcessor

					try:
										if not is_torch_available():
															raise OptionalDependencyNotAvailable()
					except OptionalDependencyNotAvailable:
										pass
					else:
										from .modeling_dpt import (
										    DPT_PRETRAINED_MODEL_ARCHIVE_LIST,
										    DPTForDepthEstimation,
										    DPTForSemanticSegmentation,
										    DPTModel,
										    DPTPreTrainedModel,
										)


else:
					import sys

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







'''simple docstring'''
from torch import nn






def A__   (					UpperCAmelCase_							):
						if act_fn in ["swish", "silu"]:
												return nn.SiLU()
						elif act_fn == "mish":
												return nn.Mish()
						elif act_fn == "gelu":
												return nn.GELU()
						else:
												raise ValueError(f'Unsupported activation function: {act_fn}'							)


