





from typing import Tuple, Union

from ...modeling_outputs import BackboneOutput
from ...modeling_utils import PreTrainedModel
from ...utils import is_timm_available, is_torch_available, requires_backends
from ...utils.backbone_utils import BackboneMixin
from .configuration_timm_backbone import TimmBackboneConfig


if is_timm_available():
			import timm


if is_torch_available():
			from torch import Tensor






class       __A					(					lowerCAmelCase    ,       lowerCAmelCase				):

			'''simple docstring'''







			lowerCAmelCase_							  =		"""pixel_values"""
			lowerCAmelCase_							  =		False
			lowerCAmelCase_							  =		TimmBackboneConfig





			def __init__(					self ,						__lowerCAmelCase ,						**__lowerCAmelCase							):



				'''simple docstring'''







				requires_backends(self ,						'''timm'''							)
				super().__init__(__lowerCAmelCase							)
				lowerCamelCase__              =	config

				if config.backbone is None:
					raise ValueError('''backbone is not set in the config. Please set it to a timm model name.'''							)

				if config.backbone not in timm.list_models():
					raise ValueError(F'backbone {config.backbone} is not supported by timm.'							)

				if hasattr(__lowerCAmelCase ,						'''out_features'''							) and config.out_features is not None:
					raise ValueError('''out_features is not supported by TimmBackbone. Please use out_indices instead.'''							)

				lowerCamelCase__              =	getattr(__lowerCAmelCase ,						'''use_pretrained_backbone''' ,						__lowerCAmelCase							)
				if pretrained is None:
					raise ValueError('''use_pretrained_backbone is not set in the config. Please set it to True or False.'''							)

				# We just take the final layer by default. This matches the default for the transformers models.
				lowerCamelCase__              =	config.out_indices if getattr(__lowerCAmelCase ,						'''out_indices''' ,						__lowerCAmelCase							) is not None else (-1,)

				lowerCamelCase__              =	timm.create_model(
				    config.backbone ,						pretrained=__lowerCAmelCase ,						features_only=config.features_only ,						in_chans=config.num_channels ,						out_indices=__lowerCAmelCase ,						**__lowerCAmelCase ,						)
				# These are used to control the output of the model when called. If output_hidden_states is True, then
				# return_layers is modified to include all layers.
				lowerCamelCase__              =	self._backbone.return_layers
				lowerCamelCase__              =	{layer['''module''']: str(__lowerCAmelCase							) for i, layer in enumerate(self._backbone.feature_info.info							)}
				super()._init_backbone(__lowerCAmelCase							)





			@classmethod
			def 	__lowerCamelCase       (					cls ,						__lowerCAmelCase ,						*__lowerCAmelCase ,						**__lowerCAmelCase							):



				'''simple docstring'''







				requires_backends(cls ,						['''vision''', '''timm''']							)
				from ...models.timm_backbone import TimmBackboneConfig

				lowerCamelCase__              =	kwargs.pop('''config''' ,						TimmBackboneConfig()							)

				lowerCamelCase__              =	kwargs.pop('''use_timm_backbone''' ,						__lowerCAmelCase							)
				if not use_timm:
					raise ValueError('''use_timm_backbone must be True for timm backbones'''							)

				lowerCamelCase__              =	kwargs.pop('''num_channels''' ,						config.num_channels							)
				lowerCamelCase__              =	kwargs.pop('''features_only''' ,						config.features_only							)
				lowerCamelCase__              =	kwargs.pop('''use_pretrained_backbone''' ,						config.use_pretrained_backbone							)
				lowerCamelCase__              =	kwargs.pop('''out_indices''' ,						config.out_indices							)
				lowerCamelCase__              =	TimmBackboneConfig(
				    backbone=__lowerCAmelCase ,						num_channels=__lowerCAmelCase ,						features_only=__lowerCAmelCase ,						use_pretrained_backbone=__lowerCAmelCase ,						out_indices=__lowerCAmelCase ,						)
				return super()._from_config(__lowerCAmelCase ,						**__lowerCAmelCase							)





			def 	__lowerCamelCase       (					self ,						__lowerCAmelCase							):



				'''simple docstring'''







				pass





			def 	__lowerCamelCase       (					self ,						__lowerCAmelCase ,						__lowerCAmelCase=None ,						__lowerCAmelCase=None ,						__lowerCAmelCase=None ,						**__lowerCAmelCase							):



				'''simple docstring'''







				lowerCamelCase__              =	return_dict if return_dict is not None else self.config.use_return_dict
				lowerCamelCase__              =	(
				    output_hidden_states if output_hidden_states is not None else self.config.output_hidden_states
				)
				lowerCamelCase__              =	output_attentions if output_attentions is not None else self.config.output_attentions

				if output_attentions:
					raise ValueError('''Cannot output attentions for timm backbones at the moment'''							)

				if output_hidden_states:
					# We modify the return layers to include all the stages of the backbone
					lowerCamelCase__              =	self._all_layers
					lowerCamelCase__              =	self._backbone(__lowerCAmelCase ,						**__lowerCAmelCase							)
					lowerCamelCase__              =	self._return_layers
					lowerCamelCase__              =	tuple(hidden_states[i] for i in self.out_indices							)
				else:
					lowerCamelCase__              =	self._backbone(__lowerCAmelCase ,						**__lowerCAmelCase							)
					lowerCamelCase__              =	None

				lowerCamelCase__              =	tuple(__lowerCAmelCase							)
				lowerCamelCase__              =	tuple(__lowerCAmelCase							) if hidden_states is not None else None

				if not return_dict:
					lowerCamelCase__              =	(feature_maps,)
					if output_hidden_states:
						lowerCamelCase__              =	output + (hidden_states,)
					return output

				return BackboneOutput(feature_maps=__lowerCAmelCase ,						hidden_states=__lowerCAmelCase ,						attentions=__lowerCAmelCase							)










from __future__ import annotations





def lowerCAmelCase__(__snake_case ,__snake_case ,__snake_case							)       ->   float:







	'''simple docstring'''







	if days_between_payments <= 0:
		raise ValueError('''days_between_payments must be > 0'''							)
	if daily_interest_rate < 0:
		raise ValueError('''daily_interest_rate must be >= 0'''							)
	if principal <= 0:
		raise ValueError('''principal must be > 0'''							)
	return principal * daily_interest_rate * days_between_payments





def lowerCAmelCase__(__snake_case ,__snake_case ,__snake_case ,)       ->   float:







	'''simple docstring'''







	if number_of_compounding_periods <= 0:
		raise ValueError('''number_of_compounding_periods must be > 0'''							)
	if nominal_annual_interest_rate_percentage < 0:
		raise ValueError('''nominal_annual_interest_rate_percentage must be >= 0'''							)
	if principal <= 0:
		raise ValueError('''principal must be > 0'''							)

	return principal * (
	    (1 + nominal_annual_interest_rate_percentage) ** number_of_compounding_periods
	    - 1
	)





def lowerCAmelCase__(__snake_case ,__snake_case ,__snake_case ,)       ->   float:







	'''simple docstring'''







	if number_of_years <= 0:
		raise ValueError('''number_of_years must be > 0'''							)
	if nominal_annual_percentage_rate < 0:
		raise ValueError('''nominal_annual_percentage_rate must be >= 0'''							)
	if principal <= 0:
		raise ValueError('''principal must be > 0'''							)

	return compound_interest(
	    __snake_case ,nominal_annual_percentage_rate / 365 ,number_of_years * 365							)


if __name__ == "__main__":
			import doctest

			doctest.testmod()



