





"""simple docstring"""





from __future__ import annotations

import matplotlib.pyplot as plt  # type: ignore
import numpy

# initial triangle of Koch snowflake
lowerCAmelCase__     			=			numpy.array([0, 0])
lowerCAmelCase__     			=			numpy.array([0.5, 0.8_66_02_54])
lowerCAmelCase__     			=			numpy.array([1, 0])
lowerCAmelCase__     			=			[VECTOR_1, VECTOR_2, VECTOR_3, VECTOR_1]


def       a__					(					_SCREAMING_SNAKE_CASE  ,	_SCREAMING_SNAKE_CASE    ):




		"""simple docstring"""


		UpperCamelCase   =	initial_vectors
		for _ in range(_SCREAMING_SNAKE_CASE    ):
				UpperCamelCase   =	iteration_step(_SCREAMING_SNAKE_CASE    )
		return vectors


def       a__					(					_SCREAMING_SNAKE_CASE    ):




		"""simple docstring"""


		UpperCamelCase   =	[]
		for i, start_vector in enumerate(vectors[:-1]    ):
				UpperCamelCase   =	vectors[i + 1]
				new_vectors.append(_SCREAMING_SNAKE_CASE    )
				UpperCamelCase   =	end_vector - start_vector
				new_vectors.append(start_vector + difference_vector / 3    )
				new_vectors.append(
				    start_vector + difference_vector / 3 + rotate(difference_vector / 3  ,	60    )    )
				new_vectors.append(start_vector + difference_vector * 2 / 3    )
		new_vectors.append(vectors[-1]    )
		return new_vectors


def       a__					(					_SCREAMING_SNAKE_CASE  ,	_SCREAMING_SNAKE_CASE    ):




		"""simple docstring"""


		UpperCamelCase   =	numpy.radians(_SCREAMING_SNAKE_CASE    )
		UpperCamelCase   ,				UpperCamelCase   =	numpy.cos(_SCREAMING_SNAKE_CASE    ), numpy.sin(_SCREAMING_SNAKE_CASE    )
		UpperCamelCase   =	numpy.array(((c, -s), (s, c))    )
		return numpy.dot(_SCREAMING_SNAKE_CASE  ,	_SCREAMING_SNAKE_CASE    )


def       a__					(					_SCREAMING_SNAKE_CASE    ):




		"""simple docstring"""


		UpperCamelCase   =	plt.gca()
		axes.set_aspect("equal"    )

		# matplotlib.pyplot.plot takes a list of all x-coordinates and a list of all
		# y-coordinates as inputs, which are constructed from the vector-list using
		# zip()
		UpperCamelCase   ,				UpperCamelCase   =	zip(*_SCREAMING_SNAKE_CASE    )
		plt.plot(_SCREAMING_SNAKE_CASE  ,	_SCREAMING_SNAKE_CASE    )
		plt.show()


if __name__ == "__main__":
						import doctest

						doctest.testmod()

						lowerCAmelCase__     			=			iterate(INITIAL_VECTORS, 5)
						plot(processed_vectors)













"""simple docstring"""





import copy

from ...configuration_utils import PretrainedConfig
from ...utils import logging
from ..auto.configuration_auto import CONFIG_MAPPING


lowerCAmelCase__     			=			logging.get_logger(__name__)





class        _lowerCamelCase      (       _lowercase ):
						UpperCAmelCase_ =			"upernet"


						def __init__(self   ,							__a=None   ,							__a=5_12   ,							__a=0.02   ,							__a=[1, 2, 3, 6]   ,							__a=True   ,							__a=0.4   ,							__a=3_84   ,							__a=2_56   ,							__a=1   ,							__a=False   ,							__a=2_55   ,							**__a   ,							) ->   Tuple:
								super().__init__(**__a		)

								if backbone_config is None:
										logger.info("`backbone_config` is `None`. Initializing the config with the default `ResNet` backbone."		)
										UpperCamelCase   =	CONFIG_MAPPING["resnet"](out_features=["stage1", "stage2", "stage3", "stage4"]		)
								elif isinstance(__a   ,							__a		):
										UpperCamelCase   =	backbone_config.get("model_type"		)
										UpperCamelCase   =	CONFIG_MAPPING[backbone_model_type]
										UpperCamelCase   =	config_class.from_dict(__a		)

								UpperCamelCase   =	backbone_config
								UpperCamelCase   =	hidden_size
								UpperCamelCase   =	initializer_range
								UpperCamelCase   =	pool_scales
								UpperCamelCase   =	use_auxiliary_head
								UpperCamelCase   =	auxiliary_loss_weight
								UpperCamelCase   =	auxiliary_in_channels
								UpperCamelCase   =	auxiliary_channels
								UpperCamelCase   =	auxiliary_num_convs
								UpperCamelCase   =	auxiliary_concat_input
								UpperCamelCase   =	loss_ignore_index




						def     snake_case_   (self		) ->   Optional[int]:
								UpperCamelCase   =	copy.deepcopy(self.__dict__		)
								UpperCamelCase   =	self.backbone_config.to_dict()
								UpperCamelCase   =	self.__class__.model_type
								return output






