


'''simple docstring'''

import copy
import inspect

from transformers.testing_utils import require_torch, torch_device
from transformers.utils.backbone_utils import BackboneType


@require_torch
class    a__					:







				"""simple docstring"""



				__UpperCamelCase     :		Union[str, Any]						=						()
				__UpperCamelCase     :		Tuple						=						True




				def        _snake_case	(self		):
										__lowerCAmelCase											=					self.config_class

										# test default config
										__lowerCAmelCase											=					config_class()
										self.assertIsNotNone(__lowercase		)
										__lowerCAmelCase											=					['''stem'''] + [F"""stage{idx}""" for idx in range(1							,      len(config.depths		) + 1		)]
										self.assertEqual(config.stage_names							,      __lowercase		)
										self.assertTrue(set(config.out_features		).issubset(set(config.stage_names		)		)		)

										# Test out_features and out_indices are correctly set
										# out_features and out_indices both None
										__lowerCAmelCase											=					config_class(out_features=__lowercase							,      out_indices=__lowercase		)
										self.assertEqual(config.out_features							,      [config.stage_names[-1]]		)
										self.assertEqual(config.out_indices							,      [len(config.stage_names		) - 1]		)

										# out_features and out_indices both set
										__lowerCAmelCase											=					config_class(out_features=['''stem''', '''stage1''']							,      out_indices=[0, 1]		)
										self.assertEqual(config.out_features							,      ['''stem''', '''stage1''']		)
										self.assertEqual(config.out_indices							,      [0, 1]		)

										# Only out_features set
										__lowerCAmelCase											=					config_class(out_features=['''stage1''', '''stage3''']		)
										self.assertEqual(config.out_features							,      ['''stage1''', '''stage3''']		)
										self.assertEqual(config.out_indices							,      [1, 3]		)

										# Only out_indices set
										__lowerCAmelCase											=					config_class(out_indices=[0, 2]		)
										self.assertEqual(config.out_features							,      [config.stage_names[0], config.stage_names[2]]		)
										self.assertEqual(config.out_indices							,      [0, 2]		)

										# Error raised when out_indices do not correspond to out_features
										with self.assertRaises(__lowercase		):
																__lowerCAmelCase											=					config_class(out_features=['''stage1''', '''stage2''']							,      out_indices=[0, 2]		)




				def        _snake_case	(self		):
										__lowerCAmelCase							,       __lowerCAmelCase											=					self.model_tester.prepare_config_and_inputs_for_common()

										for model_class in self.all_model_classes:
																__lowerCAmelCase											=					model_class(__lowercase		)
																__lowerCAmelCase											=					inspect.signature(model.forward		)
																# signature.parameters is an OrderedDict => so arg_names order is deterministic
																__lowerCAmelCase											=					[*signature.parameters.keys()]
																__lowerCAmelCase											=					['''pixel_values''']
																self.assertListEqual(arg_names[:1]							,      __lowercase		)




				def        _snake_case	(self		):
										__lowerCAmelCase							,       __lowerCAmelCase											=					self.model_tester.prepare_config_and_inputs_for_common()

										for model_class in self.all_model_classes:
																__lowerCAmelCase											=					model_class(__lowercase		)
																self.assertEqual(len(model.channels		)							,      len(config.out_features		)		)
																__lowerCAmelCase											=					model.num_features
																__lowerCAmelCase											=					[config.stage_names.index(__lowercase		) for feat in config.out_features]
																__lowerCAmelCase											=					[num_features[idx] for idx in out_indices]
																self.assertListEqual(model.channels							,      __lowercase		)

																__lowerCAmelCase											=					copy.deepcopy(__lowercase		)
																__lowerCAmelCase											=					None
																__lowerCAmelCase											=					model_class(__lowercase		)
																self.assertEqual(len(model.channels		)							,      1		)
																self.assertListEqual(model.channels							,      [num_features[-1]]		)

																__lowerCAmelCase											=					copy.deepcopy(__lowercase		)
																__lowerCAmelCase											=					None
																__lowerCAmelCase											=					model_class(__lowercase		)
																self.assertEqual(len(model.channels		)							,      1		)
																self.assertListEqual(model.channels							,      [num_features[-1]]		)




				def        _snake_case	(self		):
										__lowerCAmelCase							,       __lowerCAmelCase											=					self.model_tester.prepare_config_and_inputs_for_common()

										for model_class in self.all_model_classes:
																__lowerCAmelCase											=					model_class(__lowercase		)
																model.to(__lowercase		)
																model.eval()
																__lowerCAmelCase											=					model(**__lowercase		)

																self.assertEqual(len(result.feature_maps		)							,      len(config.out_features		)		)
																self.assertEqual(len(model.channels		)							,      len(config.out_features		)		)
																self.assertEqual(len(result.feature_maps		)							,      len(config.out_indices		)		)
																self.assertEqual(len(model.channels		)							,      len(config.out_indices		)		)

																# Check output of last stage is taken if out_features=None, out_indices=None
																__lowerCAmelCase											=					copy.deepcopy(__lowercase		)
																__lowerCAmelCase											=					None
																__lowerCAmelCase											=					model_class(__lowercase		)
																model.to(__lowercase		)
																model.eval()
																__lowerCAmelCase											=					model(**__lowercase		)

																self.assertEqual(len(result.feature_maps		)							,      1		)
																self.assertEqual(len(model.channels		)							,      1		)

																__lowerCAmelCase											=					copy.deepcopy(__lowercase		)
																__lowerCAmelCase											=					None
																__lowerCAmelCase											=					model_class(__lowercase		)
																model.to(__lowercase		)
																model.eval()
																__lowerCAmelCase											=					model(**__lowercase		)

																self.assertEqual(len(result.feature_maps		)							,      1		)
																self.assertEqual(len(model.channels		)							,      1		)

																# Check backbone can be initialized with fresh weights
																__lowerCAmelCase											=					copy.deepcopy(__lowercase		)
																__lowerCAmelCase											=					False
																__lowerCAmelCase											=					model_class(__lowercase		)
																model.to(__lowercase		)
																model.eval()
																__lowerCAmelCase											=					model(**__lowercase		)




				def        _snake_case	(self		):
										__lowerCAmelCase							,       __lowerCAmelCase											=					self.model_tester.prepare_config_and_inputs_for_common()

										for backbone_class in self.all_model_classes:
																__lowerCAmelCase											=					backbone_class(__lowercase		)

																self.assertTrue(hasattr(__lowercase							,      '''backbone_type'''		)		)
																self.assertTrue(hasattr(__lowercase							,      '''stage_names'''		)		)
																self.assertTrue(hasattr(__lowercase							,      '''num_features'''		)		)
																self.assertTrue(hasattr(__lowercase							,      '''out_indices'''		)		)
																self.assertTrue(hasattr(__lowercase							,      '''out_features'''		)		)
																self.assertTrue(hasattr(__lowercase							,      '''out_feature_channels'''		)		)
																self.assertTrue(hasattr(__lowercase							,      '''channels'''		)		)

																self.assertIsInstance(backbone.backbone_type							,      __lowercase		)
																# Verify num_features has been initialized in the backbone init
																self.assertIsNotNone(backbone.num_features		)
																self.assertTrue(len(backbone.channels		) == len(backbone.out_indices		)		)
																self.assertTrue(len(backbone.stage_names		) == len(backbone.num_features		)		)
																self.assertTrue(len(backbone.channels		) <= len(backbone.num_features		)		)
																self.assertTrue(len(backbone.out_feature_channels		) == len(backbone.stage_names		)		)




				def        _snake_case	(self		):
										__lowerCAmelCase							,       __lowerCAmelCase											=					self.model_tester.prepare_config_and_inputs_for_common()
										__lowerCAmelCase											=					inputs_dict['''pixel_values'''].shape[0]

										for backbone_class in self.all_model_classes:
																__lowerCAmelCase											=					backbone_class(__lowercase		)
																backbone.to(__lowercase		)
																backbone.eval()

																__lowerCAmelCase											=					backbone(**__lowercase		)

																# Test default outputs and verify feature maps
																self.assertIsInstance(outputs.feature_maps							,      __lowercase		)
																self.assertTrue(len(outputs.feature_maps		) == len(backbone.channels		)		)
																for feature_map, n_channels in zip(outputs.feature_maps							,      backbone.channels		):
																						self.assertTrue(feature_map.shape[:2]							,      (batch_size, n_channels)		)
																self.assertIsNone(outputs.hidden_states		)
																self.assertIsNone(outputs.attentions		)

																# Test output_hidden_states=True
																__lowerCAmelCase											=					backbone(**__lowercase							,      output_hidden_states=__lowercase		)
																self.assertIsNotNone(outputs.hidden_states		)
																self.assertTrue(len(outputs.hidden_states		)							,      len(backbone.stage_names		)		)
																for hidden_state, n_channels in zip(outputs.hidden_states							,      backbone.channels		):
																						self.assertTrue(hidden_state.shape[:2]							,      (batch_size, n_channels)		)

																# Test output_attentions=True
																if self.has_attentions:
																						__lowerCAmelCase											=					backbone(**__lowercase							,      output_attentions=__lowercase		)
																						self.assertIsNotNone(outputs.attentions		)





'''simple docstring'''

from __future__ import annotations

import random
from collections.abc import Iterable
from typing import Any, Generic, TypeVar

_UpperCAmelCase					:			Any				     =					TypeVar("""T""", bound=bool)


class    a__					(			Generic[T]   ):







				"""simple docstring"""



				def __init__(self							,      __lowercase		):
										__lowerCAmelCase											=					value
										__lowerCAmelCase											=					None
										__lowerCAmelCase											=					None




				@property
				def        _snake_case	(self		):
										return self._value




				@staticmethod
				def        _snake_case	(__lowercase							,      __lowercase		):
										if not roota:
																return roota

										if not roota:
																return roota

										if roota.value > roota.value:
																__lowerCAmelCase							,       __lowerCAmelCase											=					roota, roota

										if random.choice([True, False]		):
																__lowerCAmelCase							,       __lowerCAmelCase											=					roota.right, roota.left

										__lowerCAmelCase											=					RandomizedHeapNode.merge(roota.left							,      __lowercase		)

										return roota


class    a__					(			Generic[T]   ):







				"""simple docstring"""



				def __init__(self							,      __lowercase = ()		):
										__lowerCAmelCase											=					None

										if data:
																for item in data:
																						self.insert(__lowercase		)




				def        _snake_case	(self							,      __lowercase		):
										__lowerCAmelCase											=					RandomizedHeapNode.merge(self._root							,      RandomizedHeapNode(__lowercase		)		)




				def        _snake_case	(self		):
										__lowerCAmelCase											=					self.top()

										if self._root is None:
																return None

										__lowerCAmelCase											=					RandomizedHeapNode.merge(self._root.left							,      self._root.right		)

										return result




				def        _snake_case	(self		):
										if not self._root:
																raise IndexError('''Can\'t get top element for the empty heap.'''		)
										return self._root.value




				def        _snake_case	(self		):
										__lowerCAmelCase											=					None




				def        _snake_case	(self		):
										__lowerCAmelCase											=					[]
										while self:
																result.append(self.pop()		)

										return result




				def __bool__(self		):
										return self._root is not None


if __name__ == "__main__":
	import doctest

	doctest.testmod()

