




"""simple docstring"""

from .number_theory.prime_numbers import next_prime
class 			lowerCamelCase__    :


			def __init__(     self				, SCREAMING_SNAKE_CASE				, SCREAMING_SNAKE_CASE = None				, SCREAMING_SNAKE_CASE = None				, ):



					"""simple docstring"""







					snake_case		:						Optional[Any]								=				size_table
					snake_case		:						List[Any]								=				[None] * self.size_table
					snake_case		:						Any								=				0.75 if lim_charge is None else lim_charge
					snake_case		:						str								=				1 if charge_factor is None else charge_factor
					snake_case		:						list								=				[]
					snake_case		:						dict								=				{}


			def 							lowerCamelCase_				(     self							):



					"""simple docstring"""







					return self._keys


			def 							lowerCamelCase_				(     self							):



					"""simple docstring"""







					return sum(1 for slot in self.values if slot is not None							) / (
					    self.size_table * self.charge_factor
					)


			def 							lowerCamelCase_				(     self				, SCREAMING_SNAKE_CASE							):



					"""simple docstring"""







					return key % self.size_table


			def 							lowerCamelCase_				(     self				, SCREAMING_SNAKE_CASE							):



					"""simple docstring"""







					print(F'''step {step_ord}'''							)
					print(list(range(len(self.values							)							)							)							)
					print(self.values							)


			def 							lowerCamelCase_				(     self				, SCREAMING_SNAKE_CASE							):



					"""simple docstring"""







					snake_case		:						Any								=				1
					snake_case		:						Tuple								=				values
					for value in values:
							self.insert_data(SCREAMING_SNAKE_CASE							)
							self._step_by_step(SCREAMING_SNAKE_CASE							)
							i += 1


			def 							lowerCamelCase_				(     self				, SCREAMING_SNAKE_CASE				, SCREAMING_SNAKE_CASE							):



					"""simple docstring"""







					snake_case		:						str								=				data
					snake_case		:						Any								=				data


			def 							lowerCamelCase_				(     self				, SCREAMING_SNAKE_CASE				, SCREAMING_SNAKE_CASE=None							):



					"""simple docstring"""







					snake_case		:						List[Any]								=				self.hash_function(key + 1							)

					while self.values[new_key] is not None and self.values[new_key] != key:
							if self.values.count(SCREAMING_SNAKE_CASE							) > 0:
									snake_case		:						Any								=				self.hash_function(new_key + 1							)
							else:
									snake_case		:						Optional[Any]								=				None
									break

					return new_key


			def 							lowerCamelCase_				(     self							):



					"""simple docstring"""







					snake_case		:						Tuple								=				[value for value in self.values if value is not None]
					snake_case		:						Dict								=				next_prime(self.size_table				, factor=2							)
					self._keys.clear()
					snake_case		:						Union[str, Any]								=				[None] * self.size_table  # hell's pointers D: don't DRY ;/
					for value in survivor_values:
							self.insert_data(SCREAMING_SNAKE_CASE							)



			def 							lowerCamelCase_				(     self				, SCREAMING_SNAKE_CASE							):



					"""simple docstring"""







					snake_case		:						Dict								=				self.hash_function(SCREAMING_SNAKE_CASE							)

					if self.values[key] is None:
							self._set_value(SCREAMING_SNAKE_CASE				, SCREAMING_SNAKE_CASE							)

					elif self.values[key] == data:
							pass

					else:
							snake_case		:						List[str]								=				self._collision_resolution(SCREAMING_SNAKE_CASE				, SCREAMING_SNAKE_CASE							)
							if collision_resolution is not None:
									self._set_value(SCREAMING_SNAKE_CASE				, SCREAMING_SNAKE_CASE							)
							else:
									self.rehashing()
									self.insert_data(SCREAMING_SNAKE_CASE							)







"""simple docstring"""

from ...processing_utils import ProcessorMixin
from ...tokenization_utils_base import BatchEncoding
class 			lowerCamelCase__    (  lowerCamelCase_			):
			a__ :      Tuple								=     ["""image_processor""", """tokenizer"""]
			a__ :      List[Any]								=     """EfficientNetImageProcessor"""
			a__ :      str								=     ("""BertTokenizer""", """BertTokenizerFast""")


			def __init__(     self				, SCREAMING_SNAKE_CASE				, SCREAMING_SNAKE_CASE							):



					"""simple docstring"""







					super().__init__(SCREAMING_SNAKE_CASE				, SCREAMING_SNAKE_CASE							)


			def __call__(     self				, SCREAMING_SNAKE_CASE=None				, SCREAMING_SNAKE_CASE=None				, SCREAMING_SNAKE_CASE="max_length"				, SCREAMING_SNAKE_CASE=64				, SCREAMING_SNAKE_CASE=None				, **SCREAMING_SNAKE_CASE							):



					"""simple docstring"""







					if text is None and images is None:
							raise ValueError("You have to specify either text or images. Both cannot be none."							)

					if text is not None:
							snake_case		:						Dict								=				self.tokenizer(
							    SCREAMING_SNAKE_CASE				, padding=SCREAMING_SNAKE_CASE				, max_length=SCREAMING_SNAKE_CASE				, return_tensors=SCREAMING_SNAKE_CASE				, **SCREAMING_SNAKE_CASE							)

					if images is not None:
							snake_case		:						Tuple								=				self.image_processor(SCREAMING_SNAKE_CASE				, return_tensors=SCREAMING_SNAKE_CASE				, **SCREAMING_SNAKE_CASE							)

					if text is not None and images is not None:
							snake_case		:						Dict								=				image_features.pixel_values
							return encoding
					elif text is not None:
							return encoding
					else:
							return BatchEncoding(data=dict(**SCREAMING_SNAKE_CASE							)				, tensor_type=SCREAMING_SNAKE_CASE							)


			def 							lowerCamelCase_				(     self				, *SCREAMING_SNAKE_CASE				, **SCREAMING_SNAKE_CASE							):



					"""simple docstring"""







					return self.tokenizer.batch_decode(*SCREAMING_SNAKE_CASE				, **SCREAMING_SNAKE_CASE							)


			def 							lowerCamelCase_				(     self				, *SCREAMING_SNAKE_CASE				, **SCREAMING_SNAKE_CASE							):



					"""simple docstring"""







					return self.tokenizer.decode(*SCREAMING_SNAKE_CASE				, **SCREAMING_SNAKE_CASE							)



			@property
			def 							lowerCamelCase_				(     self							):



					"""simple docstring"""







					snake_case		:						Optional[Any]								=				self.tokenizer.model_input_names
					snake_case		:						Any								=				self.image_processor.model_input_names
					return list(dict.fromkeys(tokenizer_input_names + image_processor_input_names							)							)

