


'''simple docstring'''






from collections import Counter

import numpy as np
from sklearn import datasets
from sklearn.model_selection import train_test_split

__UpperCAmelCase					       =							datasets.load_iris()

__UpperCAmelCase					       =							np.array(data['''data'''])
__UpperCAmelCase					       =							np.array(data['''target'''])
__UpperCAmelCase					       =							data['''target_names''']

__UpperCAmelCase       ,    __UpperCAmelCase       ,    __UpperCAmelCase       ,    __UpperCAmelCase					       =							train_test_split(X, y)


def       _snake_case     (  A				,					A )		->					str:
							return np.linalg.norm(np.array(A ) - np.array(A ) )


def       _snake_case     (  A				,					A				,					A				,					A				,					A=5 )		->					List[Any]:
							lowerCAmelCase__      =			zip(A				,					A )
							# List of distances of all points from the point to be classified
							lowerCAmelCase__      =			[]
							for data_point in data:
														lowerCAmelCase__      =			euclidean_distance(data_point[0]				,					A )
														distances.append((distance, data_point[1]) )
							# Choosing 'k' points with the least distances.
							lowerCAmelCase__      =			[i[1] for i in sorted(A )[:k]]
							# Most commonly occurring class among them
							# is the class into which the point is classified
							lowerCAmelCase__      =			Counter(A ).most_common(1 )[0][0]
							return classes[result]


if __name__ == "__main__":
		print(classifier(X_train, y_train, classes, [4.4, 3.1, 1.3, 1.4]))



'''simple docstring'''






import jax.numpy as jnp

from ...utils import logging
from ..ta.modeling_flax_ta import FlaxTaEncoderModel, FlaxTaForConditionalGeneration, FlaxTaModel
from .configuration_mta import MTaConfig


__UpperCAmelCase					       =							logging.get_logger(__name__)

__UpperCAmelCase					       =							'''T5Config'''


def       _snake_case     (  A				,					A				,					A )		->					jnp.ndarray:
							lowerCAmelCase__      =			jnp.zeros_like(A )
							lowerCAmelCase__      =			shifted_input_ids.at[:, 1:].set(input_ids[:, :-1] )
							lowerCAmelCase__      =			shifted_input_ids.at[:, 0].set(A )

							lowerCAmelCase__      =			jnp.where(shifted_input_ids == -100				,					A				,					A )
							return shifted_input_ids




class 	a__       (							a__						):





							'''simple docstring'''






							lowercase__    :     int					=   "mt5"
							lowercase__    :     Dict					=   MTaConfig




class 	a__       (							a__						):





							'''simple docstring'''






							lowercase__    :     int					=   "mt5"
							lowercase__    :     Any					=   MTaConfig




class 	a__       (							a__						):





							'''simple docstring'''






							lowercase__    :     Union[str, Any]					=   "mt5"
							lowercase__    :     Tuple					=   MTaConfig