
from collections import Counter

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

lowercase        =  datasets.load_iris()

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

lowercase   ,						lowercase   ,						lowercase   ,						lowercase        =  train_test_split(X, y)



def      __lowerCAmelCase						(							UpperCAmelCase__				:      Tuple			,				UpperCAmelCase__				:      int       )  ->    Dict:
							return np.linalg.norm(np.array(UpperCAmelCase__       ) - np.array(UpperCAmelCase__       )       )



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







import collections
import os
from typing import List, Optional, Tuple

from transformers.utils import is_jieba_available, requires_backends


if is_jieba_available():
		import jieba

from ...tokenization_utils import PreTrainedTokenizer
from ...utils import logging


lowercase        =  logging.get_logger(__name__)

lowercase        =  {'''vocab_file''': '''vocab.txt'''}

lowercase        =  {
    '''vocab_file''': {
        '''openbmb/cpm-ant-10b''': '''https://huggingface.co/openbmb/cpm-ant-10b/blob/main/vocab.txt''',
    },
}

lowercase        =  {
    '''openbmb/cpm-ant-10b''': 1_0_2_4,
}



def      __lowerCAmelCase						(							UpperCAmelCase__				:      List[str]       )  ->    Dict:
							lowerCamelCase_							  =					collections.OrderedDict()
							with open(UpperCAmelCase__			,				"""r"""			,				encoding="""utf-8"""       ) as reader:
														lowerCamelCase_							  =					reader.readlines()
							for index, token in enumerate(UpperCAmelCase__       ):
														lowerCamelCase_							  =					token.rstrip("""\n"""       )
														lowerCamelCase_							  =					index
							return vocab





class       __A(				UpperCAmelCase       ):

					def __init__(	self					:     Optional[Any]   ,					__UpperCamelCase					:     Tuple   ,					__UpperCamelCase					:     List[str]="<unk>"   ,					__UpperCamelCase					:     List[str]=2_0_0   ):
												lowerCamelCase_							  =					vocab
												lowerCamelCase_							  =					unk_token
												lowerCamelCase_							  =					max_input_chars_per_word



					def    lowercase__      (	self					:     int   ,					__UpperCamelCase					:     int   ):
												lowerCamelCase_							  =					list(__UpperCamelCase   )
												if len(__UpperCamelCase   ) > self.max_input_chars_per_word:
																			return [self.unk_token]

												lowerCamelCase_							  =					0
												lowerCamelCase_							  =					[]
												while start < len(__UpperCamelCase   ):
																			lowerCamelCase_							  =					len(__UpperCamelCase   )
																			lowerCamelCase_							  =					None
																			while start < end:
																										lowerCamelCase_							  =					"""""".join(chars[start:end]   )
																										if substr in self.vocab:
																																	lowerCamelCase_							  =					substr
																																	break
																										end -= 1
																			if cur_substr is None:
																										sub_tokens.append(self.unk_token   )
																										start += 1
																			else:
																										sub_tokens.append(__UpperCamelCase   )
																										lowerCamelCase_							  =					end

												return sub_tokens





class       __A(				UpperCAmelCase       ):
					SCREAMING_SNAKE_CASE			    =    VOCAB_FILES_NAMES
					SCREAMING_SNAKE_CASE			    =    PRETRAINED_VOCAB_FILES_MAP
					SCREAMING_SNAKE_CASE			    =    PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
					SCREAMING_SNAKE_CASE			    =    ['''input_ids''', '''attention_mask''']
					SCREAMING_SNAKE_CASE			    =    False

					def __init__(	self					:     int   ,					__UpperCamelCase					:     Optional[int]   ,					__UpperCamelCase					:     Optional[int]="<d>"   ,					__UpperCamelCase					:     List[str]="</d>"   ,					__UpperCamelCase					:     Optional[Any]="<s>"   ,					__UpperCamelCase					:     Union[str, Any]="</s>"   ,					__UpperCamelCase					:     List[str]="<pad>"   ,					__UpperCamelCase					:     Union[str, Any]="<unk>"   ,					__UpperCamelCase					:     List[Any]="</n>"   ,					__UpperCamelCase					:     Tuple="</_>"   ,					__UpperCamelCase					:     Optional[Any]="left"   ,					**__UpperCamelCase					:     List[str]   ,					):
												requires_backends(self   ,					["""jieba"""]   )
												super().__init__(
												    bod_token=__UpperCamelCase   ,					eod_token=__UpperCamelCase   ,					bos_token=__UpperCamelCase   ,					eos_token=__UpperCamelCase   ,					pad_token=__UpperCamelCase   ,					unk_token=__UpperCamelCase   ,					line_token=__UpperCamelCase   ,					space_token=__UpperCamelCase   ,					padding_side=__UpperCamelCase   ,					**__UpperCamelCase   ,					)
												lowerCamelCase_							  =					bod_token
												lowerCamelCase_							  =					eod_token
												lowerCamelCase_							  =					load_vocab(__UpperCamelCase   )
												lowerCamelCase_							  =					self.encoder[space_token]
												lowerCamelCase_							  =					self.encoder[line_token]

												del self.encoder[space_token]
												del self.encoder[line_token]

												lowerCamelCase_							  =					collections.OrderedDict(sorted(self.encoder.items()   ,					key=lambda __UpperCamelCase   : x[1]   )   )
												lowerCamelCase_							  =					{v: k for k, v in self.encoder.items()}

												lowerCamelCase_							  =					WordpieceTokenizer(vocab=self.encoder   ,					unk_token=self.unk_token   )

					@property
					def    lowercase__      (	self					:     Any   ):
												return self.encoder[self.bod_token]

					@property
					def    lowercase__      (	self					:     Any   ):
												return self.encoder[self.eod_token]

					@property
					def    lowercase__      (	self					:     int   ):
												return self.encoder["\n"]

					@property
					def    lowercase__      (	self					:     str   ):
												return len(self.encoder   )

					def    lowercase__      (	self					:     Any   ):
												return dict(self.encoder   ,					**self.added_tokens_encoder   )

					def    lowercase__      (	self					:     Any   ,					__UpperCamelCase					:     Optional[Any]   ):
												lowerCamelCase_							  =					[]
												for x in jieba.cut(__UpperCamelCase   ,					cut_all=__UpperCamelCase   ):
																			output_tokens.extend(self.wordpiece_tokenizer.tokenize(__UpperCamelCase   )   )
												return output_tokens

					def    lowercase__      (	self					:     Optional[Any]   ,					__UpperCamelCase					:     Dict   ,					**__UpperCamelCase					:     str   ):
												lowerCamelCase_							  =					[i for i in token_ids if i >= 0]
												lowerCamelCase_							  =					[
												    x for x in token_ids if x != self.pad_token_id and x != self.eos_token_id and x != self.bos_token_id
												]
												return super()._decode(__UpperCamelCase   ,					**__UpperCamelCase   )

					def    lowercase__      (	self					:     Dict   ,					__UpperCamelCase					:     Optional[Any]   ):
												return token in self.encoder

					def    lowercase__      (	self					:     int   ,					__UpperCamelCase					:     List[str]   ):
												return "".join(__UpperCamelCase   )

					def    lowercase__      (	self					:     List[str]   ,					__UpperCamelCase					:     int   ):
												return self.encoder.get(__UpperCamelCase   ,					self.encoder.get(self.unk_token   )   )

					def    lowercase__      (	self					:     Any   ,					__UpperCamelCase					:     Union[str, Any]   ):
												return self.decoder.get(__UpperCamelCase   ,					self.unk_token   )

					def    lowercase__      (	self					:     Union[str, Any]   ,					__UpperCamelCase					:     str   ,					__UpperCamelCase					:     Optional[str] = None   ):
												if os.path.isdir(__UpperCamelCase   ):
																			lowerCamelCase_							  =					os.path.join(
																			    __UpperCamelCase   ,					(filename_prefix + """-""" if filename_prefix else """""") + VOCAB_FILES_NAMES["""vocab_file"""]   )
												else:
																			lowerCamelCase_							  =					(filename_prefix + """-""" if filename_prefix else """""") + save_directory
												lowerCamelCase_							  =					0
												if " " in self.encoder:
																			lowerCamelCase_							  =					self.encoder[""" """]
																			del self.encoder[" "]
												if "\n" in self.encoder:
																			lowerCamelCase_							  =					self.encoder["""\n"""]
																			del self.encoder["\n"]
												lowerCamelCase_							  =					collections.OrderedDict(sorted(self.encoder.items()   ,					key=lambda __UpperCamelCase   : x[1]   )   )
												with open(__UpperCamelCase   ,					"""w"""   ,					encoding="""utf-8"""   ) as writer:
																			for token, token_index in self.encoder.items():
																										if index != token_index:
																																	logger.warning(
																																	    F'''Saving vocabulary to {vocab_file}: vocabulary indices are not consecutive.'''
																																	    """ Please check that the vocabulary is not corrupted!"""   )
																																	lowerCamelCase_							  =					token_index
																										writer.write(token + """\n"""   )
																										index += 1
												return (vocab_file,)

					def    lowercase__      (	self					:     Any   ,					__UpperCamelCase					:     List[int]   ,					__UpperCamelCase					:     List[int] = None   ):
												if token_ids_a is None:
																			return [self.bos_token_id] + token_ids_a
												return [self.bos_token_id] + token_ids_a + [self.bos_token_id] + token_ids_a



					def    lowercase__      (	self					:     int   ,					__UpperCamelCase					:     List[int]   ,					__UpperCamelCase					:     Optional[List[int]] = None   ,					__UpperCamelCase					:     bool = False   ):

												if already_has_special_tokens:
																			return super().get_special_tokens_mask(
																			    token_ids_a=__UpperCamelCase   ,					token_ids_a=__UpperCamelCase   ,					already_has_special_tokens=__UpperCamelCase   )

												if token_ids_a is not None:
																			return [1] + ([0] * len(__UpperCamelCase   )) + [1] + ([0] * len(__UpperCamelCase   ))
												return [1] + ([0] * len(__UpperCamelCase   ))





