






"""simple docstring"""
import os
import unittest

from transformers import MobileBertTokenizer, MobileBertTokenizerFast
from transformers.models.bert.tokenization_bert import (
    VOCAB_FILES_NAMES,
    BasicTokenizer,
    WordpieceTokenizer,
    _is_control,
    _is_punctuation,
    _is_whitespace,
)
from transformers.testing_utils import require_tokenizers, slow

from ...test_tokenization_common import TokenizerTesterMixin, filter_non_english







@require_tokenizers
class     UpperCamelCase_ (__A       ,		unittest.TestCase  ):
	__magic_name__			   =       MobileBertTokenizer
	__magic_name__			   =       MobileBertTokenizerFast
	__magic_name__			   =       True
	__magic_name__			   =       True
	__magic_name__			   =       filter_non_english
	__magic_name__			   =       '''google/mobilebert-uncased'''





	def   _SCREAMING_SNAKE_CASE   (   self      :				Optional[int]		)		->    Optional[Any]:
				super().setUp()

				UpperCAmelCase_  :				Dict      =      [
				    "[UNK]",
				    "[CLS]",
				    "[SEP]",
				    "[PAD]",
				    "[MASK]",
				    "want",
				    "##want",
				    "##ed",
				    "wa",
				    "un",
				    "runn",
				    "##ing",
				    ",",
				    "low",
				    "lowest",
				]
				UpperCAmelCase_  :				Optional[int]      =      os.path.join(self.tmpdirname			,			VOCAB_FILES_NAMES["vocab_file"]		)
				with open(self.vocab_file			,			"w"			,			encoding="utf-8"		) as vocab_writer:
							vocab_writer.write("".join([x + "\n" for x in vocab_tokens]		)		)

				UpperCAmelCase_  :				Any      =      [
				    (tokenizer_def[0], self.pre_trained_model_path, tokenizer_def[2])  # else the 'google/' prefix is stripped
				    for tokenizer_def in self.tokenizers_list
				]





	def   _SCREAMING_SNAKE_CASE   (   self      :				Any			,			lowerCAmelCase_      :				Dict		)		->    Optional[Any]:
				UpperCAmelCase_  :				List[Any]      =      "UNwant\u00E9d,running"
				UpperCAmelCase_  :				int      =      "unwanted, running"
				return input_text, output_text





	def   _SCREAMING_SNAKE_CASE   (   self      :				Dict		)		->    Union[str, Any]:
				UpperCAmelCase_  :				Optional[Any]      =      self.tokenizer_class(self.vocab_file		)

				UpperCAmelCase_  :				Any      =      tokenizer.tokenize("UNwant\u00E9d,running"		)
				self.assertListEqual(lowerCAmelCase_			,			["un", "##want", "##ed", ",", "runn", "##ing"]		)
				self.assertListEqual(tokenizer.convert_tokens_to_ids(lowerCAmelCase_		)			,			[9, 6, 7, 12, 10, 11]		)





	def   _SCREAMING_SNAKE_CASE   (   self      :				int		)		->    str:
				if not self.test_rust_tokenizer:
							return

				UpperCAmelCase_  :				List[str]      =      self.get_tokenizer()
				UpperCAmelCase_  :				List[Any]      =      self.get_rust_tokenizer()

				UpperCAmelCase_  :				List[str]      =      "UNwant\u00E9d,running"

				UpperCAmelCase_  :				str      =      tokenizer.tokenize(lowerCAmelCase_		)
				UpperCAmelCase_  :				Tuple      =      rust_tokenizer.tokenize(lowerCAmelCase_		)
				self.assertListEqual(lowerCAmelCase_			,			lowerCAmelCase_		)

				UpperCAmelCase_  :				Optional[int]      =      tokenizer.encode(lowerCAmelCase_			,			add_special_tokens=lowerCAmelCase_		)
				UpperCAmelCase_  :				Any      =      rust_tokenizer.encode(lowerCAmelCase_			,			add_special_tokens=lowerCAmelCase_		)
				self.assertListEqual(lowerCAmelCase_			,			lowerCAmelCase_		)

				UpperCAmelCase_  :				List[str]      =      self.get_rust_tokenizer()
				UpperCAmelCase_  :				int      =      tokenizer.encode(lowerCAmelCase_		)
				UpperCAmelCase_  :				Dict      =      rust_tokenizer.encode(lowerCAmelCase_		)
				self.assertListEqual(lowerCAmelCase_			,			lowerCAmelCase_		)

				# With lower casing
				UpperCAmelCase_  :				Union[str, Any]      =      self.get_tokenizer(do_lower_case=lowerCAmelCase_		)
				UpperCAmelCase_  :				Optional[Any]      =      self.get_rust_tokenizer(do_lower_case=lowerCAmelCase_		)

				UpperCAmelCase_  :				Tuple      =      "UNwant\u00E9d,running"

				UpperCAmelCase_  :				List[Any]      =      tokenizer.tokenize(lowerCAmelCase_		)
				UpperCAmelCase_  :				int      =      rust_tokenizer.tokenize(lowerCAmelCase_		)
				self.assertListEqual(lowerCAmelCase_			,			lowerCAmelCase_		)

				UpperCAmelCase_  :				int      =      tokenizer.encode(lowerCAmelCase_			,			add_special_tokens=lowerCAmelCase_		)
				UpperCAmelCase_  :				str      =      rust_tokenizer.encode(lowerCAmelCase_			,			add_special_tokens=lowerCAmelCase_		)
				self.assertListEqual(lowerCAmelCase_			,			lowerCAmelCase_		)

				UpperCAmelCase_  :				Dict      =      self.get_rust_tokenizer()
				UpperCAmelCase_  :				Tuple      =      tokenizer.encode(lowerCAmelCase_		)
				UpperCAmelCase_  :				Optional[int]      =      rust_tokenizer.encode(lowerCAmelCase_		)
				self.assertListEqual(lowerCAmelCase_			,			lowerCAmelCase_		)





	def   _SCREAMING_SNAKE_CASE   (   self      :				Optional[Any]		)		->    Union[str, Any]:
				UpperCAmelCase_  :				int      =      BasicTokenizer()

				self.assertListEqual(tokenizer.tokenize("ah\u535A\u63A8zz"		)			,			["ah", "\u535A", "\u63A8", "zz"]		)





	def   _SCREAMING_SNAKE_CASE   (   self      :				Optional[Any]		)		->    Union[str, Any]:
				UpperCAmelCase_  :				Tuple      =      BasicTokenizer(do_lower_case=lowerCAmelCase_		)

				self.assertListEqual(
				    tokenizer.tokenize(" \tHeLLo!how  \n Are yoU?  "		)			,			["hello", "!", "how", "are", "you", "?"]		)
				self.assertListEqual(tokenizer.tokenize("H\u00E9llo"		)			,			["hello"]		)





	def   _SCREAMING_SNAKE_CASE   (   self      :				Optional[int]		)		->    List[str]:
				UpperCAmelCase_  :				Any      =      BasicTokenizer(do_lower_case=lowerCAmelCase_			,			strip_accents=lowerCAmelCase_		)

				self.assertListEqual(
				    tokenizer.tokenize(" \tHäLLo!how  \n Are yoU?  "		)			,			["hällo", "!", "how", "are", "you", "?"]		)
				self.assertListEqual(tokenizer.tokenize("H\u00E9llo"		)			,			["h\u00E9llo"]		)





	def   _SCREAMING_SNAKE_CASE   (   self      :				Union[str, Any]		)		->    Optional[Any]:
				UpperCAmelCase_  :				Union[str, Any]      =      BasicTokenizer(do_lower_case=lowerCAmelCase_			,			strip_accents=lowerCAmelCase_		)

				self.assertListEqual(
				    tokenizer.tokenize(" \tHäLLo!how  \n Are yoU?  "		)			,			["hallo", "!", "how", "are", "you", "?"]		)
				self.assertListEqual(tokenizer.tokenize("H\u00E9llo"		)			,			["hello"]		)





	def   _SCREAMING_SNAKE_CASE   (   self      :				Optional[Any]		)		->    List[str]:
				UpperCAmelCase_  :				List[str]      =      BasicTokenizer(do_lower_case=lowerCAmelCase_		)

				self.assertListEqual(
				    tokenizer.tokenize(" \tHäLLo!how  \n Are yoU?  "		)			,			["hallo", "!", "how", "are", "you", "?"]		)
				self.assertListEqual(tokenizer.tokenize("H\u00E9llo"		)			,			["hello"]		)





	def   _SCREAMING_SNAKE_CASE   (   self      :				Optional[Any]		)		->    List[str]:
				UpperCAmelCase_  :				Union[str, Any]      =      BasicTokenizer(do_lower_case=lowerCAmelCase_		)

				self.assertListEqual(
				    tokenizer.tokenize(" \tHeLLo!how  \n Are yoU?  "		)			,			["HeLLo", "!", "how", "Are", "yoU", "?"]		)





	def   _SCREAMING_SNAKE_CASE   (   self      :				Tuple		)		->    str:
				UpperCAmelCase_  :				str      =      BasicTokenizer(do_lower_case=lowerCAmelCase_			,			strip_accents=lowerCAmelCase_		)

				self.assertListEqual(
				    tokenizer.tokenize(" \tHäLLo!how  \n Are yoU?  "		)			,			["HäLLo", "!", "how", "Are", "yoU", "?"]		)





	def   _SCREAMING_SNAKE_CASE   (   self      :				Dict		)		->    List[str]:
				UpperCAmelCase_  :				Dict      =      BasicTokenizer(do_lower_case=lowerCAmelCase_			,			strip_accents=lowerCAmelCase_		)

				self.assertListEqual(
				    tokenizer.tokenize(" \tHäLLo!how  \n Are yoU?  "		)			,			["HaLLo", "!", "how", "Are", "yoU", "?"]		)





	def   _SCREAMING_SNAKE_CASE   (   self      :				Any		)		->    Optional[int]:
				UpperCAmelCase_  :				Any      =      BasicTokenizer(do_lower_case=lowerCAmelCase_			,			never_split=["[UNK]"]		)

				self.assertListEqual(
				    tokenizer.tokenize(" \tHeLLo!how  \n Are yoU? [UNK]"		)			,			["HeLLo", "!", "how", "Are", "yoU", "?", "[UNK]"]		)





	def   _SCREAMING_SNAKE_CASE   (   self      :				Any		)		->    Optional[Any]:
				UpperCAmelCase_  :				Any      =      ["[UNK]", "[CLS]", "[SEP]", "want", "##want", "##ed", "wa", "un", "runn", "##ing"]

				UpperCAmelCase_  :				Optional[Any]      =      {}
				for i, token in enumerate(lowerCAmelCase_		):
							UpperCAmelCase_  :				List[Any]      =      i
				UpperCAmelCase_  :				str      =      WordpieceTokenizer(vocab=lowerCAmelCase_			,			unk_token="[UNK]"		)

				self.assertListEqual(tokenizer.tokenize(""		)			,			[]		)

				self.assertListEqual(tokenizer.tokenize("unwanted running"		)			,			["un", "##want", "##ed", "runn", "##ing"]		)

				self.assertListEqual(tokenizer.tokenize("unwantedX running"		)			,			["[UNK]", "runn", "##ing"]		)





	def   _SCREAMING_SNAKE_CASE   (   self      :				int		)		->    Tuple:
				self.assertTrue(_is_whitespace(" "		)		)
				self.assertTrue(_is_whitespace("\t"		)		)
				self.assertTrue(_is_whitespace("\r"		)		)
				self.assertTrue(_is_whitespace("\n"		)		)
				self.assertTrue(_is_whitespace("\u00A0"		)		)

				self.assertFalse(_is_whitespace("A"		)		)
				self.assertFalse(_is_whitespace("-"		)		)





	def   _SCREAMING_SNAKE_CASE   (   self      :				List[Any]		)		->    List[str]:
				self.assertTrue(_is_control("\u0005"		)		)

				self.assertFalse(_is_control("A"		)		)
				self.assertFalse(_is_control(" "		)		)
				self.assertFalse(_is_control("\t"		)		)
				self.assertFalse(_is_control("\r"		)		)





	def   _SCREAMING_SNAKE_CASE   (   self      :				Any		)		->    Optional[Any]:
				self.assertTrue(_is_punctuation("-"		)		)
				self.assertTrue(_is_punctuation("$"		)		)
				self.assertTrue(_is_punctuation("`"		)		)
				self.assertTrue(_is_punctuation("."		)		)

				self.assertFalse(_is_punctuation("A"		)		)
				self.assertFalse(_is_punctuation(" "		)		)





	def   _SCREAMING_SNAKE_CASE   (   self      :				List[Any]		)		->    Optional[Any]:
				UpperCAmelCase_  :				List[Any]      =      self.get_tokenizer()
				UpperCAmelCase_  :				Dict      =      self.get_rust_tokenizer()

				# Example taken from the issue https://github.com/huggingface/tokenizers/issues/340
				self.assertListEqual([tokenizer.tokenize(lowerCAmelCase_		) for t in ["Test", "\xad", "test"]]			,			[["[UNK]"], [], ["[UNK]"]]		)

				self.assertListEqual(
				    [rust_tokenizer.tokenize(lowerCAmelCase_		) for t in ["Test", "\xad", "test"]]			,			[["[UNK]"], [], ["[UNK]"]]		)





	@slow
	def   _SCREAMING_SNAKE_CASE   (   self      :				Union[str, Any]		)		->    Optional[Any]:
				UpperCAmelCase_  :				int      =      self.tokenizer_class.from_pretrained("google/mobilebert-uncased"		)

				UpperCAmelCase_  :				Optional[Any]      =      tokenizer.encode("sequence builders"			,			add_special_tokens=lowerCAmelCase_		)
				UpperCAmelCase_  :				Tuple      =      tokenizer.encode("multi-sequence build"			,			add_special_tokens=lowerCAmelCase_		)

				UpperCAmelCase_  :				int      =      tokenizer.build_inputs_with_special_tokens(lowerCAmelCase_		)
				UpperCAmelCase_  :				Optional[Any]      =      tokenizer.build_inputs_with_special_tokens(lowerCAmelCase_			,			lowerCAmelCase_		)

				assert encoded_sentence == [101] + text + [102]
				assert encoded_pair == [101] + text + [102] + text_a + [102]





	def   _SCREAMING_SNAKE_CASE   (   self      :				Dict		)		->    List[Any]:
				for tokenizer, pretrained_name, kwargs in self.tokenizers_list:
							with self.subTest(f"""{tokenizer.__class__.__name__} ({pretrained_name})"""		):
										UpperCAmelCase_  :				Optional[int]      =      self.rust_tokenizer_class.from_pretrained(lowerCAmelCase_			,			**lowerCAmelCase_		)

										UpperCAmelCase_  :				List[Any]      =      f"""A, naïve {tokenizer_r.mask_token} AllenNLP sentence."""
										UpperCAmelCase_  :				int      =      tokenizer_r.encode_plus(
										    lowerCAmelCase_			,			return_attention_mask=lowerCAmelCase_			,			return_token_type_ids=lowerCAmelCase_			,			return_offsets_mapping=lowerCAmelCase_			,			add_special_tokens=lowerCAmelCase_			,			)

										UpperCAmelCase_  :				List[Any]      =      tokenizer_r.do_lower_case if hasattr(lowerCAmelCase_			,			"do_lower_case"		) else False
										UpperCAmelCase_  :				Tuple      =      (
										    [
										        ((0, 0), tokenizer_r.cls_token),
										        ((0, 1), "A"),
										        ((1, 2), ","),
										        ((3, 5), "na"),
										        ((5, 6), "##ï"),
										        ((6, 8), "##ve"),
										        ((9, 15), tokenizer_r.mask_token),
										        ((16, 21), "Allen"),
										        ((21, 23), "##NL"),
										        ((23, 24), "##P"),
										        ((25, 33), "sentence"),
										        ((33, 34), "."),
										        ((0, 0), tokenizer_r.sep_token),
										    ]
										    if not do_lower_case
										    else [
										        ((0, 0), tokenizer_r.cls_token),
										        ((0, 1), "a"),
										        ((1, 2), ","),
										        ((3, 8), "naive"),
										        ((9, 15), tokenizer_r.mask_token),
										        ((16, 21), "allen"),
										        ((21, 23), "##nl"),
										        ((23, 24), "##p"),
										        ((25, 33), "sentence"),
										        ((33, 34), "."),
										        ((0, 0), tokenizer_r.sep_token),
										    ]
										)

										self.assertEqual(
										    [e[1] for e in expected_results]			,			tokenizer_r.convert_ids_to_tokens(tokens["input_ids"]		)		)
										self.assertEqual([e[0] for e in expected_results]			,			tokens["offset_mapping"]		)





	def   _SCREAMING_SNAKE_CASE   (   self      :				Optional[int]		)		->    str:
				UpperCAmelCase_  :				int      =      ["的", "人", "有"]
				UpperCAmelCase_  :				Union[str, Any]      =      "".join(lowerCAmelCase_		)
				for tokenizer, pretrained_name, kwargs in self.tokenizers_list:
							with self.subTest(f"""{tokenizer.__class__.__name__} ({pretrained_name})"""		):
										UpperCAmelCase_  :				List[Any]      =      True
										UpperCAmelCase_  :				List[str]      =      self.tokenizer_class.from_pretrained(lowerCAmelCase_			,			**lowerCAmelCase_		)
										UpperCAmelCase_  :				Optional[int]      =      self.rust_tokenizer_class.from_pretrained(lowerCAmelCase_			,			**lowerCAmelCase_		)

										UpperCAmelCase_  :				Dict      =      tokenizer_p.encode(lowerCAmelCase_			,			add_special_tokens=lowerCAmelCase_		)
										UpperCAmelCase_  :				Tuple      =      tokenizer_r.encode(lowerCAmelCase_			,			add_special_tokens=lowerCAmelCase_		)

										UpperCAmelCase_  :				Union[str, Any]      =      tokenizer_r.convert_ids_to_tokens(lowerCAmelCase_		)
										UpperCAmelCase_  :				Optional[Any]      =      tokenizer_p.convert_ids_to_tokens(lowerCAmelCase_		)

										# it is expected that each Chinese character is not preceded by "##"
										self.assertListEqual(lowerCAmelCase_			,			lowerCAmelCase_		)
										self.assertListEqual(lowerCAmelCase_			,			lowerCAmelCase_		)

										UpperCAmelCase_  :				Tuple      =      False
										UpperCAmelCase_  :				Optional[int]      =      self.rust_tokenizer_class.from_pretrained(lowerCAmelCase_			,			**lowerCAmelCase_		)
										UpperCAmelCase_  :				Tuple      =      self.tokenizer_class.from_pretrained(lowerCAmelCase_			,			**lowerCAmelCase_		)

										UpperCAmelCase_  :				Dict      =      tokenizer_r.encode(lowerCAmelCase_			,			add_special_tokens=lowerCAmelCase_		)
										UpperCAmelCase_  :				Optional[int]      =      tokenizer_p.encode(lowerCAmelCase_			,			add_special_tokens=lowerCAmelCase_		)

										UpperCAmelCase_  :				Union[str, Any]      =      tokenizer_r.convert_ids_to_tokens(lowerCAmelCase_		)
										UpperCAmelCase_  :				int      =      tokenizer_p.convert_ids_to_tokens(lowerCAmelCase_		)

										# it is expected that only the first Chinese character is not preceded by "##".
										UpperCAmelCase_  :				Any      =      [
										    f"""##{token}""" if idx != 0 else token for idx, token in enumerate(lowerCAmelCase_		)
										]
										self.assertListEqual(lowerCAmelCase_			,			lowerCAmelCase_		)
										self.assertListEqual(lowerCAmelCase_			,			lowerCAmelCase_		)











"""simple docstring"""
import numpy as np
from numpy import ndarray
from scipy.optimize import Bounds, LinearConstraint, minimize

def        snake_case   (     A__		):
			return np.dot(A__			,A__		)







class     UpperCamelCase_ :





	def __init__(   self      :				int			,			*,
	    lowerCAmelCase_      :				float = np.inf			,			lowerCAmelCase_      :				str = "linear"			,			lowerCAmelCase_      :				float = 0.0			,			)		->    None:
				UpperCAmelCase_  :				List[str]      =      regularization
				UpperCAmelCase_  :				Tuple      =      gamma
				if kernel == "linear":
							UpperCAmelCase_  :				List[Any]      =      self.__linear
				elif kernel == "rbf":
							if self.gamma == 0:
										raise ValueError("rbf kernel requires gamma"		)
							if not isinstance(self.gamma			,			(float, int)		):
										raise ValueError("gamma must be float or int"		)
							if not self.gamma > 0:
										raise ValueError("gamma must be > 0"		)
							UpperCAmelCase_  :				Union[str, Any]      =      self.__rbf
							# in the future, there could be a default value like in sklearn
							# sklear: def_gamma = 1/(n_features * X.var()) (wiki)
							# previously it was 1/(n_features)
				else:
							UpperCAmelCase_  :				Tuple      =      f"""Unknown kernel: {kernel}"""
							raise ValueError(lowerCAmelCase_		)





	def   _SCREAMING_SNAKE_CASE   (   self      :				Tuple			,			lowerCAmelCase_      :				ndarray			,			lowerCAmelCase_      :				ndarray		)		->    float:
				return np.dot(lowerCAmelCase_			,			lowerCAmelCase_		)





	def   _SCREAMING_SNAKE_CASE   (   self      :				Union[str, Any]			,			lowerCAmelCase_      :				ndarray			,			lowerCAmelCase_      :				ndarray		)		->    float:
				return np.exp(-(self.gamma * norm_squared(vectora - vectora		))		)





	def   _SCREAMING_SNAKE_CASE   (   self      :				Dict			,			lowerCAmelCase_      :				list[ndarray]			,			lowerCAmelCase_      :				ndarray		)		->    None:
				UpperCAmelCase_  :				int      =      observations
				UpperCAmelCase_  :				Optional[Any]      =      classes

				# using Wolfe's Dual to calculate w.
				# Primal problem: minimize 1/2*norm_squared(w)
				#   constraint: yn(w . xn + b) >= 1
				#
				# With l a vector
				# Dual problem: maximize sum_n(ln) -
				#       1/2 * sum_n(sum_m(ln*lm*yn*ym*xn . xm))
				#   constraint: self.C >= ln >= 0
				#           and sum_n(ln*yn) = 0
				# Then we get w using w = sum_n(ln*yn*xn)
				# At the end we can get b ~= mean(yn - w . xn)
				#
				# Since we use kernels, we only need l_star to calculate b
				# and to classify observations

				((UpperCAmelCase_)  ,			)  :				Optional[int]      =      np.shape(lowerCAmelCase_		)

				def to_minimize(lowerCAmelCase_      :				ndarray		) -> float:
							UpperCAmelCase_  :				int      =      0
							((UpperCAmelCase_)  ,			)  :				str      =      np.shape(lowerCAmelCase_		)
							for i in range(lowerCAmelCase_		):
										for j in range(lowerCAmelCase_		):
													s += (
													    candidate[i]
													    * candidate[j]
													    * classes[i]
													    * classes[j]
													    * self.kernel(observations[i]			,			observations[j]		)
													)
							return 1 / 2 * s - sum(lowerCAmelCase_		)

				UpperCAmelCase_  :				int      =      LinearConstraint(lowerCAmelCase_			,			0			,			0		)
				UpperCAmelCase_  :				Dict      =      Bounds(0			,			self.regularization		)

				UpperCAmelCase_  :				Optional[Any]      =      minimize(
				    lowerCAmelCase_			,			np.ones(lowerCAmelCase_		)			,			bounds=lowerCAmelCase_			,			constraints=[ly_contraint]		).x
				UpperCAmelCase_  :				Optional[Any]      =      l_star

				# calculating mean offset of separation plane to points
				UpperCAmelCase_  :				Optional[int]      =      0
				for i in range(lowerCAmelCase_		):
							for j in range(lowerCAmelCase_		):
										s += classes[i] - classes[i] * self.optimum[i] * self.kernel(
										    observations[i]			,			observations[j]		)
				UpperCAmelCase_  :				str      =      s / n





	def   _SCREAMING_SNAKE_CASE   (   self      :				List[Any]			,			lowerCAmelCase_      :				ndarray		)		->    int:
				UpperCAmelCase_  :				List[Any]      =      sum(
				    self.optimum[n]
				    * self.classes[n]
				    * self.kernel(self.observations[n]			,			lowerCAmelCase_		)
				    for n in range(len(self.classes		)		)		)
				return 1 if s + self.offset >= 0 else -1


if __name__ == "__main__":
			import doctest

			doctest.testmod()



