



"""simple docstring"""






import os
import unittest

from transformers import RealmTokenizerFast
from transformers.models.bert.tokenization_bert import (
    VOCAB_FILES_NAMES,
    BasicTokenizer,
    WordpieceTokenizer,
    _is_control,
    _is_punctuation,
    _is_whitespace,
)
from transformers.models.realm.tokenization_realm import RealmTokenizer
from transformers.testing_utils import require_tokenizers, slow

from ...test_tokenization_common import TokenizerTesterMixin, filter_non_english

@require_tokenizers
class 	__lowerCAmelCase							(__UpperCamelCase					,unittest.TestCase  ):


					'''simple docstring'''


					a__        =     RealmTokenizer
					a__        =     RealmTokenizerFast
					a__        =     True
					a__        =     True
					a__        =     filter_non_english







					def 		_a (      self   ):




										"""simple docstring"""





										super().setUp()

										snake_case_						:str								=						[
										    "[UNK]",
										    "[CLS]",
										    "[SEP]",
										    "[PAD]",
										    "[MASK]",
										    "want",
										    "##want",
										    "##ed",
										    "wa",
										    "un",
										    "runn",
										    "##ing",
										    ",",
										    "low",
										    "lowest",
										]
										snake_case_						:Optional[Any]								=						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]   )   )







					def 		_a (      self    ,       a   ):




										"""simple docstring"""





										snake_case_						:Dict								=						"UNwant\u00E9d,running"
										snake_case_						:Union[str, Any]								=						"unwanted, running"
										return input_text, output_text







					def 		_a (      self   ):




										"""simple docstring"""





										snake_case_						:int								=						self.tokenizer_class(self.vocab_file   )

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







					def 		_a (      self   ):




										"""simple docstring"""





										if not self.test_rust_tokenizer:
															return

										snake_case_						:Union[str, Any]								=						self.get_tokenizer()
										snake_case_						:Optional[int]								=						self.get_rust_tokenizer()

										snake_case_						:Dict								=						"UNwant\u00E9d,running"

										snake_case_						:str								=						tokenizer.tokenize(a   )
										snake_case_						:Optional[int]								=						rust_tokenizer.tokenize(a   )
										self.assertListEqual(a    ,       a   )

										snake_case_						:Union[str, Any]								=						tokenizer.encode(a    ,       add_special_tokens=a   )
										snake_case_						:Optional[int]								=						rust_tokenizer.encode(a    ,       add_special_tokens=a   )
										self.assertListEqual(a    ,       a   )

										snake_case_						:int								=						self.get_rust_tokenizer()
										snake_case_						:Union[str, Any]								=						tokenizer.encode(a   )
										snake_case_						:str								=						rust_tokenizer.encode(a   )
										self.assertListEqual(a    ,       a   )

										# With lower casing
										snake_case_						:Union[str, Any]								=						self.get_tokenizer(do_lower_case=a   )
										snake_case_						:List[Any]								=						self.get_rust_tokenizer(do_lower_case=a   )

										snake_case_						:str								=						"UNwant\u00E9d,running"

										snake_case_						:Optional[int]								=						tokenizer.tokenize(a   )
										snake_case_						:Optional[int]								=						rust_tokenizer.tokenize(a   )
										self.assertListEqual(a    ,       a   )

										snake_case_						:int								=						tokenizer.encode(a    ,       add_special_tokens=a   )
										snake_case_						:Tuple								=						rust_tokenizer.encode(a    ,       add_special_tokens=a   )
										self.assertListEqual(a    ,       a   )

										snake_case_						:Dict								=						self.get_rust_tokenizer()
										snake_case_						:Optional[Any]								=						tokenizer.encode(a   )
										snake_case_						:Optional[int]								=						rust_tokenizer.encode(a   )
										self.assertListEqual(a    ,       a   )







					def 		_a (      self   ):




										"""simple docstring"""





										snake_case_						:Union[str, Any]								=						BasicTokenizer()

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







					def 		_a (      self   ):




										"""simple docstring"""





										snake_case_						:Union[str, Any]								=						BasicTokenizer(do_lower_case=a   )

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







					def 		_a (      self   ):




										"""simple docstring"""





										snake_case_						:Dict								=						BasicTokenizer(do_lower_case=a    ,       strip_accents=a   )

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







					def 		_a (      self   ):




										"""simple docstring"""





										snake_case_						:str								=						BasicTokenizer(do_lower_case=a    ,       strip_accents=a   )

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







					def 		_a (      self   ):




										"""simple docstring"""





										snake_case_						:Any								=						BasicTokenizer(do_lower_case=a   )

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







					def 		_a (      self   ):




										"""simple docstring"""





										snake_case_						:Any								=						BasicTokenizer(do_lower_case=a   )

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







					def 		_a (      self   ):




										"""simple docstring"""





										snake_case_						:Any								=						BasicTokenizer(do_lower_case=a    ,       strip_accents=a   )

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







					def 		_a (      self   ):




										"""simple docstring"""





										snake_case_						:List[str]								=						BasicTokenizer(do_lower_case=a    ,       strip_accents=a   )

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







					def 		_a (      self   ):




										"""simple docstring"""





										snake_case_						:Optional[Any]								=						BasicTokenizer(do_lower_case=a    ,       never_split=["[UNK]"]   )

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







					def 		_a (      self   ):




										"""simple docstring"""





										snake_case_						:List[str]								=						["[UNK]", "[CLS]", "[SEP]", "want", "##want", "##ed", "wa", "un", "runn", "##ing"]

										snake_case_						:Any								=						{}
										for i, token in enumerate(a   ):
															snake_case_						:Optional[Any]								=						i
										snake_case_						:str								=						WordpieceTokenizer(vocab=a    ,       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 		_a (      self   ):




										"""simple docstring"""





										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 		_a (      self   ):




										"""simple docstring"""





										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 		_a (      self   ):




										"""simple docstring"""





										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 		_a (      self   ):




										"""simple docstring"""





										snake_case_						:List[str]								=						self.get_tokenizer()

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

										if self.test_rust_tokenizer:
															snake_case_						:str								=						self.get_rust_tokenizer()
															self.assertListEqual(
															    [rust_tokenizer.tokenize(a   ) for t in ["Test", "\xad", "test"]]    ,       [["[UNK]"], [], ["[UNK]"]]   )







					@slow
					def 		_a (      self   ):




										"""simple docstring"""





										snake_case_						:Tuple								=						self.tokenizer_class.from_pretrained("bert-base-uncased"   )

										snake_case_						:Union[str, Any]								=						tokenizer.encode("sequence builders"    ,       add_special_tokens=a   )
										snake_case_						:int								=						tokenizer.encode("multi-sequence build"    ,       add_special_tokens=a   )

										snake_case_						:int								=						tokenizer.build_inputs_with_special_tokens(a   )
										snake_case_						:List[Any]								=						tokenizer.build_inputs_with_special_tokens(a    ,       a   )

										assert encoded_sentence == [1_01] + text + [1_02]
										assert encoded_pair == [1_01] + text + [1_02] + text_a + [1_02]







					def 		_a (      self   ):




										"""simple docstring"""





										for tokenizer, pretrained_name, kwargs in self.tokenizers_list:
															with self.subTest(F'''{tokenizer.__class__.__name__} ({pretrained_name})'''   ):
																				snake_case_						:List[Any]								=						self.rust_tokenizer_class.from_pretrained(a    ,       **a   )

																				snake_case_						:Union[str, Any]								=						F'''A, naïve {tokenizer_r.mask_token} AllenNLP sentence.'''
																				snake_case_						:Any								=						tokenizer_r.encode_plus(
																				    a    ,       return_attention_mask=a    ,       return_token_type_ids=a    ,       return_offsets_mapping=a    ,       add_special_tokens=a    ,       )

																				snake_case_						:List[Any]								=						tokenizer_r.do_lower_case if hasattr(a    ,       "do_lower_case"   ) else False
																				snake_case_						:str								=						(
																				    [
																				        ((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"]   )







					@slow
					def 		_a (      self   ):




										"""simple docstring"""





										for tokenizer, pretrained_name, kwargs in self.tokenizers_list:
															with self.subTest(F'''{tokenizer.__class__.__name__} ({pretrained_name})'''   ):
																				snake_case_						:int								=						self.rust_tokenizer_class.from_pretrained(a    ,       **a   )
																				snake_case_						:int								=						self.tokenizer_class.from_pretrained(a    ,       **a   )
																				snake_case_						:int								=						[["Hello world!", "Nice to meet you!"], ["The cute cat.", "The adorable dog."]]

																				snake_case_						:Dict								=						tokenizer_r.batch_encode_candidates(a    ,       max_length=10    ,       return_tensors="np"   )
																				snake_case_						:Tuple								=						tokenizer_p.batch_encode_candidates(a    ,       max_length=10    ,       return_tensors="np"   )

																				snake_case_						:str								=						(2, 2, 10)

																				self.assertEqual(encoded_sentence_r["input_ids"].shape    ,       a   )
																				self.assertEqual(encoded_sentence_r["attention_mask"].shape    ,       a   )
																				self.assertEqual(encoded_sentence_r["token_type_ids"].shape    ,       a   )

																				self.assertEqual(encoded_sentence_p["input_ids"].shape    ,       a   )
																				self.assertEqual(encoded_sentence_p["attention_mask"].shape    ,       a   )
																				self.assertEqual(encoded_sentence_p["token_type_ids"].shape    ,       a   )






"""simple docstring"""






from typing import Any

import numpy as np

class 	__lowerCAmelCase							:


					'''simple docstring'''


					def __init__(      self    ,       a    ,       a   ):




										"""simple docstring"""





										if np.any(tableau[:, -1]    ,       where=tableau[:, -1] < 0   ):
															raise ValueError("RHS must be > 0"   )

										snake_case_						:List[Any]								=						tableau
										snake_case_	,  snake_case_						:Dict								=						tableau.shape

										# Number of decision variables x1, x2, x3...
										snake_case_						:Union[str, Any]								=						n_vars

										# Number of artificial variables to be minimised
										snake_case_						:Tuple								=						len(np.where(tableau[self.n_vars : -1] == -1   )[0]   )

										# 2 if there are >= or == constraints (nonstandard), 1 otherwise (std)
										snake_case_						:List[str]								=						(self.n_art_vars > 0) + 1

										# Number of slack variables added to make inequalities into equalities
										snake_case_						:Optional[int]								=						self.n_rows - self.n_stages

										# Objectives for each stage
										snake_case_						:Union[str, Any]								=						["max"]

										# In two stage simplex, first minimise then maximise
										if self.n_art_vars:
															self.objectives.append("min"   )

										snake_case_						:Dict								=						[""]

										# Index of current pivot row and column
										snake_case_						:List[str]								=						None
										snake_case_						:List[Any]								=						None

										# Does objective row only contain (non)-negative values?
										snake_case_						:Union[str, Any]								=						False







					@staticmethod
					def 		_a (      *a   ):




										"""simple docstring"""





										if len(a   ) != 3:
															raise ValueError("Must provide n_vars, n_slack, and n_art_vars"   )

										if not all(x >= 0 and isinstance(a    ,       a   ) for x in args   ):
															raise ValueError("All arguments must be non-negative integers"   )

										# decision | slack | artificial
										snake_case_						:Tuple								=						["x", "s", "a"]
										snake_case_						:Dict								=						[]
										for i in range(3   ):
															for j in range(args[i]   ):
																				titles.append(string_starts[i] + str(j + 1   )   )
										titles.append("RHS"   )
										return titles







					def 		_a (      self    ,       a   ):




										"""simple docstring"""





										snake_case_						:str								=						self.objectives[-1]

										# Find entries of highest magnitude in objective rows
										snake_case_						:Dict								=						(objective == "min") - (objective == "max")
										snake_case_						:Optional[Any]								=						np.argmax(sign * tableau[0, : self.n_vars]   )

										# Choice is only valid if below 0 for maximise, and above for minimise
										if sign * self.tableau[0, col_idx] <= 0:
															snake_case_						:Dict								=						True
															return 0, 0

										# Pivot row is chosen as having the lowest quotient when elements of
										# the pivot column divide the right-hand side

										# Slice excluding the objective rows
										snake_case_						:str								=						slice(self.n_stages    ,       self.n_rows   )

										# RHS
										snake_case_						:Optional[Any]								=						tableau[s, -1]

										# Elements of pivot column within slice
										snake_case_						:Union[str, Any]								=						tableau[s, col_idx]

										# Array filled with nans
										snake_case_						:Optional[Any]								=						np.full(self.n_rows - self.n_stages    ,       np.nan   )

										# If element in pivot column is greater than zeron_stages, return
										# quotient or nan otherwise
										snake_case_						:Dict								=						np.divide(a    ,       a    ,       out=a    ,       where=divisor > 0   )

										# Arg of minimum quotient excluding the nan values. n_stages is added
										# to compensate for earlier exclusion of objective columns
										snake_case_						:List[Any]								=						np.nanargmin(a   ) + self.n_stages
										return row_idx, col_idx







					def 		_a (      self    ,       a    ,       a    ,       a   ):




										"""simple docstring"""





										snake_case_						:Tuple								=						tableau[row_idx].copy()

										snake_case_						:Any								=						piv_row[col_idx]

										# Entry becomes 1
										piv_row *= 1 / piv_val

										# Variable in pivot column becomes basic, ie the only non-zero entry
										for idx, coeff in enumerate(tableau[:, col_idx]   ):
															tableau[idx] += -coeff * piv_row
										snake_case_						:str								=						piv_row
										return tableau







					def 		_a (      self    ,       a   ):




										"""simple docstring"""





										self.objectives.pop()

										if not self.objectives:
															return tableau

										# Slice containing ids for artificial columns
										snake_case_						:str								=						slice(-self.n_art_vars - 1    ,       -1   )

										# Delete the artificial variable columns
										snake_case_						:Optional[int]								=						np.delete(a    ,       a    ,       axis=1   )

										# Delete the objective row of the first stage
										snake_case_						:List[str]								=						np.delete(a    ,       0    ,       axis=0   )

										snake_case_						:Optional[Any]								=						1
										self.n_rows -= 1
										snake_case_						:List[Any]								=						0
										snake_case_						:Dict								=						False
										return tableau







					def 		_a (      self   ):




										"""simple docstring"""





										for _ in range(1_00   ):
															# Completion of each stage removes an objective. If both stages
															# are complete, then no objectives are left
															if not self.objectives:
																				snake_case_						:str								=						self.generate_col_titles(
																				    self.n_vars    ,       self.n_slack    ,       self.n_art_vars   )

																				# Find the values of each variable at optimal solution
																				return self.interpret_tableau(self.tableau    ,       self.col_titles   )

															snake_case_	,  snake_case_						:Union[str, Any]								=						self.find_pivot(self.tableau   )

															# If there are no more negative values in objective row
															if self.stop_iter:
																				# Delete artificial variable columns and rows. Update attributes
																				snake_case_						:str								=						self.change_stage(self.tableau   )
															else:
																				snake_case_						:str								=						self.pivot(self.tableau    ,       a    ,       a   )
										return {}







					def 		_a (      self    ,       a    ,       a   ):




										"""simple docstring"""





										snake_case_						:Any								=						{"P": abs(tableau[0, -1]   )}

										for i in range(self.n_vars   ):
															# Gives ids of nonzero entries in the ith column
															snake_case_						:Dict								=						np.nonzero(tableau[:, i]   )
															snake_case_						:Tuple								=						len(nonzero[0]   )

															# First entry in the nonzero ids
															snake_case_						:Any								=						nonzero[0][0]
															snake_case_						:int								=						tableau[nonzero_rowidx, i]

															# If there is only one nonzero value in column, which is one
															if n_nonzero == nonzero_val == 1:
																				snake_case_						:Tuple								=						tableau[nonzero_rowidx, -1]
																				snake_case_						:Tuple								=						rhs_val

        # Check for basic variables
										for title in col_titles:
															# Don't add RHS or slack variables to output dict
															if title[0] not in "R-s-a":
																				output_dict.setdefault(a    ,       0   )
										return output_dict


if __name__ == "__main__":
				import doctest

				doctest.testmod()

