




import itertools
import json
import os
import unittest

from transformers import AddedToken, LongformerTokenizer, LongformerTokenizerFast
from transformers.models.longformer.tokenization_longformer import VOCAB_FILES_NAMES
from transformers.testing_utils import require_tokenizers, slow

from ...test_tokenization_common import TokenizerTesterMixin

@require_tokenizers
class 		__lowerCAmelCase	(	__magic_name__      ,       unittest.TestCase ):
							UpperCamelCase__					     =  LongformerTokenizer
							UpperCamelCase__					     =  True
							UpperCamelCase__					     =  LongformerTokenizerFast
							UpperCamelCase__					     =  True
							def       lowerCamelCase__							(						self						:Dict				):







								'''simple docstring'''







								super().setUp()

								# Adapted from Sennrich et al. 2015 and https://github.com/rsennrich/subword-nmt
								a										=							[
								    """l""",
								    """o""",
								    """w""",
								    """e""",
								    """r""",
								    """s""",
								    """t""",
								    """i""",
								    """d""",
								    """n""",
								    """\u0120""",
								    """\u0120l""",
								    """\u0120n""",
								    """\u0120lo""",
								    """\u0120low""",
								    """er""",
								    """\u0120lowest""",
								    """\u0120newer""",
								    """\u0120wider""",
								    """<unk>""",
								]
								a										=							dict(zip(__magic_name__		,      range(len(__magic_name__				)				)				)				)
								a										=							["""#version: 0.2""", """\u0120 l""", """\u0120l o""", """\u0120lo w""", """e r""", """"""]
								a										=							{"""unk_token""": """<unk>"""}

								a										=							os.path.join(self.tmpdirname		,      VOCAB_FILES_NAMES["""vocab_file"""]				)
								a										=							os.path.join(self.tmpdirname		,      VOCAB_FILES_NAMES["""merges_file"""]				)
								with open(self.vocab_file		,      """w"""		,      encoding="""utf-8"""				) as fp:
									fp.write(json.dumps(__magic_name__				) + """\n"""				)
								with open(self.merges_file		,      """w"""		,      encoding="""utf-8"""				) as fp:
									fp.write("""\n""".join(__magic_name__				)				)
							def       lowerCamelCase__							(						self						:Tuple		,      **__magic_name__						:Any				):







								'''simple docstring'''







								kwargs.update(self.special_tokens_map				)
								return self.tokenizer_class.from_pretrained(self.tmpdirname		,      **__magic_name__				)
							def       lowerCamelCase__							(						self						:List[Any]		,      **__magic_name__						:Union[str, Any]				):







								'''simple docstring'''







								kwargs.update(self.special_tokens_map				)
								return self.rust_tokenizer_class.from_pretrained(self.tmpdirname		,      **__magic_name__				)
							def       lowerCamelCase__							(						self						:Tuple		,      __magic_name__						:List[Any]				):







								'''simple docstring'''







								a										=							"""lower newer"""
								a										=							"""lower newer"""
								return input_text, output_text
							def       lowerCamelCase__							(						self						:Any				):







								'''simple docstring'''







								a										=							self.tokenizer_class(self.vocab_file		,      self.merges_file		,      **self.special_tokens_map				)
								a										=							"""lower newer"""
								a										=							["""l""", """o""", """w""", """er""", """\u0120""", """n""", """e""", """w""", """er"""]
								a										=							tokenizer.tokenize(__magic_name__				)  # , add_prefix_space=True)
								self.assertListEqual(__magic_name__		,      __magic_name__				)

								a										=							tokens + [tokenizer.unk_token]
								a										=							[0, 1, 2, 15, 10, 9, 3, 2, 15, 19]
								self.assertListEqual(tokenizer.convert_tokens_to_ids(__magic_name__				)		,      __magic_name__				)
							def       lowerCamelCase__							(						self						:Optional[int]				):







								'''simple docstring'''







								a										=							self.get_tokenizer()

								self.assertListEqual(tokenizer.encode("""Hello world!"""		,      add_special_tokens=__magic_name__				)		,      [0, 3_1414, 232, 328, 2]				)
								self.assertListEqual(
								    tokenizer.encode("""Hello world! cécé herlolip 418"""		,      add_special_tokens=__magic_name__				)		,      [0, 3_1414, 232, 328, 740, 1140, 1_2695, 69, 4_6078, 1588, 2]		,      )
							@slow
							def       lowerCamelCase__							(						self						:List[Any]				):







								'''simple docstring'''







								a										=							self.tokenizer_class.from_pretrained("""allenai/longformer-base-4096"""				)

								a										=							tokenizer.encode("""sequence builders"""		,      add_special_tokens=__magic_name__				)
								a										=							tokenizer.encode("""multi-sequence build"""		,      add_special_tokens=__magic_name__				)

								a										=							tokenizer.encode(
								    """sequence builders"""		,      add_special_tokens=__magic_name__		,      add_prefix_space=__magic_name__				)
								a										=							tokenizer.encode(
								    """sequence builders"""		,      """multi-sequence build"""		,      add_special_tokens=__magic_name__		,      add_prefix_space=__magic_name__				)

								a										=							tokenizer.build_inputs_with_special_tokens(__magic_name__				)
								a										=							tokenizer.build_inputs_with_special_tokens(__magic_name__		,      __magic_name__				)

								assert encoded_sentence == encoded_text_from_decode
								assert encoded_pair == encoded_pair_from_decode
							def       lowerCamelCase__							(						self						:List[str]				):







								'''simple docstring'''







								a										=							self.get_tokenizer()

								a										=							"""Encode this sequence."""
								a										=							tokenizer.byte_encoder[""" """.encode("""utf-8"""				)[0]]

								# Testing encoder arguments
								a										=							tokenizer.encode(__magic_name__		,      add_special_tokens=__magic_name__		,      add_prefix_space=__magic_name__				)
								a										=							tokenizer.convert_ids_to_tokens(encoded[0]				)[0]
								self.assertNotEqual(__magic_name__		,      __magic_name__				)

								a										=							tokenizer.encode(__magic_name__		,      add_special_tokens=__magic_name__		,      add_prefix_space=__magic_name__				)
								a										=							tokenizer.convert_ids_to_tokens(encoded[0]				)[0]
								self.assertEqual(__magic_name__		,      __magic_name__				)

								tokenizer.add_special_tokens({"""bos_token""": """<s>"""}				)
								a										=							tokenizer.encode(__magic_name__		,      add_special_tokens=__magic_name__				)
								a										=							tokenizer.convert_ids_to_tokens(encoded[1]				)[0]
								self.assertNotEqual(__magic_name__		,      __magic_name__				)

								# Testing spaces after special tokens
								a										=							"""<mask>"""
								tokenizer.add_special_tokens(
								    {"""mask_token""": AddedToken(__magic_name__		,      lstrip=__magic_name__		,      rstrip=__magic_name__				)}				)  # mask token has a left space
								a										=							tokenizer.convert_tokens_to_ids(__magic_name__				)

								a										=							"""Encode <mask> sequence"""
								a										=							"""Encode <mask>sequence"""

								a										=							tokenizer.encode(__magic_name__				)
								a										=							encoded.index(__magic_name__				)
								a										=							tokenizer.convert_ids_to_tokens(encoded[mask_loc + 1]				)[0]
								self.assertEqual(__magic_name__		,      __magic_name__				)

								a										=							tokenizer.encode(__magic_name__				)
								a										=							encoded.index(__magic_name__				)
								a										=							tokenizer.convert_ids_to_tokens(encoded[mask_loc + 1]				)[0]
								self.assertNotEqual(__magic_name__		,      __magic_name__				)
							def       lowerCamelCase__							(						self						:Any				):







								'''simple docstring'''







								pass
							def       lowerCamelCase__							(						self						:List[str]				):







								'''simple docstring'''







								for tokenizer, pretrained_name, kwargs in self.tokenizers_list:
									with self.subTest(F'{tokenizer.__class__.__name__} ({pretrained_name})'				):
										a										=							self.rust_tokenizer_class.from_pretrained(__magic_name__		,      **__magic_name__				)
										a										=							self.tokenizer_class.from_pretrained(__magic_name__		,      **__magic_name__				)
										a										=							"""A, <mask> AllenNLP sentence."""
										a										=							tokenizer_r.encode_plus(__magic_name__		,      add_special_tokens=__magic_name__		,      return_token_type_ids=__magic_name__				)
										a										=							tokenizer_p.encode_plus(__magic_name__		,      add_special_tokens=__magic_name__		,      return_token_type_ids=__magic_name__				)

										# token_type_ids should put 0 everywhere
										self.assertEqual(sum(tokens_r["""token_type_ids"""]				)		,      sum(tokens_p["""token_type_ids"""]				)				)

										# attention_mask should put 1 everywhere, so sum over length should be 1
										self.assertEqual(
										    sum(tokens_r["""attention_mask"""]				) / len(tokens_r["""attention_mask"""]				)		,      sum(tokens_p["""attention_mask"""]				) / len(tokens_p["""attention_mask"""]				)		,      )

										a										=							tokenizer_r.convert_ids_to_tokens(tokens_r["""input_ids"""]				)
										a										=							tokenizer_p.convert_ids_to_tokens(tokens_p["""input_ids"""]				)

										# Rust correctly handles the space before the mask while python doesnt
										self.assertSequenceEqual(tokens_p["""input_ids"""]		,      [0, 250, 6, 5_0264, 3823, 487, 2_1992, 3645, 4, 2]				)
										self.assertSequenceEqual(tokens_r["""input_ids"""]		,      [0, 250, 6, 5_0264, 3823, 487, 2_1992, 3645, 4, 2]				)

										self.assertSequenceEqual(
										    __magic_name__		,      ["""<s>""", """A""", """,""", """<mask>""", """ĠAllen""", """N""", """LP""", """Ġsentence""", """.""", """</s>"""]				)
										self.assertSequenceEqual(
										    __magic_name__		,      ["""<s>""", """A""", """,""", """<mask>""", """ĠAllen""", """N""", """LP""", """Ġsentence""", """.""", """</s>"""]				)
							def       lowerCamelCase__							(						self						:str				):







								'''simple docstring'''







								for trim_offsets, add_prefix_space in itertools.product([True, False]		,      repeat=2				):
									a										=							self.rust_tokenizer_class.from_pretrained(
									    self.tmpdirname		,      use_fast=__magic_name__		,      add_prefix_space=__magic_name__		,      trim_offsets=__magic_name__				)

									a										=							json.loads(tokenizer_r.backend_tokenizer.pre_tokenizer.__getstate__()				)
									a										=							json.loads(tokenizer_r.backend_tokenizer.post_processor.__getstate__()				)

									self.assertEqual(pre_tokenizer_state["""add_prefix_space"""]		,      __magic_name__				)

									self.assertEqual(post_processor_state["""add_prefix_space"""]		,      __magic_name__				)
									self.assertEqual(post_processor_state["""trim_offsets"""]		,      __magic_name__				)





							def       lowerCamelCase__							(						self						:Any				):







								'''simple docstring'''







								for tokenizer, pretrained_name, kwargs in self.tokenizers_list:
									with self.subTest(F'{tokenizer.__class__.__name__} ({pretrained_name})'				):
										a										=							"""hello"""  # `hello` is a token in the vocabulary of `pretrained_name`
										a										=							F'{text_of_1_token} {text_of_1_token}'

										a										=							self.rust_tokenizer_class.from_pretrained(
										    __magic_name__		,      use_fast=__magic_name__		,      add_prefix_space=__magic_name__		,      trim_offsets=__magic_name__				)
										a										=							tokenizer_r(__magic_name__		,      return_offsets_mapping=__magic_name__		,      add_special_tokens=__magic_name__				)
										self.assertEqual(encoding.offset_mapping[0]		,      (0, len(__magic_name__				))				)
										self.assertEqual(
										    encoding.offset_mapping[1]		,      (len(__magic_name__				) + 1, len(__magic_name__				) + 1 + len(__magic_name__				))		,      )

										a										=							self.rust_tokenizer_class.from_pretrained(
										    __magic_name__		,      use_fast=__magic_name__		,      add_prefix_space=__magic_name__		,      trim_offsets=__magic_name__				)
										a										=							tokenizer_r(__magic_name__		,      return_offsets_mapping=__magic_name__		,      add_special_tokens=__magic_name__				)
										self.assertEqual(encoding.offset_mapping[0]		,      (0, len(__magic_name__				))				)
										self.assertEqual(
										    encoding.offset_mapping[1]		,      (len(__magic_name__				) + 1, len(__magic_name__				) + 1 + len(__magic_name__				))		,      )

										a										=							self.rust_tokenizer_class.from_pretrained(
										    __magic_name__		,      use_fast=__magic_name__		,      add_prefix_space=__magic_name__		,      trim_offsets=__magic_name__				)
										a										=							tokenizer_r(__magic_name__		,      return_offsets_mapping=__magic_name__		,      add_special_tokens=__magic_name__				)
										self.assertEqual(encoding.offset_mapping[0]		,      (0, len(__magic_name__				))				)
										self.assertEqual(
										    encoding.offset_mapping[1]		,      (len(__magic_name__				), len(__magic_name__				) + 1 + len(__magic_name__				))		,      )

										a										=							self.rust_tokenizer_class.from_pretrained(
										    __magic_name__		,      use_fast=__magic_name__		,      add_prefix_space=__magic_name__		,      trim_offsets=__magic_name__				)
										a										=							tokenizer_r(__magic_name__		,      return_offsets_mapping=__magic_name__		,      add_special_tokens=__magic_name__				)
										self.assertEqual(encoding.offset_mapping[0]		,      (0, len(__magic_name__				))				)
										self.assertEqual(
										    encoding.offset_mapping[1]		,      (len(__magic_name__				), len(__magic_name__				) + 1 + len(__magic_name__				))		,      )

										a										=							F' {text}'

										# tokenizer_r = self.rust_tokenizer_class.from_pretrained(
										#     pretrained_name, use_fast=True, add_prefix_space=True, trim_offsets=True
										# )
										# encoding = tokenizer_r(text, return_offsets_mapping=True, add_special_tokens=False)
										# self.assertEqual(encoding.offset_mapping[0], (1, 1 + len(text_of_1_token)))
										# self.assertEqual(
										#     encoding.offset_mapping[1],
										#     (1 + len(text_of_1_token) + 1, 1 + len(text_of_1_token) + 1 + len(text_of_1_token)),
										# )

										a										=							self.rust_tokenizer_class.from_pretrained(
										    __magic_name__		,      use_fast=__magic_name__		,      add_prefix_space=__magic_name__		,      trim_offsets=__magic_name__				)
										a										=							tokenizer_r(__magic_name__		,      return_offsets_mapping=__magic_name__		,      add_special_tokens=__magic_name__				)
										self.assertEqual(encoding.offset_mapping[0]		,      (1, 1 + len(__magic_name__				))				)
										self.assertEqual(
										    encoding.offset_mapping[1]		,      (1 + len(__magic_name__				) + 1, 1 + len(__magic_name__				) + 1 + len(__magic_name__				))		,      )

										a										=							self.rust_tokenizer_class.from_pretrained(
										    __magic_name__		,      use_fast=__magic_name__		,      add_prefix_space=__magic_name__		,      trim_offsets=__magic_name__				)
										a										=							tokenizer_r(__magic_name__		,      return_offsets_mapping=__magic_name__		,      add_special_tokens=__magic_name__				)
										self.assertEqual(encoding.offset_mapping[0]		,      (0, 1 + len(__magic_name__				))				)
										self.assertEqual(
										    encoding.offset_mapping[1]		,      (1 + len(__magic_name__				), 1 + len(__magic_name__				) + 1 + len(__magic_name__				))		,      )

										a										=							self.rust_tokenizer_class.from_pretrained(
										    __magic_name__		,      use_fast=__magic_name__		,      add_prefix_space=__magic_name__		,      trim_offsets=__magic_name__				)
										a										=							tokenizer_r(__magic_name__		,      return_offsets_mapping=__magic_name__		,      add_special_tokens=__magic_name__				)
										self.assertEqual(encoding.offset_mapping[0]		,      (0, 1 + len(__magic_name__				))				)
										self.assertEqual(
										    encoding.offset_mapping[1]		,      (1 + len(__magic_name__				), 1 + len(__magic_name__				) + 1 + len(__magic_name__				))		,      )







from __future__ import annotations





def 		__A		(	__lowerCamelCase							,			__lowerCamelCase = None    )      ->       list[list[str]]:
	a										=							word_bank or []
	# create a table
	a										=							len(__lowerCamelCase    ) + 1

	a										=							[]
	for _ in range(__lowerCamelCase    ):
		table.append([]    )
	# seed value
	a										=							[[]]  # because empty string has empty combination

	# iterate through the indices
	for i in range(__lowerCamelCase    ):
		# condition
		if table[i] != []:
			for word in word_bank:
				# slice condition
				if target[i : i + len(__lowerCamelCase    )] == word:
					a										=							[
					    [word, *way] for way in table[i]
					]
					# adds the word to every combination the current position holds
					# now,push that combination to the table[i+len(word)]
					table[i + len(__lowerCamelCase    )] += new_combinations

    # combinations are in reverse order so reverse for better output
	for combination in table[len(__lowerCamelCase    )]:
		combination.reverse()

	return table[len(__lowerCamelCase    )]


if __name__ == "__main__":
		print(all_construct("jwajalapa", ["jwa", "j", "w", "a", "la", "lapa"]))
		print(all_construct("rajamati", ["s", "raj", "amat", "raja", "ma", "i", "t"]))
		print(
		    all_construct(
		        "hexagonosaurus",
		        ["h", "ex", "hex", "ag", "ago", "ru", "auru", "rus", "go", "no", "o", "s"],
		    )
		)

