



'''simple docstring'''




import os
import unittest

from transformers import FunnelTokenizer, FunnelTokenizerFast
from transformers.models.funnel.tokenization_funnel import VOCAB_FILES_NAMES
from transformers.testing_utils import require_tokenizers

from ...test_tokenization_common import TokenizerTesterMixin

@require_tokenizers
class 			UpperCamelCase_ (							__magic_name__      ,     unittest.TestCase			):
	lowercase          = FunnelTokenizer
	lowercase          = FunnelTokenizerFast
	lowercase          = True
	lowercase          = True





	def  _lowercase(  self    )			->			Union[str, Any]:
								super().setUp()

								UpperCAmelCase     :		List[Any]							     =		[
								    """<unk>""",
								    """<cls>""",
								    """<sep>""",
								    """want""",
								    """##want""",
								    """##ed""",
								    """wa""",
								    """un""",
								    """runn""",
								    """##ing""",
								    """,""",
								    """low""",
								    """lowest""",
								]
								UpperCAmelCase     :		Tuple							     =		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  _lowercase(  self		,		**A    )			->			Optional[Any]:
								return FunnelTokenizer.from_pretrained(self.tmpdirname		,		**A    )





	def  _lowercase(  self		,		**A    )			->			Tuple:
								return FunnelTokenizerFast.from_pretrained(self.tmpdirname		,		**A    )





	def  _lowercase(  self		,		A    )			->			Any:
								UpperCAmelCase     :		Tuple							     =		"""UNwant\u00E9d,running"""
								UpperCAmelCase     :		int							     =		"""unwanted, running"""
								return input_text, output_text





	def  _lowercase(  self    )			->			Tuple:
								UpperCAmelCase     :		Dict							     =		self.tokenizer_class(self.vocab_file    )

								UpperCAmelCase     :		Optional[int]							     =		tokenizer.tokenize("""UNwant\u00E9d,running"""    )
								self.assertListEqual(A		,		["""un""", """##want""", """##ed""", """,""", """runn""", """##ing"""]    )
								self.assertListEqual(tokenizer.convert_tokens_to_ids(A    )		,		[7, 4, 5, 10, 8, 9]    )






	def  _lowercase(  self    )			->			Any:
								UpperCAmelCase     :		str							     =		self.get_tokenizers(do_lower_case=A    )
								for tokenizer in tokenizers:
															UpperCAmelCase     :		Dict							     =		tokenizer("""UNwant\u00E9d,running"""    )
															UpperCAmelCase     :		str							     =		len(inputs["""input_ids"""]    ) - 1
															self.assertListEqual(inputs["""token_type_ids"""]		,		[2] + [0] * sentence_len    )

															UpperCAmelCase     :		Union[str, Any]							     =		tokenizer("""UNwant\u00E9d,running"""		,		"""UNwant\u00E9d,running"""    )
															self.assertListEqual(inputs["""token_type_ids"""]		,		[2] + [0] * sentence_len + [1] * sentence_len    )






'''simple docstring'''




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 			UpperCamelCase_ (							__magic_name__      ,     unittest.TestCase			):
	lowercase          = LongformerTokenizer
	lowercase          = True
	lowercase          = LongformerTokenizerFast
	lowercase          = True





	def  _lowercase(  self    )			->			List[Any]:
								super().setUp()

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

								UpperCAmelCase     :		int							     =		os.path.join(self.tmpdirname		,		VOCAB_FILES_NAMES["""vocab_file"""]    )
								UpperCAmelCase     :		Optional[int]							     =		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(A    ) + """\n"""    )
								with open(self.merges_file		,		"""w"""		,		encoding="""utf-8"""    ) as fp:
															fp.write("""\n""".join(A    )    )





	def  _lowercase(  self		,		**A    )			->			Optional[Any]:
								kwargs.update(self.special_tokens_map    )
								return self.tokenizer_class.from_pretrained(self.tmpdirname		,		**A    )





	def  _lowercase(  self		,		**A    )			->			int:
								kwargs.update(self.special_tokens_map    )
								return self.rust_tokenizer_class.from_pretrained(self.tmpdirname		,		**A    )





	def  _lowercase(  self		,		A    )			->			Optional[int]:
								UpperCAmelCase     :		Optional[Any]							     =		"""lower newer"""
								UpperCAmelCase     :		Optional[int]							     =		"""lower newer"""
								return input_text, output_text





	def  _lowercase(  self    )			->			Optional[Any]:
								UpperCAmelCase     :		Tuple							     =		self.tokenizer_class(self.vocab_file		,		self.merges_file		,		**self.special_tokens_map    )
								UpperCAmelCase     :		Dict							     =		"""lower newer"""
								UpperCAmelCase     :		int							     =		["""l""", """o""", """w""", """er""", """\u0120""", """n""", """e""", """w""", """er"""]
								UpperCAmelCase     :		Tuple							     =		tokenizer.tokenize(A    )  # , add_prefix_space=True)
								self.assertListEqual(A		,		A    )

								UpperCAmelCase     :		Any							     =		tokens + [tokenizer.unk_token]
								UpperCAmelCase     :		Tuple							     =		[0, 1, 2, 15, 10, 9, 3, 2, 15, 19]
								self.assertListEqual(tokenizer.convert_tokens_to_ids(A    )		,		A    )





	def  _lowercase(  self    )			->			Union[str, Any]:
								UpperCAmelCase     :		str							     =		self.get_tokenizer()

								self.assertListEqual(tokenizer.encode("""Hello world!"""		,		add_special_tokens=A    )		,		[0, 31414, 232, 328, 2]    )
								self.assertListEqual(
								    tokenizer.encode("""Hello world! cécé herlolip 418"""		,		add_special_tokens=A    )		,		[0, 31414, 232, 328, 740, 1140, 12695, 69, 46078, 1588, 2]		,		)





	@slow
	def  _lowercase(  self    )			->			Optional[int]:
								UpperCAmelCase     :		Any							     =		self.tokenizer_class.from_pretrained("""allenai/longformer-base-4096"""    )

								UpperCAmelCase     :		List[Any]							     =		tokenizer.encode("""sequence builders"""		,		add_special_tokens=A    )
								UpperCAmelCase     :		Optional[Any]							     =		tokenizer.encode("""multi-sequence build"""		,		add_special_tokens=A    )

								UpperCAmelCase     :		List[str]							     =		tokenizer.encode(
								    """sequence builders"""		,		add_special_tokens=A		,		add_prefix_space=A    )
								UpperCAmelCase     :		List[str]							     =		tokenizer.encode(
								    """sequence builders"""		,		"""multi-sequence build"""		,		add_special_tokens=A		,		add_prefix_space=A    )

								UpperCAmelCase     :		Union[str, Any]							     =		tokenizer.build_inputs_with_special_tokens(A    )
								UpperCAmelCase     :		Any							     =		tokenizer.build_inputs_with_special_tokens(A		,		A    )

								assert encoded_sentence == encoded_text_from_decode
								assert encoded_pair == encoded_pair_from_decode





	def  _lowercase(  self    )			->			List[Any]:
								UpperCAmelCase     :		str							     =		self.get_tokenizer()

								UpperCAmelCase     :		List[Any]							     =		"""Encode this sequence."""
								UpperCAmelCase     :		List[str]							     =		tokenizer.byte_encoder[""" """.encode("""utf-8"""    )[0]]

								# Testing encoder arguments
								UpperCAmelCase     :		Union[str, Any]							     =		tokenizer.encode(A		,		add_special_tokens=A		,		add_prefix_space=A    )
								UpperCAmelCase     :		Dict							     =		tokenizer.convert_ids_to_tokens(encoded[0]    )[0]
								self.assertNotEqual(A		,		A    )

								UpperCAmelCase     :		Tuple							     =		tokenizer.encode(A		,		add_special_tokens=A		,		add_prefix_space=A    )
								UpperCAmelCase     :		int							     =		tokenizer.convert_ids_to_tokens(encoded[0]    )[0]
								self.assertEqual(A		,		A    )

								tokenizer.add_special_tokens({"""bos_token""": """<s>"""}    )
								UpperCAmelCase     :		int							     =		tokenizer.encode(A		,		add_special_tokens=A    )
								UpperCAmelCase     :		List[Any]							     =		tokenizer.convert_ids_to_tokens(encoded[1]    )[0]
								self.assertNotEqual(A		,		A    )

								# Testing spaces after special tokens
								UpperCAmelCase     :		Union[str, Any]							     =		"""<mask>"""
								tokenizer.add_special_tokens(
								    {"""mask_token""": AddedToken(A		,		lstrip=A		,		rstrip=A    )}    )  # mask token has a left space
								UpperCAmelCase     :		str							     =		tokenizer.convert_tokens_to_ids(A    )

								UpperCAmelCase     :		Union[str, Any]							     =		"""Encode <mask> sequence"""
								UpperCAmelCase     :		Union[str, Any]							     =		"""Encode <mask>sequence"""

								UpperCAmelCase     :		Union[str, Any]							     =		tokenizer.encode(A    )
								UpperCAmelCase     :		Union[str, Any]							     =		encoded.index(A    )
								UpperCAmelCase     :		List[str]							     =		tokenizer.convert_ids_to_tokens(encoded[mask_loc + 1]    )[0]
								self.assertEqual(A		,		A    )

								UpperCAmelCase     :		Tuple							     =		tokenizer.encode(A    )
								UpperCAmelCase     :		Optional[int]							     =		encoded.index(A    )
								UpperCAmelCase     :		Optional[int]							     =		tokenizer.convert_ids_to_tokens(encoded[mask_loc + 1]    )[0]
								self.assertNotEqual(A		,		A    )





	def  _lowercase(  self    )			->			Optional[int]:
								pass





	def  _lowercase(  self    )			->			Any:
								for tokenizer, pretrained_name, kwargs in self.tokenizers_list:
															with self.subTest(f'''{tokenizer.__class__.__name__} ({pretrained_name})'''    ):
																						UpperCAmelCase     :		str							     =		self.rust_tokenizer_class.from_pretrained(A		,		**A    )
																						UpperCAmelCase     :		int							     =		self.tokenizer_class.from_pretrained(A		,		**A    )
																						UpperCAmelCase     :		Dict							     =		"""A, <mask> AllenNLP sentence."""
																						UpperCAmelCase     :		Dict							     =		tokenizer_r.encode_plus(A		,		add_special_tokens=A		,		return_token_type_ids=A    )
																						UpperCAmelCase     :		Tuple							     =		tokenizer_p.encode_plus(A		,		add_special_tokens=A		,		return_token_type_ids=A    )

																						# 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"""]    )		,		)

																						UpperCAmelCase     :		List[Any]							     =		tokenizer_r.convert_ids_to_tokens(tokens_r["""input_ids"""]    )
																						UpperCAmelCase     :		int							     =		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, 50264, 3823, 487, 21992, 3645, 4, 2]    )
																						self.assertSequenceEqual(tokens_r["""input_ids"""]		,		[0, 250, 6, 50264, 3823, 487, 21992, 3645, 4, 2]    )

																						self.assertSequenceEqual(
																						    A		,		["""<s>""", """A""", """,""", """<mask>""", """ĠAllen""", """N""", """LP""", """Ġsentence""", """.""", """</s>"""]    )
																						self.assertSequenceEqual(
																						    A		,		["""<s>""", """A""", """,""", """<mask>""", """ĠAllen""", """N""", """LP""", """Ġsentence""", """.""", """</s>"""]    )





	def  _lowercase(  self    )			->			List[Any]:
								for trim_offsets, add_prefix_space in itertools.product([True, False]		,		repeat=2    ):
															UpperCAmelCase     :		Optional[int]							     =		self.rust_tokenizer_class.from_pretrained(
															    self.tmpdirname		,		use_fast=A		,		add_prefix_space=A		,		trim_offsets=A    )

															UpperCAmelCase     :		Optional[int]							     =		json.loads(tokenizer_r.backend_tokenizer.pre_tokenizer.__getstate__()    )
															UpperCAmelCase     :		Optional[int]							     =		json.loads(tokenizer_r.backend_tokenizer.post_processor.__getstate__()    )

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

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






	def  _lowercase(  self    )			->			Optional[Any]:
								# Test which aims to verify that the offsets are well adapted to the argument `add_prefix_space` and
								# `trim_offsets`
								for tokenizer, pretrained_name, kwargs in self.tokenizers_list:
															with self.subTest(f'''{tokenizer.__class__.__name__} ({pretrained_name})'''    ):
																						UpperCAmelCase     :		Union[str, Any]							     =		"""hello"""  # `hello` is a token in the vocabulary of `pretrained_name`
																						UpperCAmelCase     :		int							     =		f'''{text_of_1_token} {text_of_1_token}'''

																						UpperCAmelCase     :		List[Any]							     =		self.rust_tokenizer_class.from_pretrained(
																						    A		,		use_fast=A		,		add_prefix_space=A		,		trim_offsets=A    )
																						UpperCAmelCase     :		str							     =		tokenizer_r(A		,		return_offsets_mapping=A		,		add_special_tokens=A    )
																						self.assertEqual(encoding.offset_mapping[0]		,		(0, len(A    ))    )
																						self.assertEqual(
																						    encoding.offset_mapping[1]		,		(len(A    ) + 1, len(A    ) + 1 + len(A    ))		,		)

																						UpperCAmelCase     :		Optional[Any]							     =		self.rust_tokenizer_class.from_pretrained(
																						    A		,		use_fast=A		,		add_prefix_space=A		,		trim_offsets=A    )
																						UpperCAmelCase     :		Dict							     =		tokenizer_r(A		,		return_offsets_mapping=A		,		add_special_tokens=A    )
																						self.assertEqual(encoding.offset_mapping[0]		,		(0, len(A    ))    )
																						self.assertEqual(
																						    encoding.offset_mapping[1]		,		(len(A    ) + 1, len(A    ) + 1 + len(A    ))		,		)

																						UpperCAmelCase     :		int							     =		self.rust_tokenizer_class.from_pretrained(
																						    A		,		use_fast=A		,		add_prefix_space=A		,		trim_offsets=A    )
																						UpperCAmelCase     :		List[Any]							     =		tokenizer_r(A		,		return_offsets_mapping=A		,		add_special_tokens=A    )
																						self.assertEqual(encoding.offset_mapping[0]		,		(0, len(A    ))    )
																						self.assertEqual(
																						    encoding.offset_mapping[1]		,		(len(A    ), len(A    ) + 1 + len(A    ))		,		)

																						UpperCAmelCase     :		Any							     =		self.rust_tokenizer_class.from_pretrained(
																						    A		,		use_fast=A		,		add_prefix_space=A		,		trim_offsets=A    )
																						UpperCAmelCase     :		str							     =		tokenizer_r(A		,		return_offsets_mapping=A		,		add_special_tokens=A    )
																						self.assertEqual(encoding.offset_mapping[0]		,		(0, len(A    ))    )
																						self.assertEqual(
																						    encoding.offset_mapping[1]		,		(len(A    ), len(A    ) + 1 + len(A    ))		,		)

																						UpperCAmelCase     :		Optional[Any]							     =		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)),
																						# )

																						UpperCAmelCase     :		Any							     =		self.rust_tokenizer_class.from_pretrained(
																						    A		,		use_fast=A		,		add_prefix_space=A		,		trim_offsets=A    )
																						UpperCAmelCase     :		str							     =		tokenizer_r(A		,		return_offsets_mapping=A		,		add_special_tokens=A    )
																						self.assertEqual(encoding.offset_mapping[0]		,		(1, 1 + len(A    ))    )
																						self.assertEqual(
																						    encoding.offset_mapping[1]		,		(1 + len(A    ) + 1, 1 + len(A    ) + 1 + len(A    ))		,		)

																						UpperCAmelCase     :		Optional[int]							     =		self.rust_tokenizer_class.from_pretrained(
																						    A		,		use_fast=A		,		add_prefix_space=A		,		trim_offsets=A    )
																						UpperCAmelCase     :		Union[str, Any]							     =		tokenizer_r(A		,		return_offsets_mapping=A		,		add_special_tokens=A    )
																						self.assertEqual(encoding.offset_mapping[0]		,		(0, 1 + len(A    ))    )
																						self.assertEqual(
																						    encoding.offset_mapping[1]		,		(1 + len(A    ), 1 + len(A    ) + 1 + len(A    ))		,		)

																						UpperCAmelCase     :		Union[str, Any]							     =		self.rust_tokenizer_class.from_pretrained(
																						    A		,		use_fast=A		,		add_prefix_space=A		,		trim_offsets=A    )
																						UpperCAmelCase     :		Optional[int]							     =		tokenizer_r(A		,		return_offsets_mapping=A		,		add_special_tokens=A    )
																						self.assertEqual(encoding.offset_mapping[0]		,		(0, 1 + len(A    ))    )
																						self.assertEqual(
																						    encoding.offset_mapping[1]		,		(1 + len(A    ), 1 + len(A    ) + 1 + len(A    ))		,		)

