






"""simple docstring"""






import json
import os
import re
import shutil
import tempfile
import unittest
from typing import Tuple

from transformers import AddedToken, BatchEncoding, ByTaTokenizer
from transformers.utils import cached_property, is_tf_available, is_torch_available

from ...test_tokenization_common import TokenizerTesterMixin


if is_torch_available():
					SCREAMING_SNAKE_CASE    :    Optional[Any]        =							'''pt'''
elif is_tf_available():
					SCREAMING_SNAKE_CASE    :    Optional[Any]        =							'''tf'''
else:
					SCREAMING_SNAKE_CASE    :    Any        =							'''jax'''





class    snake_case_							(     _lowerCamelCase     ,				unittest.TestCase							):



	"""simple docstring"""

	SCREAMING_SNAKE_CASE_:				int       =       ByTaTokenizer
	SCREAMING_SNAKE_CASE_:				Optional[int]       =       False


	def    _UpperCAmelCase    (   self    ):


					"""simple docstring"""

					super().setUp()
					A__							=							ByTaTokenizer()
					tokenizer.save_pretrained(self.tmpdirname    )


	@cached_property
	def    _UpperCAmelCase    (   self    ):


					"""simple docstring"""

					return ByTaTokenizer.from_pretrained('google/byt5-small'    )


	def    _UpperCAmelCase    (   self	,       **__a    ):


					"""simple docstring"""

					return self.tokenizer_class.from_pretrained(self.tmpdirname	,       **lowerCamelCase_    )


	def    _UpperCAmelCase    (   self	,       __a	,       __a=False	,       __a=20	,       __a=5    ):


					"""simple docstring"""

					A__							=							[]
					for i in range(len(lowerCamelCase_    )    ):
									try:
													A__							=							tokenizer.decode([i]	,       clean_up_tokenization_spaces=lowerCamelCase_    )
									except UnicodeDecodeError:
													pass
									toks.append((i, tok)    )

					A__							=							list(filter(lambda __a    : re.match(r'^[ a-zA-Z]+$'	,       t[1]    )	,       lowerCamelCase_    )    )
					A__							=							list(filter(lambda __a    : [t[0]] == tokenizer.encode(t[1]	,       add_special_tokens=lowerCamelCase_    )	,       lowerCamelCase_    )    )
					if max_length is not None and len(lowerCamelCase_    ) > max_length:
									A__							=							toks[:max_length]
					if min_length is not None and len(lowerCamelCase_    ) < min_length and len(lowerCamelCase_    ) > 0:
									while len(lowerCamelCase_    ) < min_length:
													A__							=							toks + toks
        # toks_str = [t[1] for t in toks]
					A__							=							[t[0] for t in toks]

					# Ensure consistency
					A__							=							tokenizer.decode(lowerCamelCase_	,       clean_up_tokenization_spaces=lowerCamelCase_    )
					if " " not in output_txt and len(lowerCamelCase_    ) > 1:
									A__							=							(
									    tokenizer.decode([toks_ids[0]]	,       clean_up_tokenization_spaces=lowerCamelCase_    )
									    + ' '
									    + tokenizer.decode(toks_ids[1:]	,       clean_up_tokenization_spaces=lowerCamelCase_    )
									)
					if with_prefix_space:
									A__							=							' ' + output_txt
					A__							=							tokenizer.encode(lowerCamelCase_	,       add_special_tokens=lowerCamelCase_    )
					return output_txt, output_ids


	def    _UpperCAmelCase    (   self    ):


					"""simple docstring"""

					A__							=							self.ta_base_tokenizer
					A__							=							tokenizer(['hi</s>', 'I went to the gym</s>', '</s>']    )
					A__							=							tokenizer(['hi', 'I went to the gym', '']    )
					self.assertListEqual(batch_with_eos_added['input_ids']	,       batch_without_eos_added['input_ids']    )


	def    _UpperCAmelCase    (   self    ):


					"""simple docstring"""

					A__							=							self.ta_base_tokenizer
					A__							=							'Unicode €.'
					A__							=							tokenizer(lowerCamelCase_    )
					A__							=							[88, 113, 108, 102, 114, 103, 104, 35, 229, 133, 175, 49, 1]
					self.assertEqual(encoded['input_ids']	,       lowerCamelCase_    )

					# decoding
					A__							=							tokenizer.decode(lowerCamelCase_    )
					self.assertEqual(lowerCamelCase_	,       'Unicode €.</s>'    )

					A__							=							tokenizer('e è é ê ë'    )
					A__							=							[104, 35, 198, 171, 35, 198, 172, 35, 198, 173, 35, 198, 174, 1]
					self.assertEqual(encoded['input_ids']	,       lowerCamelCase_    )
					# decoding
					A__							=							tokenizer.decode(lowerCamelCase_    )
					self.assertEqual(lowerCamelCase_	,       'e è é ê ë</s>'    )

					# encode/decode, but with `encode` instead of `__call__`
					self.assertEqual(tokenizer.decode(tokenizer.encode('e è é ê ë'    )    )	,       'e è é ê ë</s>'    )


	def    _UpperCAmelCase    (   self    ):


					"""simple docstring"""

					A__							=							self.ta_base_tokenizer
					A__							=							['A long paragraph for summarization.', 'Another paragraph for summarization.']
					# fmt: off
					A__							=							[68, 35, 111, 114, 113, 106, 35, 115, 100, 117, 100, 106, 117, 100, 115, 107, 35, 105, 114, 117, 35, 118, 120, 112, 112, 100, 117, 108, 125, 100, 119, 108, 114, 113, 49, 1, 0]
					# fmt: on
					A__							=							tokenizer(lowerCamelCase_	,       padding=lowerCamelCase_	,       return_tensors=lowerCamelCase_    )
					self.assertIsInstance(lowerCamelCase_	,       lowerCamelCase_    )

					if FRAMEWORK != "jax":
									A__							=							list(batch.input_ids.numpy()[0]    )
					else:
									A__							=							list(batch.input_ids.tolist()[0]    )

					self.assertListEqual(lowerCamelCase_	,       lowerCamelCase_    )

					self.assertEqual((2, 37)	,       batch.input_ids.shape    )
					self.assertEqual((2, 37)	,       batch.attention_mask.shape    )


	def    _UpperCAmelCase    (   self    ):


					"""simple docstring"""

					A__							=							self.ta_base_tokenizer
					A__							=							['A long paragraph for summarization.', 'Another paragraph for summarization.']
					A__							=							tokenizer(lowerCamelCase_	,       padding=lowerCamelCase_	,       return_tensors=lowerCamelCase_    )
					# check if input_ids are returned and no decoder_input_ids
					self.assertIn('input_ids'	,       lowerCamelCase_    )
					self.assertIn('attention_mask'	,       lowerCamelCase_    )
					self.assertNotIn('decoder_input_ids'	,       lowerCamelCase_    )
					self.assertNotIn('decoder_attention_mask'	,       lowerCamelCase_    )


	def    _UpperCAmelCase    (   self    ):


					"""simple docstring"""

					A__							=							self.ta_base_tokenizer
					A__							=							[
					    'Summary of the text.',
					    'Another summary.',
					]
					A__							=							tokenizer(
					    text_target=lowerCamelCase_	,       max_length=32	,       padding='max_length'	,       truncation=lowerCamelCase_	,       return_tensors=lowerCamelCase_    )
					self.assertEqual(32	,       targets['input_ids'].shape[1]    )


	def    _UpperCAmelCase    (   self    ):


					"""simple docstring"""

					A__							=							self.ta_base_tokenizer
					A__							=							['A long paragraph for summarization. </s>']
					A__							=							['Summary of the text. </s>']
					# fmt: off
					A__							=							[68, 35, 111, 114, 113, 106, 35, 115, 100, 117, 100, 106, 117, 100, 115, 107, 35, 105, 114, 117, 35, 118, 120, 112, 112, 100, 117, 108, 125, 100, 119, 108, 114, 113, 49, 35, 1]
					A__							=							[86, 120, 112, 112, 100, 117, 124, 35, 114, 105, 35, 119, 107, 104, 35, 119, 104, 123, 119, 49, 35, 1]
					# fmt: on

					A__							=							tokenizer(lowerCamelCase_	,       text_target=lowerCamelCase_    )

					self.assertEqual(lowerCamelCase_	,       batch['input_ids'][0]    )
					self.assertEqual(lowerCamelCase_	,       batch['labels'][0]    )


	def    _UpperCAmelCase    (   self    ):


					"""simple docstring"""

					A__							=							self.get_tokenizers()
					for tokenizer in tokenizers:
									with self.subTest(f'''{tokenizer.__class__.__name__}'''    ):
													self.assertNotEqual(tokenizer.model_max_length	,       42    )

        # Now let's start the test
					A__							=							self.get_tokenizers()
					for tokenizer in tokenizers:
									with self.subTest(f'''{tokenizer.__class__.__name__}'''    ):
													# Isolate this from the other tests because we save additional tokens/etc
													A__							=							tempfile.mkdtemp()

													A__							=							' He is very happy, UNwant\u00E9d,running'
													A__							=							tokenizer.encode(lowerCamelCase_	,       add_special_tokens=lowerCamelCase_    )
													tokenizer.save_pretrained(lowerCamelCase_    )

													A__							=							tokenizer.__class__.from_pretrained(lowerCamelCase_    )
													A__							=							after_tokenizer.encode(lowerCamelCase_	,       add_special_tokens=lowerCamelCase_    )
													self.assertListEqual(lowerCamelCase_	,       lowerCamelCase_    )

													shutil.rmtree(lowerCamelCase_    )

					A__							=							self.get_tokenizers(model_max_length=42    )
					for tokenizer in tokenizers:
									with self.subTest(f'''{tokenizer.__class__.__name__}'''    ):
													# Isolate this from the other tests because we save additional tokens/etc
													A__							=							tempfile.mkdtemp()

													A__							=							' He is very happy, UNwant\u00E9d,running'
													tokenizer.add_tokens(['bim', 'bambam']    )
													A__							=							tokenizer.additional_special_tokens
													additional_special_tokens.append('new_additional_special_token'    )
													tokenizer.add_special_tokens({'additional_special_tokens': additional_special_tokens}    )
													A__							=							tokenizer.encode(lowerCamelCase_	,       add_special_tokens=lowerCamelCase_    )
													tokenizer.save_pretrained(lowerCamelCase_    )

													A__							=							tokenizer.__class__.from_pretrained(lowerCamelCase_    )
													A__							=							after_tokenizer.encode(lowerCamelCase_	,       add_special_tokens=lowerCamelCase_    )
													self.assertListEqual(lowerCamelCase_	,       lowerCamelCase_    )
													self.assertIn('new_additional_special_token'	,       after_tokenizer.additional_special_tokens    )
													self.assertEqual(after_tokenizer.model_max_length	,       42    )

													A__							=							tokenizer.__class__.from_pretrained(lowerCamelCase_	,       model_max_length=43    )
													self.assertEqual(tokenizer.model_max_length	,       43    )

													shutil.rmtree(lowerCamelCase_    )


	def    _UpperCAmelCase    (   self    ):


					"""simple docstring"""

					A__							=							[]
					if self.test_slow_tokenizer:
									tokenizer_list.append((self.tokenizer_class, self.get_tokenizer())    )

					if self.test_rust_tokenizer:
									tokenizer_list.append((self.rust_tokenizer_class, self.get_rust_tokenizer())    )

					for tokenizer_class, tokenizer_utils in tokenizer_list:
									with tempfile.TemporaryDirectory() as tmp_dir:
													tokenizer_utils.save_pretrained(lowerCamelCase_    )

													with open(os.path.join(lowerCamelCase_	,       'special_tokens_map.json'    )	,       encoding='utf-8'    ) as json_file:
																	A__							=							json.load(lowerCamelCase_    )

													with open(os.path.join(lowerCamelCase_	,       'tokenizer_config.json'    )	,       encoding='utf-8'    ) as json_file:
																	A__							=							json.load(lowerCamelCase_    )

													A__							=							[f'''<extra_id_{i}>''' for i in range(125    )]

													A__							=							added_tokens_extra_ids + [
													    'an_additional_special_token'
													]
													A__							=							added_tokens_extra_ids + [
													    'an_additional_special_token'
													]

													with open(os.path.join(lowerCamelCase_	,       'special_tokens_map.json'    )	,       'w'	,       encoding='utf-8'    ) as outfile:
																	json.dump(lowerCamelCase_	,       lowerCamelCase_    )
													with open(os.path.join(lowerCamelCase_	,       'tokenizer_config.json'    )	,       'w'	,       encoding='utf-8'    ) as outfile:
																	json.dump(lowerCamelCase_	,       lowerCamelCase_    )

													# the following checks allow us to verify that our test works as expected, i.e. that the tokenizer takes
													# into account the new value of additional_special_tokens given in the "tokenizer_config.json" and
													# "special_tokens_map.json" files
													A__							=							tokenizer_class.from_pretrained(
													    lowerCamelCase_	,       )
													self.assertIn(
													    'an_additional_special_token'	,       tokenizer_without_change_in_init.additional_special_tokens    )
													# self.assertIn("an_additional_special_token",tokenizer_without_change_in_init.get_vocab()) # ByT5Tokenization no vocab
													self.assertEqual(
													    ['an_additional_special_token']	,       tokenizer_without_change_in_init.convert_ids_to_tokens(
													        tokenizer_without_change_in_init.convert_tokens_to_ids(['an_additional_special_token']    )    )	,       )

													# Now we test that we can change the value of additional_special_tokens in the from_pretrained
													A__							=							added_tokens_extra_ids + [AddedToken('a_new_additional_special_token'	,       lstrip=lowerCamelCase_    )]
													A__							=							tokenizer_class.from_pretrained(
													    lowerCamelCase_	,       additional_special_tokens=lowerCamelCase_	,       )

													self.assertIn('a_new_additional_special_token'	,       tokenizer.additional_special_tokens    )
													self.assertEqual(
													    ['a_new_additional_special_token']	,       tokenizer.convert_ids_to_tokens(
													        tokenizer.convert_tokens_to_ids(['a_new_additional_special_token']    )    )	,       )


	def    _UpperCAmelCase    (   self    ):


					"""simple docstring"""

					A__							=							[]
					if self.test_slow_tokenizer:
									tokenizer_list.append((self.tokenizer_class, self.get_tokenizer())    )

					if self.test_rust_tokenizer:
									tokenizer_list.append((self.rust_tokenizer_class, self.get_rust_tokenizer())    )

					for tokenizer_class, tokenizer_utils in tokenizer_list:
									with tempfile.TemporaryDirectory() as tmp_dir:
													tokenizer_utils.save_pretrained(lowerCamelCase_    )

													A__							=							tokenizer_class.from_pretrained(lowerCamelCase_    )

													self.assertTrue(tokenizer.decode([255]    ) == ''    )


	def    _UpperCAmelCase    (   self    ):


					"""simple docstring"""

					pass


	def    _UpperCAmelCase    (   self    ):


					"""simple docstring"""

					pass


	def    _UpperCAmelCase    (   self    ):


					"""simple docstring"""

					pass


	def    _UpperCAmelCase    (   self    ):


					"""simple docstring"""

					pass


	def    _UpperCAmelCase    (   self    ):


					"""simple docstring"""

					A__							=							self.get_tokenizers(fast=lowerCamelCase_	,       do_lower_case=lowerCamelCase_    )
					for tokenizer in tokenizers:
									with self.subTest(f'''{tokenizer.__class__.__name__}'''    ):
													A__							=							['t', 'h', 'i', 's', ' ', 'i', 's', ' ', 'a', ' ', 't', 'e', 'x', 't', '</s>']
													A__							=							tokenizer.convert_tokens_to_string(lowerCamelCase_    )

													self.assertIsInstance(lowerCamelCase_	,       lowerCamelCase_    )






	def    _UpperCAmelCase    (   self    ):


					"""simple docstring"""

					A__							=							self.get_tokenizers()
					for tokenizer in tokenizers:
									with self.subTest(f'''{tokenizer.__class__.__name__}'''    ):
													A__							=							[
													    'bos_token',
													    'eos_token',
													    'unk_token',
													    'sep_token',
													    'pad_token',
													    'cls_token',
													    'mask_token',
													]

													A__							=							0
													A__							=							tokenizer.convert_ids_to_tokens(
													    lowerCamelCase_	,       skip_special_tokens=lowerCamelCase_    )

													for attr in attributes_list:
																	setattr(lowerCamelCase_	,       attr + '_id'	,       lowerCamelCase_    )
																	self.assertEqual(getattr(lowerCamelCase_	,       lowerCamelCase_    )	,       lowerCamelCase_    )
																	self.assertEqual(getattr(lowerCamelCase_	,       attr + '_id'    )	,       lowerCamelCase_    )

																	setattr(lowerCamelCase_	,       attr + '_id'	,       lowerCamelCase_    )
																	self.assertEqual(getattr(lowerCamelCase_	,       lowerCamelCase_    )	,       lowerCamelCase_    )
																	self.assertEqual(getattr(lowerCamelCase_	,       attr + '_id'    )	,       lowerCamelCase_    )

													setattr(lowerCamelCase_	,       'additional_special_tokens_ids'	,       []    )
													self.assertListEqual(getattr(lowerCamelCase_	,       'additional_special_tokens'    )	,       []    )
													self.assertListEqual(getattr(lowerCamelCase_	,       'additional_special_tokens_ids'    )	,       []    )

													setattr(lowerCamelCase_	,       'additional_special_tokens_ids'	,       [token_id_to_test_setters]    )
													self.assertListEqual(getattr(lowerCamelCase_	,       'additional_special_tokens'    )	,       [token_to_test_setters]    )
													self.assertListEqual(getattr(lowerCamelCase_	,       'additional_special_tokens_ids'    )	,       [token_id_to_test_setters]    )





"""simple docstring"""


import re

from filelock import FileLock


try:
  import nltk

  UpperCAmelCase													=True
except (ImportError, ModuleNotFoundError):
  UpperCAmelCase													=False

if NLTK_AVAILABLE:
  with FileLock(".lock") as lock:
    nltk.download("punkt", quiet=True)



def   _A					(	_a	:						str				):



      """simple docstring"""






      re.sub("""<n>"""     ,   """"""     ,   _a				)  # remove pegasus newline char
      assert NLTK_AVAILABLE, "nltk must be installed to separate newlines between sentences. (pip install nltk)"
      return "\n".join(nltk.sent_tokenize(_a				)				)




