
'''simple docstring'''


import json
import os
import shutil
import tempfile
import unittest

from transformers import BatchEncoding, CanineTokenizer
from transformers.testing_utils import require_tokenizers, require_torch
from transformers.tokenization_utils import AddedToken
from transformers.utils import cached_property

from ...test_tokenization_common import TokenizerTesterMixin

class 	__lowercase				(  _lowercase      ,     unittest.TestCase    ):
			lowerCamelCase			:		int	      =			CanineTokenizer
			lowerCamelCase			:		int	      =			False

			def        UpperCAmelCase__ (self      ):
								super().setUp()
								lowerCamelCase_					:      Optional[int]     =		CanineTokenizer()
								tokenizer.save_pretrained(self.tmpdirname      )

			@cached_property
			def        UpperCAmelCase__ (self      ):
								return CanineTokenizer.from_pretrained('''google/canine-s'''      )

			def        UpperCAmelCase__ (self			,   **A      ):
								lowerCamelCase_					:      List[Any]     =		self.tokenizer_class.from_pretrained(self.tmpdirname			,   **A      )
								lowerCamelCase_					:      Optional[Any]     =		1_0_2_4
								return tokenizer

			@require_torch
			def        UpperCAmelCase__ (self      ):
								lowerCamelCase_					:      str     =		self.canine_tokenizer
								lowerCamelCase_					:      List[Any]     =		['''Life is like a box of chocolates.''', '''You never know what you\'re gonna get.''']
								# fmt: off
								lowerCamelCase_					:      Optional[int]     =		[5_7_3_4_4, 7_6, 1_0_5, 1_0_2, 1_0_1, 3_2, 1_0_5, 1_1_5, 3_2, 1_0_8, 1_0_5, 1_0_7, 1_0_1, 3_2, 9_7, 3_2, 9_8, 1_1_1, 1_2_0, 3_2, 1_1_1, 1_0_2, 3_2, 9_9, 1_0_4, 1_1_1, 9_9, 1_1_1, 1_0_8, 9_7, 1_1_6, 1_0_1, 1_1_5, 4_6, 5_7_3_4_5, 0, 0, 0, 0]
								# fmt: on
								lowerCamelCase_					:      str     =		tokenizer(A			,   padding=A			,   return_tensors='''pt'''      )
								self.assertIsInstance(A			,   A      )

								lowerCamelCase_					:      List[str]     =		list(batch.input_ids.numpy()[0]      )

								self.assertListEqual(A			,   A      )

								self.assertEqual((2, 3_9)			,   batch.input_ids.shape      )
								self.assertEqual((2, 3_9)			,   batch.attention_mask.shape      )

			@require_torch
			def        UpperCAmelCase__ (self      ):
								lowerCamelCase_					:      List[Any]     =		self.canine_tokenizer
								lowerCamelCase_					:      Optional[Any]     =		['''Once there was a man.''', '''He wrote a test in HuggingFace Tranformers.''']
								lowerCamelCase_					:      Optional[Any]     =		tokenizer(A			,   padding=A			,   return_tensors='''pt'''      )
								# check if input_ids, attention_mask and token_type_ids are returned
								self.assertIn('''input_ids'''			,   A      )
								self.assertIn('''attention_mask'''			,   A      )
								self.assertIn('''token_type_ids'''			,   A      )

			@require_torch
			def        UpperCAmelCase__ (self      ):
								lowerCamelCase_					:      Optional[int]     =		self.canine_tokenizer
								lowerCamelCase_					:      str     =		[
								    '''What\'s the weater?''',
								    '''It\'s about 25 degrees.''',
								]
								lowerCamelCase_					:      List[str]     =		tokenizer(
								    text_target=A			,   max_length=3_2			,   padding='''max_length'''			,   truncation=A			,   return_tensors='''pt'''      )
								self.assertEqual(3_2			,   targets['''input_ids'''].shape[1]      )

			def        UpperCAmelCase__ (self      ):
								# safety check on max_len default value so we are sure the test works
								lowerCamelCase_					:      Any     =		self.get_tokenizers()
								for tokenizer in tokenizers:
													with self.subTest(F"""{tokenizer.__class__.__name__}"""      ):
																		self.assertNotEqual(tokenizer.model_max_length			,   4_2      )

        # Now let's start the test
								lowerCamelCase_					:      Dict     =		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
																		lowerCamelCase_					:      Union[str, Any]     =		tempfile.mkdtemp()

																		lowerCamelCase_					:      Union[str, Any]     =		''' He is very happy, UNwant\u00E9d,running'''
																		lowerCamelCase_					:      List[Any]     =		tokenizer.encode(A			,   add_special_tokens=A      )
																		tokenizer.save_pretrained(A      )

																		lowerCamelCase_					:      Any     =		tokenizer.__class__.from_pretrained(A      )
																		lowerCamelCase_					:      List[str]     =		after_tokenizer.encode(A			,   add_special_tokens=A      )
																		self.assertListEqual(A			,   A      )

																		shutil.rmtree(A      )

								lowerCamelCase_					:      Tuple     =		self.get_tokenizers(model_max_length=4_2      )
								for tokenizer in tokenizers:
													with self.subTest(F"""{tokenizer.__class__.__name__}"""      ):
																		# Isolate this from the other tests because we save additional tokens/etc
																		lowerCamelCase_					:      Dict     =		tempfile.mkdtemp()

																		lowerCamelCase_					:      int     =		''' He is very happy, UNwant\u00E9d,running'''

																		lowerCamelCase_					:      List[Any]     =		tokenizer.additional_special_tokens

																		# We can add a new special token for Canine as follows:
																		lowerCamelCase_					:      Dict     =		chr(0xe007      )
																		additional_special_tokens.append(A      )
																		tokenizer.add_special_tokens({'''additional_special_tokens''': additional_special_tokens}      )
																		lowerCamelCase_					:      Union[str, Any]     =		tokenizer.encode(A			,   add_special_tokens=A      )
																		tokenizer.save_pretrained(A      )

																		lowerCamelCase_					:      Optional[int]     =		tokenizer.__class__.from_pretrained(A      )
																		lowerCamelCase_					:      int     =		after_tokenizer.encode(A			,   add_special_tokens=A      )
																		self.assertListEqual(A			,   A      )
																		self.assertIn(A			,   after_tokenizer.additional_special_tokens      )
																		self.assertEqual(after_tokenizer.model_max_length			,   4_2      )

																		lowerCamelCase_					:      List[Any]     =		tokenizer.__class__.from_pretrained(A			,   model_max_length=4_3      )
																		self.assertEqual(tokenizer.model_max_length			,   4_3      )

																		shutil.rmtree(A      )

			def        UpperCAmelCase__ (self      ):
								lowerCamelCase_					:      int     =		self.get_tokenizers(do_lower_case=A      )
								for tokenizer in tokenizers:
													with self.subTest(F"""{tokenizer.__class__.__name__}"""      ):
																		lowerCamelCase_					:      Tuple     =		self.get_clean_sequence(A      )

																		# a special token for Canine can be defined as follows:
																		lowerCamelCase_					:      List[Any]     =		0xe005
																		lowerCamelCase_					:      Any     =		chr(A      )

																		tokenizer.add_special_tokens({'''cls_token''': special_token}      )
																		lowerCamelCase_					:      Union[str, Any]     =		tokenizer.encode(A			,   add_special_tokens=A      )
																		self.assertEqual(len(A      )			,   1      )

																		lowerCamelCase_					:      List[Any]     =		tokenizer.decode(ids + encoded_special_token			,   clean_up_tokenization_spaces=A      )
																		lowerCamelCase_					:      str     =		tokenizer.encode(A			,   add_special_tokens=A      )

																		lowerCamelCase_					:      Union[str, Any]     =		tokenizer.encode(A			,   add_special_tokens=A      )
																		lowerCamelCase_					:      Dict     =		tokenizer.encode(A			,   add_special_tokens=A      )
																		self.assertEqual(A			,   input_encoded + special_token_id      )

																		lowerCamelCase_					:      Tuple     =		tokenizer.decode(A			,   skip_special_tokens=A      )
																		self.assertTrue(special_token not in decoded      )

			def        UpperCAmelCase__ (self      ):
								lowerCamelCase_					:      Dict     =		self.get_tokenizers(do_lower_case=A      )
								for tokenizer in tokenizers:
													with self.subTest(F"""{tokenizer.__class__.__name__}"""      ):
																		lowerCamelCase_					:      Any     =		chr(0xe005      )
																		lowerCamelCase_					:      int     =		chr(0xe006      )

																		# `add_tokens` method stores special tokens only in `tokenizer.unique_no_split_tokens`. (in tokenization_utils.py)
																		tokenizer.add_tokens([SPECIAL_TOKEN_1]			,   special_tokens=A      )
																		# `add_special_tokens` method stores special tokens in `tokenizer.additional_special_tokens`,
																		# which also occur in `tokenizer.all_special_tokens`. (in tokenization_utils_base.py)
																		tokenizer.add_special_tokens({'''additional_special_tokens''': [SPECIAL_TOKEN_2]}      )

																		lowerCamelCase_					:      List[str]     =		tokenizer.tokenize(A      )
																		lowerCamelCase_					:      Dict     =		tokenizer.tokenize(A      )

																		self.assertEqual(len(A      )			,   1      )
																		self.assertEqual(len(A      )			,   1      )
																		self.assertEqual(token_a[0]			,   A      )
																		self.assertEqual(token_a[0]			,   A      )

			@require_tokenizers
			def        UpperCAmelCase__ (self      ):
								lowerCamelCase_					:      int     =		self.get_tokenizers(do_lower_case=A      )
								for tokenizer in tokenizers:
													with self.subTest(F"""{tokenizer.__class__.__name__}"""      ):
																		# a special token for Canine can be defined as follows:
																		lowerCamelCase_					:      int     =		0xe006
																		lowerCamelCase_					:      List[str]     =		chr(A      )

																		lowerCamelCase_					:      Optional[int]     =		AddedToken(A			,   lstrip=A      )
																		tokenizer.add_special_tokens({'''additional_special_tokens''': [new_token]}      )

																		with tempfile.TemporaryDirectory() as tmp_dir_name:
																							tokenizer.save_pretrained(A      )
																							tokenizer.from_pretrained(A      )

			def        UpperCAmelCase__ (self      ):
								lowerCamelCase_					:      Dict     =		[]
								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(A      )

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

																		with open(os.path.join(A			,   '''tokenizer_config.json'''      )			,   encoding='''utf-8'''      ) as json_file:
																							lowerCamelCase_					:      List[str]     =		json.load(A      )

																		# a special token for Canine can be defined as follows:
																		lowerCamelCase_					:      Tuple     =		0xe006
																		lowerCamelCase_					:      Optional[int]     =		chr(A      )

																		lowerCamelCase_					:      List[str]     =		[new_token_a]
																		lowerCamelCase_					:      Tuple     =		[new_token_a]

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

																		# 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
																		lowerCamelCase_					:      Union[str, Any]     =		tokenizer_class.from_pretrained(A			,   extra_ids=0      )
																		self.assertIn(A			,   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(
																		    [new_token_a]			,   tokenizer_without_change_in_init.convert_ids_to_tokens(
																		        tokenizer_without_change_in_init.convert_tokens_to_ids([new_token_a]      )      )			,   )

																		lowerCamelCase_					:      str     =		0xe007
																		lowerCamelCase_					:      Any     =		chr(A      )
																		# Now we test that we can change the value of additional_special_tokens in the from_pretrained
																		lowerCamelCase_					:      int     =		[AddedToken(A			,   lstrip=A      )]
																		lowerCamelCase_					:      int     =		tokenizer_class.from_pretrained(
																		    A			,   additional_special_tokens=A			,   extra_ids=0      )

																		self.assertIn(A			,   tokenizer.additional_special_tokens      )
																		# self.assertIn(new_token_2,tokenizer.get_vocab()) # ByT5Tokenization no vocab
																		self.assertEqual(
																		    [new_token_a]			,   tokenizer.convert_ids_to_tokens(tokenizer.convert_tokens_to_ids([new_token_a]      )      )      )

			@require_tokenizers
			def        UpperCAmelCase__ (self      ):
								lowerCamelCase_					:      str     =		self.get_tokenizers(do_lower_case=A      )
								for tokenizer in tokenizers:
													with self.subTest(F"""{tokenizer.__class__.__name__}"""      ):
																		lowerCamelCase_					:      Dict     =		'''hello world'''
																		if self.space_between_special_tokens:
																							lowerCamelCase_					:      Any     =		'''[CLS] hello world [SEP]'''
																		else:
																							lowerCamelCase_					:      Dict     =		input
																		lowerCamelCase_					:      Dict     =		tokenizer.encode(A			,   add_special_tokens=A      )
																		lowerCamelCase_					:      str     =		tokenizer.decode(A			,   spaces_between_special_tokens=self.space_between_special_tokens      )
																		self.assertIn(A			,   [output, output.lower()]      )

			def        UpperCAmelCase__ (self      ):
								lowerCamelCase_					:      List[Any]     =		self.get_tokenizers()
								for tokenizer in tokenizers:
													with self.subTest(F"""{tokenizer.__class__.__name__}"""      ):
																		lowerCamelCase_					:      int     =		[
																		    '''bos_token''',
																		    '''eos_token''',
																		    '''unk_token''',
																		    '''sep_token''',
																		    '''pad_token''',
																		    '''cls_token''',
																		    '''mask_token''',
																		]

								lowerCamelCase_					:      Any     =		'''a'''
								lowerCamelCase_					:      int     =		ord(A      )

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

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

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

								lowerCamelCase_					:      str     =		0xe006
								lowerCamelCase_					:      List[str]     =		chr(A      )
								setattr(A			,   '''additional_special_tokens_ids'''			,   [additional_special_token_id]      )
								self.assertListEqual(getattr(A			,   '''additional_special_tokens'''      )			,   [additional_special_token]      )
								self.assertListEqual(getattr(A			,   '''additional_special_tokens_ids'''      )			,   [additional_special_token_id]      )

			def        UpperCAmelCase__ (self      ):
								pass

			def        UpperCAmelCase__ (self      ):
								pass

			def        UpperCAmelCase__ (self      ):
								pass

			def        UpperCAmelCase__ (self      ):
								pass

			def        UpperCAmelCase__ (self      ):
								pass

			def        UpperCAmelCase__ (self      ):
								pass

			def        UpperCAmelCase__ (self      ):
								pass






			def        UpperCAmelCase__ (self      ):
								pass





'''simple docstring'''


from typing import TYPE_CHECKING

from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_sentencepiece_available


__lowercase							:   List[Any]					=     {}


try:
					if not is_sentencepiece_available():
										raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
					pass
else:
					__lowercase							:   List[Any]					=     ['''MLukeTokenizer''']

if TYPE_CHECKING:
					try:
										if not is_sentencepiece_available():
															raise OptionalDependencyNotAvailable()
					except OptionalDependencyNotAvailable:
										pass
					else:
										from .tokenization_mluke import MLukeTokenizer


else:
					import sys

					__lowercase							:   List[str]					=     _LazyModule(__name__, globals()['''__file__'''], _import_structure, module_spec=__spec__)


