



import json
import os
import shutil
import tempfile
import unittest

from transformers.models.wavaveca import WavaVecaCTCTokenizer, WavaVecaFeatureExtractor, WavaVecaProcessor
from transformers.models.wavaveca.tokenization_wavaveca import VOCAB_FILES_NAMES
from transformers.utils import FEATURE_EXTRACTOR_NAME

from .test_feature_extraction_wavaveca import floats_list


class    _lowercase (unittest.TestCase   ):
				'''simple docstring'''







				def    _lowerCamelCase       (			self     ):

									'''simple docstring'''


									UpperCamelCase_			= "<pad> <s> </s> <unk> | E T A O N I H S R D L U M W C F G Y P B V K ' X J Q Z".split(" "     )
									UpperCamelCase_			= dict(zip(snake_case__  ,			range(len(snake_case__     )     )     )     )

									UpperCamelCase_			= {
									    "pad_token": "<pad>",
									    "unk_token": "<unk>",
									    "bos_token": "<s>",
									    "eos_token": "</s>",
									}
									UpperCamelCase_			= {
									    "feature_size": 1,
									    "padding_value": 0.0,
									    "sampling_rate": 1_6000,
									    "return_attention_mask": False,
									    "do_normalize": True,
									}

									UpperCamelCase_			= tempfile.mkdtemp()
									UpperCamelCase_			= os.path.join(self.tmpdirname  ,			VOCAB_FILES_NAMES["vocab_file"]     )
									UpperCamelCase_			= os.path.join(self.tmpdirname  ,			snake_case__     )
									with open(self.vocab_file  ,			"w"  ,			encoding="utf-8"     ) as fp:
														fp.write(json.dumps(snake_case__     ) + "\n"     )

									with open(self.feature_extraction_file  ,			"w"  ,			encoding="utf-8"     ) as fp:
														fp.write(json.dumps(snake_case__     ) + "\n"     )

				def    _lowerCamelCase       (			self  ,			**snake_case__     ):

									'''simple docstring'''


									UpperCamelCase_			= self.add_kwargs_tokens_map.copy()
									kwargs.update(snake_case__     )
									return WavaVecaCTCTokenizer.from_pretrained(self.tmpdirname  ,			**snake_case__     )

				def    _lowerCamelCase       (			self  ,			**snake_case__     ):

									'''simple docstring'''


									return WavaVecaFeatureExtractor.from_pretrained(self.tmpdirname  ,			**snake_case__     )

				def    _lowerCamelCase       (			self     ):

									'''simple docstring'''


									shutil.rmtree(self.tmpdirname     )

				def    _lowerCamelCase       (			self     ):

									'''simple docstring'''


									UpperCamelCase_			= self.get_tokenizer()
									UpperCamelCase_			= self.get_feature_extractor()

									UpperCamelCase_			= WavaVecaProcessor(tokenizer=snake_case__  ,			feature_extractor=snake_case__     )

									processor.save_pretrained(self.tmpdirname     )
									UpperCamelCase_			= WavaVecaProcessor.from_pretrained(self.tmpdirname     )

									self.assertEqual(processor.tokenizer.get_vocab()  ,			tokenizer.get_vocab()     )
									self.assertIsInstance(processor.tokenizer  ,			snake_case__     )

									self.assertEqual(processor.feature_extractor.to_json_string()  ,			feature_extractor.to_json_string()     )
									self.assertIsInstance(processor.feature_extractor  ,			snake_case__     )

				def    _lowerCamelCase       (			self     ):

									'''simple docstring'''


									UpperCamelCase_			= WavaVecaProcessor(tokenizer=self.get_tokenizer()  ,			feature_extractor=self.get_feature_extractor()     )
									processor.save_pretrained(self.tmpdirname     )

									UpperCamelCase_			= self.get_tokenizer(bos_token="(BOS)"  ,			eos_token="(EOS)"     )
									UpperCamelCase_			= self.get_feature_extractor(do_normalize=snake_case__  ,			padding_value=1.0     )

									UpperCamelCase_			= WavaVecaProcessor.from_pretrained(
									    self.tmpdirname  ,			bos_token="(BOS)"  ,			eos_token="(EOS)"  ,			do_normalize=snake_case__  ,			padding_value=1.0     )

									self.assertEqual(processor.tokenizer.get_vocab()  ,			tokenizer_add_kwargs.get_vocab()     )
									self.assertIsInstance(processor.tokenizer  ,			snake_case__     )

									self.assertEqual(processor.feature_extractor.to_json_string()  ,			feature_extractor_add_kwargs.to_json_string()     )
									self.assertIsInstance(processor.feature_extractor  ,			snake_case__     )

				def    _lowerCamelCase       (			self     ):

									'''simple docstring'''


									UpperCamelCase_			= self.get_feature_extractor()
									UpperCamelCase_			= self.get_tokenizer()

									UpperCamelCase_			= WavaVecaProcessor(tokenizer=snake_case__  ,			feature_extractor=snake_case__     )

									UpperCamelCase_			= floats_list((3, 1000)     )

									UpperCamelCase_			= feature_extractor(snake_case__  ,			return_tensors="np"     )
									UpperCamelCase_			= processor(snake_case__  ,			return_tensors="np"     )

									for key in input_feat_extract.keys():
														self.assertAlmostEqual(input_feat_extract[key].sum()  ,			input_processor[key].sum()  ,			delta=1e-2     )

				def    _lowerCamelCase       (			self     ):

									'''simple docstring'''


									UpperCamelCase_			= self.get_feature_extractor()
									UpperCamelCase_			= self.get_tokenizer()

									UpperCamelCase_			= WavaVecaProcessor(tokenizer=snake_case__  ,			feature_extractor=snake_case__     )

									UpperCamelCase_			= "This is a test string"

									UpperCamelCase_			= processor(text=snake_case__     )

									UpperCamelCase_			= tokenizer(snake_case__     )

									for key in encoded_tok.keys():
														self.assertListEqual(encoded_tok[key]  ,			encoded_processor[key]     )

				def    _lowerCamelCase       (			self     ):

									'''simple docstring'''


									UpperCamelCase_			= self.get_feature_extractor()
									UpperCamelCase_			= self.get_tokenizer()

									UpperCamelCase_			= WavaVecaProcessor(tokenizer=snake_case__  ,			feature_extractor=snake_case__     )

									UpperCamelCase_			= [[1, 4, 5, 8, 1, 0, 8], [3, 4, 3, 1, 1, 8, 9]]

									UpperCamelCase_			= processor.batch_decode(snake_case__     )
									UpperCamelCase_			= tokenizer.batch_decode(snake_case__     )

									self.assertListEqual(snake_case__  ,			snake_case__     )

				def    _lowerCamelCase       (			self     ):

									'''simple docstring'''


									UpperCamelCase_			= self.get_feature_extractor()
									UpperCamelCase_			= self.get_tokenizer()

									UpperCamelCase_			= WavaVecaProcessor(tokenizer=snake_case__  ,			feature_extractor=snake_case__     )

									self.assertListEqual(
									    processor.model_input_names  ,			feature_extractor.model_input_names  ,			msg="`processor` and `feature_extractor` model input names do not match"  ,			)





import json
import os
import unittest

from transformers import HerbertTokenizer, HerbertTokenizerFast
from transformers.models.herbert.tokenization_herbert import VOCAB_FILES_NAMES
from transformers.testing_utils import get_tests_dir, require_tokenizers, slow

from ...test_tokenization_common import TokenizerTesterMixin

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




			'''simple docstring'''






			UpperCamelCase     		=			HerbertTokenizer
			UpperCamelCase     		=			HerbertTokenizerFast
			UpperCamelCase     		=			True




			def 					snake_case__	(  self				:					Tuple					):
					'''simple docstring'''





					super().setUp()

					# Use a simpler test file without japanese/chinese characters
					with open(F'{get_tests_dir()}/fixtures/sample_text_no_unicode.txt'			,			encoding='''utf-8'''					) as f_data:
							__UpperCAmelCase       :	List[str]						=      f_data.read().replace('''\n\n'''			,			'''\n'''					).strip()

					__UpperCAmelCase       :	Dict						=      [
					    '''<s>''',
					    '''</s>''',
					    '''l''',
					    '''o''',
					    '''w''',
					    '''e''',
					    '''r''',
					    '''s''',
					    '''t''',
					    '''i''',
					    '''d''',
					    '''n''',
					    '''w</w>''',
					    '''r</w>''',
					    '''t</w>''',
					    '''lo''',
					    '''low''',
					    '''er</w>''',
					    '''low</w>''',
					    '''lowest</w>''',
					    '''newer</w>''',
					    '''wider</w>''',
					    ''',</w>''',
					    '''<unk>''',
					]
					__UpperCAmelCase       :	Tuple						=      dict(zip(a_			,			range(len(a_					)					)					)					)
					__UpperCAmelCase       :	Optional[int]						=      ['''l o 123''', '''lo w 1456''', '''e r</w> 1789''', '''''']

					__UpperCAmelCase       :	str						=      os.path.join(self.tmpdirname			,			VOCAB_FILES_NAMES['''vocab_file''']					)
					__UpperCAmelCase       :	List[str]						=      os.path.join(self.tmpdirname			,			VOCAB_FILES_NAMES['''merges_file''']					)
					with open(self.vocab_file			,			'''w'''					) as fp:
							fp.write(json.dumps(a_					)					)
					with open(self.merges_file			,			'''w'''					) as fp:
							fp.write('''\n'''.join(a_					)					)




			def 					snake_case__	(  self				:					Union[str, Any]			,			a_				:					Optional[Any]					):
					'''simple docstring'''





					__UpperCAmelCase       :	List[str]						=      '''lower newer'''
					__UpperCAmelCase       :	List[Any]						=      '''lower newer'''
					return input_text, output_text




			def 					snake_case__	(  self				:					int					):
					'''simple docstring'''





					__UpperCAmelCase       :	Any						=      self.tokenizer_class(vocab_file=self.vocab_file			,			merges_file=self.merges_file					)

					__UpperCAmelCase       :	Optional[int]						=      '''lower'''
					__UpperCAmelCase       :	Any						=      ['''low''', '''er</w>''']
					__UpperCAmelCase       :	Any						=      tokenizer.tokenize(a_					)
					self.assertListEqual(a_			,			a_					)

					__UpperCAmelCase       :	int						=      tokens + ['''<unk>''']
					__UpperCAmelCase       :	Optional[Any]						=      [16, 17, 23]
					self.assertListEqual(tokenizer.convert_tokens_to_ids(a_					)			,			a_					)




			def 					snake_case__	(  self				:					List[Any]					):
					'''simple docstring'''





					if not self.test_rust_tokenizer:
							return

					__UpperCAmelCase       :	str						=      self.get_tokenizer()
					__UpperCAmelCase       :	Optional[int]						=      self.get_rust_tokenizer()

					__UpperCAmelCase       :	Tuple						=      '''lower,newer'''

					__UpperCAmelCase       :	Optional[int]						=      tokenizer.tokenize(a_					)
					__UpperCAmelCase       :	Tuple						=      rust_tokenizer.tokenize(a_					)
					self.assertListEqual(a_			,			a_					)

					__UpperCAmelCase       :	Optional[Any]						=      tokenizer.encode(a_			,			add_special_tokens=a_					)
					__UpperCAmelCase       :	Union[str, Any]						=      rust_tokenizer.encode(a_			,			add_special_tokens=a_					)
					self.assertListEqual(a_			,			a_					)

					__UpperCAmelCase       :	Tuple						=      self.get_rust_tokenizer()
					__UpperCAmelCase       :	Union[str, Any]						=      tokenizer.encode(a_					)
					__UpperCAmelCase       :	str						=      rust_tokenizer.encode(a_					)
					self.assertListEqual(a_			,			a_					)




			@slow
			def 					snake_case__	(  self				:					Tuple					):
					'''simple docstring'''





					__UpperCAmelCase       :	List[Any]						=      self.tokenizer_class.from_pretrained('''allegro/herbert-base-cased'''					)

					__UpperCAmelCase       :	Tuple						=      tokenizer.encode('''konstruowanie sekwencji'''			,			add_special_tokens=a_					)
					__UpperCAmelCase       :	int						=      tokenizer.encode('''konstruowanie wielu sekwencji'''			,			add_special_tokens=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 == [0] + text + [2]
					assert encoded_pair == [0] + text + [2] + text_a + [2]





