






"""simple docstring"""







import random
import shutil
import tempfile
import unittest

import numpy as np

from transformers import TaTokenizer, TaTokenizerFast
from transformers.testing_utils import require_sentencepiece, require_torch
from transformers.utils.import_utils import is_speech_available, is_torch_available


if is_torch_available():
 pass

if is_speech_available():
 from transformers import EncodecFeatureExtractor, MusicgenProcessor


lowerCAmelCase_		:			Any				   =					random.Random()






def 					_lowerCAmelCase				(					lowerCAmelCase		,					lowerCAmelCase=1.0		,					lowerCAmelCase=None		,					lowerCAmelCase=None						):







       '''simple docstring'''
       if rng is None:
              UpperCAmelCase					=	global_rng

       UpperCAmelCase					=	[]
       for batch_idx in range(shape[0]						):
              values.append([]						)
              for _ in range(shape[1]						):
                     values[-1].append(rng.random() * scale						)

       return values





@require_torch
@require_sentencepiece
class      UpperCamelCase_       (				unittest.TestCase     ):



  def 						UpperCamelCase_ (					self )	->	str:



         """simple docstring"""





         UpperCAmelCase					=	"""facebook/musicgen-small"""
         UpperCAmelCase					=	tempfile.mkdtemp()



  def 						UpperCamelCase_ (					self       ,						**snake_case__ )	->	Optional[int]:



         """simple docstring"""





         return TaTokenizer.from_pretrained(self.checkpoint       ,						**snake_case__ )



  def 						UpperCamelCase_ (					self       ,						**snake_case__ )	->	Optional[int]:



         """simple docstring"""





         return EncodecFeatureExtractor.from_pretrained(self.checkpoint       ,						**snake_case__ )



  def 						UpperCamelCase_ (					self )	->	int:



         """simple docstring"""





         shutil.rmtree(self.tmpdirname )



  def 						UpperCamelCase_ (					self )	->	Any:



         """simple docstring"""





         UpperCAmelCase					=	self.get_tokenizer()
         UpperCAmelCase					=	self.get_feature_extractor()

         UpperCAmelCase					=	MusicgenProcessor(tokenizer=snake_case__       ,						feature_extractor=snake_case__ )

         processor.save_pretrained(self.tmpdirname )
         UpperCAmelCase					=	MusicgenProcessor.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 						UpperCamelCase_ (					self )	->	List[Any]:



         """simple docstring"""





         UpperCAmelCase					=	MusicgenProcessor(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					=	MusicgenProcessor.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 						UpperCamelCase_ (					self )	->	Any:



         """simple docstring"""





         UpperCAmelCase					=	self.get_feature_extractor()
         UpperCAmelCase					=	self.get_tokenizer()

         UpperCAmelCase					=	MusicgenProcessor(tokenizer=snake_case__       ,						feature_extractor=snake_case__ )

         UpperCAmelCase					=	floats_list((3, 10_00) )

         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 						UpperCamelCase_ (					self )	->	Any:



         """simple docstring"""





         UpperCAmelCase					=	self.get_feature_extractor()
         UpperCAmelCase					=	self.get_tokenizer()

         UpperCAmelCase					=	MusicgenProcessor(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 						UpperCamelCase_ (					self )	->	Optional[int]:



         """simple docstring"""





         UpperCAmelCase					=	self.get_feature_extractor()
         UpperCAmelCase					=	self.get_tokenizer()

         UpperCAmelCase					=	MusicgenProcessor(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(sequences=snake_case__ )
         UpperCAmelCase					=	tokenizer.batch_decode(snake_case__ )

         self.assertListEqual(snake_case__       ,						snake_case__ )



  def 						UpperCamelCase_ (					self )	->	str:



         """simple docstring"""





         UpperCAmelCase					=	self.get_feature_extractor()
         UpperCAmelCase					=	self.get_tokenizer()

         UpperCAmelCase					=	MusicgenProcessor(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"""       ,						)



  def 						UpperCamelCase_ (					self )	->	List[Any]:



         """simple docstring"""





         UpperCAmelCase					=	self.get_feature_extractor(padding_side="""left""" )
         UpperCAmelCase					=	self.get_tokenizer()

         UpperCAmelCase					=	MusicgenProcessor(tokenizer=snake_case__       ,						feature_extractor=snake_case__ )

         UpperCAmelCase					=	[floats_list((1, x) )[0] for x in range(5       ,						20       ,						5 )]
         UpperCAmelCase					=	processor(snake_case__ ).padding_mask

         UpperCAmelCase					=	np.asarray(floats_list((3, 20) ) )[:, None, :]
         UpperCAmelCase					=	processor.batch_decode(snake_case__       ,						padding_mask=snake_case__ )

         self.assertIsInstance(snake_case__       ,						snake_case__ )

         for audio in decoded_audios:
                self.assertIsInstance(snake_case__       ,						np.ndarray )

         self.assertTrue(decoded_audios[0].shape == (1, 10) )
         self.assertTrue(decoded_audios[1].shape == (1, 15) )
         self.assertTrue(decoded_audios[2].shape == (1, 20) )






import inspect
import json
import os
import tempfile
import unittest

from transformers.models.speech_to_text_a import SpeechaTextaTokenizer
from transformers.models.speech_to_text_a.tokenization_speech_to_text_a import VOCAB_FILES_NAMES

from ...test_tokenization_common import TokenizerTesterMixin
class 				__snake_case     (_a  ,		unittest.TestCase						):
				lowerCAmelCase__			=   SpeechaTextaTokenizer
				lowerCAmelCase__			=   False



				def 					SCREAMING_SNAKE_CASE				(					self					:						Optional[int]					)     ->			Optional[int]:





								'''simple docstring'''




								super().setUp()

								_lowerCAmelCase			:			Optional[int]        =					"""<s> <pad> </s> <unk> here@@ a couple of@@ words for the he@@ re@@ vocab""".split(""" """					)
								_lowerCAmelCase			:			Optional[int]        =					["""he re</w> 123""", """here a 1456"""]
								_lowerCAmelCase			:			Union[str, Any]        =					dict(zip(_UpperCAmelCase						,		range(len(_UpperCAmelCase					)					)					)					)

								_lowerCAmelCase			:			Any        =					{"""pad_token""": """<pad>""", """unk_token""": """<unk>""", """bos_token""": """<s>""", """eos_token""": """</s>"""}

								_lowerCAmelCase			:			Union[str, Any]        =					tempfile.mkdtemp()
								_lowerCAmelCase			:			Tuple        =					os.path.join(self.tmpdirname						,		VOCAB_FILES_NAMES["""vocab_file"""]					)
								_lowerCAmelCase			:			Any        =					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(_UpperCAmelCase					) + """\n"""					)

								with open(self.merges_file						,		"""w"""					) as fp:
												fp.write("""\n""".join(_UpperCAmelCase					)					)



				def 					SCREAMING_SNAKE_CASE				(					self					:						int					)     ->			Any:





								'''simple docstring'''




								_lowerCAmelCase			:			List[str]        =					list(self.get_tokenizer().get_vocab().keys()					)

								self.assertEqual(vocab_keys[0]						,		"""<s>"""					)
								self.assertEqual(vocab_keys[1]						,		"""<pad>"""					)
								self.assertEqual(vocab_keys[-1]						,		"""vocab"""					)
								self.assertEqual(len(_UpperCAmelCase					)						,		14					)



				def 					SCREAMING_SNAKE_CASE				(					self					:						Any					)     ->			int:





								'''simple docstring'''




								self.assertEqual(self.get_tokenizer().vocab_size						,		14					)



				def 					SCREAMING_SNAKE_CASE				(					self					:						str					)     ->			Tuple:





								'''simple docstring'''




								_lowerCAmelCase			:			List[Any]        =					SpeechaTextaTokenizer.from_pretrained(self.tmpdirname					)

								# make sure @@ is correctly concatenated
								_lowerCAmelCase			:			int        =					[4, 6, 8, 7, 10]  # ["here@@", "couple", "words", "of@@", "the"]
								_lowerCAmelCase			:			List[Any]        =					tokenizer.decode(_UpperCAmelCase					)

								self.assertTrue(output_string == """herecouple words ofthe"""					)



				def 					SCREAMING_SNAKE_CASE				(					self					:						Dict					)     ->			Any:





								'''simple docstring'''




								_lowerCAmelCase			:			str        =					SpeechaTextaTokenizer.from_pretrained(self.tmpdirname					)

								with tempfile.TemporaryDirectory() as tmp_dirname:
												tokenizer.save_pretrained(_UpperCAmelCase					)
												os.remove(os.path.join(_UpperCAmelCase						,		"""merges.txt"""					)					)

												# load tokenizer without merges file should not throw an error
												_lowerCAmelCase			:			Any        =					SpeechaTextaTokenizer.from_pretrained(_UpperCAmelCase					)

								with tempfile.TemporaryDirectory() as tmp_dirname:
												# save tokenizer and load again
												tokenizer.save_pretrained(_UpperCAmelCase					)
												_lowerCAmelCase			:			int        =					SpeechaTextaTokenizer.from_pretrained(_UpperCAmelCase					)

								self.assertIsNotNone(_UpperCAmelCase					)



				def 					SCREAMING_SNAKE_CASE				(					self					:						Optional[Any]					)     ->			Optional[Any]:





								'''simple docstring'''




								if not self.test_slow_tokenizer:
												return

								_lowerCAmelCase			:			Dict        =					inspect.signature(self.tokenizer_class.__init__					)
								_lowerCAmelCase			:			Union[str, Any]        =					self.get_tokenizer()

								for parameter_name, parameter in signature.parameters.items():
												if parameter.default != inspect.Parameter.empty and parameter_name != "merges_file":
																self.assertIn(_UpperCAmelCase						,		tokenizer.init_kwargs					)

