


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						 =	random.Random()




def      a_				(   SCREAMING_SNAKE_CASE__ :				Tuple		,      SCREAMING_SNAKE_CASE__ :				str=1.0		,      SCREAMING_SNAKE_CASE__ :				Optional[Any]=None		,      SCREAMING_SNAKE_CASE__ :				Dict=None					):
       '''simple docstring'''





       if rng is None:
              _lowerCamelCase	:		int          =global_rng

       _lowerCamelCase	:		List[str]          =[]
       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 A  (       unittest.TestCase					):






      def 	lowerCamelCase	( self						:					Tuple			) ->						str:
             """simple docstring"""




             _lowerCamelCase	:		int          ='facebook/musicgen-small'
             _lowerCamelCase	:		Union[str, Any]          =tempfile.mkdtemp()






      def 	lowerCamelCase	( self						:					str      ,       **lowercase_						:					str			) ->						Dict:
             """simple docstring"""




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






      def 	lowerCamelCase	( self						:					str      ,       **lowercase_						:					Optional[Any]			) ->						List[str]:
             """simple docstring"""




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






      def 	lowerCamelCase	( self						:					Dict			) ->						List[Any]:
             """simple docstring"""




             shutil.rmtree(self.tmpdirname			)






      def 	lowerCamelCase	( self						:					Tuple			) ->						str:
             """simple docstring"""




             _lowerCamelCase	:		List[str]          =self.get_tokenizer()
             _lowerCamelCase	:		Optional[int]          =self.get_feature_extractor()

             _lowerCamelCase	:		Dict          =MusicgenProcessor(tokenizer=lowercase_      ,       feature_extractor=lowercase_			)

             processor.save_pretrained(self.tmpdirname			)
             _lowerCamelCase	:		List[str]          =MusicgenProcessor.from_pretrained(self.tmpdirname			)

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

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






      def 	lowerCamelCase	( self						:					List[str]			) ->						int:
             """simple docstring"""




             _lowerCamelCase	:		Optional[Any]          =MusicgenProcessor(tokenizer=self.get_tokenizer()      ,       feature_extractor=self.get_feature_extractor()			)
             processor.save_pretrained(self.tmpdirname			)

             _lowerCamelCase	:		Tuple          =self.get_tokenizer(bos_token='(BOS)'      ,       eos_token='(EOS)'			)
             _lowerCamelCase	:		Optional[int]          =self.get_feature_extractor(do_normalize=lowercase_      ,       padding_value=1.0			)

             _lowerCamelCase	:		List[str]          =MusicgenProcessor.from_pretrained(
                 self.tmpdirname      ,       bos_token='(BOS)'      ,       eos_token='(EOS)'      ,       do_normalize=lowercase_      ,       padding_value=1.0			)

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

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






      def 	lowerCamelCase	( self						:					Optional[Any]			) ->						Any:
             """simple docstring"""




             _lowerCamelCase	:		Optional[int]          =self.get_feature_extractor()
             _lowerCamelCase	:		List[str]          =self.get_tokenizer()

             _lowerCamelCase	:		str          =MusicgenProcessor(tokenizer=lowercase_      ,       feature_extractor=lowercase_			)

             _lowerCamelCase	:		Union[str, Any]          =floats_list((3, 1000)			)

             _lowerCamelCase	:		Union[str, Any]          =feature_extractor(lowercase_      ,       return_tensors='np'			)
             _lowerCamelCase	:		Optional[int]          =processor(lowercase_      ,       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						:					Optional[int]			) ->						List[str]:
             """simple docstring"""




             _lowerCamelCase	:		List[Any]          =self.get_feature_extractor()
             _lowerCamelCase	:		List[str]          =self.get_tokenizer()

             _lowerCamelCase	:		Optional[int]          =MusicgenProcessor(tokenizer=lowercase_      ,       feature_extractor=lowercase_			)

             _lowerCamelCase	:		Dict          ='This is a test string'

             _lowerCamelCase	:		Union[str, Any]          =processor(text=lowercase_			)

             _lowerCamelCase	:		Optional[int]          =tokenizer(lowercase_			)

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






      def 	lowerCamelCase	( self						:					List[str]			) ->						int:
             """simple docstring"""




             _lowerCamelCase	:		Dict          =self.get_feature_extractor()
             _lowerCamelCase	:		Any          =self.get_tokenizer()

             _lowerCamelCase	:		Union[str, Any]          =MusicgenProcessor(tokenizer=lowercase_      ,       feature_extractor=lowercase_			)

             _lowerCamelCase	:		Dict          =[[1, 4, 5, 8, 1, 0, 8], [3, 4, 3, 1, 1, 8, 9]]

             _lowerCamelCase	:		Union[str, Any]          =processor.batch_decode(sequences=lowercase_			)
             _lowerCamelCase	:		List[Any]          =tokenizer.batch_decode(lowercase_			)

             self.assertListEqual(lowercase_      ,       lowercase_			)






      def 	lowerCamelCase	( self						:					List[Any]			) ->						Optional[Any]:
             """simple docstring"""




             _lowerCamelCase	:		Any          =self.get_feature_extractor()
             _lowerCamelCase	:		str          =self.get_tokenizer()

             _lowerCamelCase	:		Optional[Any]          =MusicgenProcessor(tokenizer=lowercase_      ,       feature_extractor=lowercase_			)

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






      def 	lowerCamelCase	( self						:					Dict			) ->						Tuple:
             """simple docstring"""




             _lowerCamelCase	:		Any          =self.get_feature_extractor(padding_side='left'			)
             _lowerCamelCase	:		List[str]          =self.get_tokenizer()

             _lowerCamelCase	:		Tuple          =MusicgenProcessor(tokenizer=lowercase_      ,       feature_extractor=lowercase_			)

             _lowerCamelCase	:		Any          =[floats_list((1, x)			)[0] for x in range(5      ,       20      ,       5			)]
             _lowerCamelCase	:		Dict          =processor(lowercase_			).padding_mask

             _lowerCamelCase	:		Dict          =np.asarray(floats_list((3, 20)			)			)[:, None, :]
             _lowerCamelCase	:		int          =processor.batch_decode(lowercase_      ,       padding_mask=lowercase_			)

             self.assertIsInstance(lowercase_      ,       lowercase_			)

             for audio in decoded_audios:
                    self.assertIsInstance(lowercase_      ,       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 argparse
import logging
import sys
from unittest.mock import patch

import run_glue_with_pabee

from transformers.testing_utils import TestCasePlus


logging.basicConfig(level=logging.DEBUG)

lowerCamelCase						 =	logging.getLogger()




def      a_				(   ):
       '''simple docstring'''





       _lowerCamelCase	:		Any          =argparse.ArgumentParser()
       parser.add_argument('-f'					)
       _lowerCamelCase	:		Optional[Any]          =parser.parse_args()
       return args.f




class A  (       UpperCamelCase_					):






      def 	lowerCamelCase	( self						:					List[Any]			) ->						int:
             """simple docstring"""




             _lowerCamelCase	:		Any          =logging.StreamHandler(sys.stdout			)
             logger.addHandler(lowercase_			)

             _lowerCamelCase	:		Dict          =self.get_auto_remove_tmp_dir()
             _lowerCamelCase	:		int          =F'''
            run_glue_with_pabee.py
            --model_type albert
            --model_name_or_path albert-base-v2
            --data_dir ./tests/fixtures/tests_samples/MRPC/
            --output_dir {tmp_dir}
            --overwrite_output_dir
            --task_name mrpc
            --do_train
            --do_eval
            --per_gpu_train_batch_size=2
            --per_gpu_eval_batch_size=1
            --learning_rate=2e-5
            --max_steps=50
            --warmup_steps=2
            --seed=42
            --max_seq_length=128
            '''.split()

             with patch.object(lowercase_      ,       'argv'      ,       lowercase_			):
                    _lowerCamelCase	:		Dict          =run_glue_with_pabee.main()
                    for value in result.values():
                           self.assertGreaterEqual(lowercase_      ,       0.75			)


