
import os
import shutil
import tempfile
import unittest

import numpy as np

from transformers import AutoTokenizer, BarkProcessor
from transformers.testing_utils import require_torch, slow
@require_torch
class  lowercase__(				unittest.TestCase							):



	"""simple docstring"""




	def 						_lowercase  (       self  :			Any       )       ->     List[str]:
					lowercase_       =					'''ylacombe/bark-small'''
					lowercase_       =					tempfile.mkdtemp()
					lowercase_       =					'''en_speaker_1'''
					lowercase_       =					'''This is a test string'''
					lowercase_       =					'''speaker_embeddings_path.json'''
					lowercase_       =					'''speaker_embeddings'''
	def 						_lowercase  (       self  :			Optional[Any]       ,							**SCREAMING_SNAKE_CASE_  :			Optional[int]       )       ->     str:
					return AutoTokenizer.from_pretrained(self.checkpoint       ,							**SCREAMING_SNAKE_CASE_       )
	def 						_lowercase  (       self  :			Dict       )       ->     Tuple:
					shutil.rmtree(self.tmpdirname       )
	def 						_lowercase  (       self  :			Union[str, Any]       )       ->     Optional[Any]:
					lowercase_       =					self.get_tokenizer()

					lowercase_       =					BarkProcessor(tokenizer=SCREAMING_SNAKE_CASE_       )

					processor.save_pretrained(self.tmpdirname       )
					lowercase_       =					BarkProcessor.from_pretrained(self.tmpdirname       )

					self.assertEqual(processor.tokenizer.get_vocab()       ,							tokenizer.get_vocab()       )
	@slow
	def 						_lowercase  (       self  :			Dict       )       ->     Any:
					lowercase_       =					BarkProcessor.from_pretrained(
					    pretrained_processor_name_or_path=self.checkpoint       ,							speaker_embeddings_dict_path=self.speaker_embeddings_dict_path       ,							)
					processor.save_pretrained(
					    self.tmpdirname       ,							speaker_embeddings_dict_path=self.speaker_embeddings_dict_path       ,							speaker_embeddings_directory=self.speaker_embeddings_directory       ,							)

					lowercase_       =					self.get_tokenizer(bos_token='''(BOS)'''       ,							eos_token='''(EOS)'''       )

					lowercase_       =					BarkProcessor.from_pretrained(
					    self.tmpdirname       ,							self.speaker_embeddings_dict_path       ,							bos_token='''(BOS)'''       ,							eos_token='''(EOS)'''       ,							)

					self.assertEqual(processor.tokenizer.get_vocab()       ,							tokenizer_add_kwargs.get_vocab()       )
	def 						_lowercase  (       self  :			int       )       ->     Optional[int]:
					lowercase_       =					BarkProcessor.from_pretrained(
					    pretrained_processor_name_or_path=self.checkpoint       ,							speaker_embeddings_dict_path=self.speaker_embeddings_dict_path       ,							)

					lowercase_       =					3_5
					lowercase_       =					2
					lowercase_       =					8

					lowercase_       =					{
					    '''semantic_prompt''': np.ones(SCREAMING_SNAKE_CASE_       ),
					    '''coarse_prompt''': np.ones((nb_codebooks_coarse, seq_len)       ),
					    '''fine_prompt''': np.ones((nb_codebooks_total, seq_len)       ),
					}

					# test providing already loaded voice_preset
					lowercase_       =					processor(text=self.input_string       ,							voice_preset=SCREAMING_SNAKE_CASE_       )

					lowercase_       =					inputs['''history_prompt''']
					for key in voice_preset:
									self.assertListEqual(voice_preset[key].tolist()       ,							processed_voice_preset.get(SCREAMING_SNAKE_CASE_       ,							np.array([]       )       ).tolist()       )

					# test loading voice preset from npz file
					lowercase_       =					os.path.join(self.tmpdirname       ,							'''file.npz'''       )
					np.savez(SCREAMING_SNAKE_CASE_       ,							**SCREAMING_SNAKE_CASE_       )
					lowercase_       =					processor(text=self.input_string       ,							voice_preset=SCREAMING_SNAKE_CASE_       )
					lowercase_       =					inputs['''history_prompt''']

					for key in voice_preset:
									self.assertListEqual(voice_preset[key].tolist()       ,							processed_voice_preset.get(SCREAMING_SNAKE_CASE_       ,							np.array([]       )       ).tolist()       )

					# test loading voice preset from the hub
					lowercase_       =					processor(text=self.input_string       ,							voice_preset=self.voice_preset       )




	def 						_lowercase  (       self  :			str       )       ->     List[Any]:
					lowercase_       =					self.get_tokenizer()

					lowercase_       =					BarkProcessor(tokenizer=SCREAMING_SNAKE_CASE_       )

					lowercase_       =					processor(text=self.input_string       )

					lowercase_       =					tokenizer(
					    self.input_string       ,							padding='''max_length'''       ,							max_length=2_5_6       ,							add_special_tokens=SCREAMING_SNAKE_CASE_       ,							return_attention_mask=SCREAMING_SNAKE_CASE_       ,							return_token_type_ids=SCREAMING_SNAKE_CASE_       ,							)

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






import logging

from transformers.configuration_utils import PretrainedConfig


__a  			=					logging.getLogger(__name__)
class  lowercase__(				UpperCAmelCase							):



	"""simple docstring"""




	a			:Optional[int]         =	'masked_bert'
	def __init__(       self  :			Optional[int]       ,							SCREAMING_SNAKE_CASE_  :			List[Any]=3_0_5_2_2       ,							SCREAMING_SNAKE_CASE_  :			List[str]=7_6_8       ,							SCREAMING_SNAKE_CASE_  :			Optional[int]=1_2       ,							SCREAMING_SNAKE_CASE_  :			Any=1_2       ,							SCREAMING_SNAKE_CASE_  :			str=3_0_7_2       ,							SCREAMING_SNAKE_CASE_  :			Union[str, Any]="gelu"       ,							SCREAMING_SNAKE_CASE_  :			Optional[int]=0.1       ,							SCREAMING_SNAKE_CASE_  :			List[str]=0.1       ,							SCREAMING_SNAKE_CASE_  :			Tuple=5_1_2       ,							SCREAMING_SNAKE_CASE_  :			str=2       ,							SCREAMING_SNAKE_CASE_  :			Dict=0.02       ,							SCREAMING_SNAKE_CASE_  :			Any=1e-12       ,							SCREAMING_SNAKE_CASE_  :			Any=0       ,							SCREAMING_SNAKE_CASE_  :			Optional[int]="topK"       ,							SCREAMING_SNAKE_CASE_  :			Dict="constant"       ,							SCREAMING_SNAKE_CASE_  :			Optional[Any]=0.0       ,							**SCREAMING_SNAKE_CASE_  :			Optional[int]       ,							)       ->     Optional[Any]:
					super().__init__(pad_token_id=SCREAMING_SNAKE_CASE_       ,							**SCREAMING_SNAKE_CASE_       )

					lowercase_       =					vocab_size
					lowercase_       =					hidden_size
					lowercase_       =					num_hidden_layers
					lowercase_       =					num_attention_heads
					lowercase_       =					hidden_act
					lowercase_       =					intermediate_size
					lowercase_       =					hidden_dropout_prob
					lowercase_       =					attention_probs_dropout_prob
					lowercase_       =					max_position_embeddings
					lowercase_       =					type_vocab_size
					lowercase_       =					initializer_range
					lowercase_       =					layer_norm_eps
					lowercase_       =					pruning_method
					lowercase_       =					mask_init
					lowercase_       =					mask_scale




