


'''simple docstring'''






from ...configuration_utils import PretrainedConfig
from ...utils import logging


__A						:						Any  =  logging.get_logger(__name__)

__A						:						List[str]  =  {
    'microsoft/cvt-13': 'https://huggingface.co/microsoft/cvt-13/resolve/main/config.json',
    # See all Cvt models at https://huggingface.co/models?filter=cvt
}
class     __UpperCamelCase						(    UpperCAmelCase__				):
							lowercase      :		Union[str, Any] 		=	'cvt'





							def __init__(	self		:str	,_UpperCamelCase		:str=3	,_UpperCamelCase		:str=[7, 3, 3]	,_UpperCamelCase		:Any=[4, 2, 2]	,_UpperCamelCase		:Any=[2, 1, 1]	,_UpperCamelCase		:Any=[6_4, 1_9_2, 3_8_4]	,_UpperCamelCase		:Optional[Any]=[1, 3, 6]	,_UpperCamelCase		:Tuple=[1, 2, 1_0]	,_UpperCamelCase		:List[str]=[4.0, 4.0, 4.0]	,_UpperCamelCase		:Any=[0.0, 0.0, 0.0]	,_UpperCamelCase		:Any=[0.0, 0.0, 0.0]	,_UpperCamelCase		:Optional[Any]=[0.0, 0.0, 0.1]	,_UpperCamelCase		:List[str]=[True, True, True]	,_UpperCamelCase		:str=[False, False, True]	,_UpperCamelCase		:Union[str, Any]=["dw_bn", "dw_bn", "dw_bn"]	,_UpperCamelCase		:List[Any]=[3, 3, 3]	,_UpperCamelCase		:List[str]=[1, 1, 1]	,_UpperCamelCase		:List[Any]=[2, 2, 2]	,_UpperCamelCase		:Dict=[1, 1, 1]	,_UpperCamelCase		:List[Any]=[1, 1, 1]	,_UpperCamelCase		:int=0.02	,_UpperCamelCase		:str=1E-1_2	,**_UpperCamelCase		:Optional[Any]	,):
									super().__init__(**_UpperCAmelCase      )
									snake_case_		:				int      							=    num_channels
									snake_case_		:				List[Any]      							=    patch_sizes
									snake_case_		:				Union[str, Any]      							=    patch_stride
									snake_case_		:				List[Any]      							=    patch_padding
									snake_case_		:				Dict      							=    embed_dim
									snake_case_		:				Optional[int]      							=    num_heads
									snake_case_		:				Union[str, Any]      							=    depth
									snake_case_		:				Dict      							=    mlp_ratio
									snake_case_		:				List[str]      							=    attention_drop_rate
									snake_case_		:				int      							=    drop_rate
									snake_case_		:				List[str]      							=    drop_path_rate
									snake_case_		:				List[str]      							=    qkv_bias
									snake_case_		:				Union[str, Any]      							=    cls_token
									snake_case_		:				Dict      							=    qkv_projection_method
									snake_case_		:				Union[str, Any]      							=    kernel_qkv
									snake_case_		:				int      							=    padding_kv
									snake_case_		:				Any      							=    stride_kv
									snake_case_		:				Optional[Any]      							=    padding_q
									snake_case_		:				List[str]      							=    stride_q
									snake_case_		:				List[Any]      							=    initializer_range
									snake_case_		:				Tuple      							=    layer_norm_eps



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 				A       (			unittest.TestCase				):
					'''simple docstring'''






					def     lowerCamelCase__	(self       :		List[Any]						)		->  List[str]:




							"""simple docstring"""


							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     lowerCamelCase__	(self       :		str ,   **_UpperCAmelCase       :		Optional[int]						)		->  str:




							"""simple docstring"""


							return AutoTokenizer.from_pretrained(self.checkpoint ,   **_UpperCAmelCase						)

					def     lowerCamelCase__	(self       :		str						)		->  List[str]:




							"""simple docstring"""


							shutil.rmtree(self.tmpdirname						)

					def     lowerCamelCase__	(self       :		Optional[int]						)		->  List[str]:




							"""simple docstring"""


							lowercase__	     =						self.get_tokenizer()

							lowercase__	     =						BarkProcessor(tokenizer=_UpperCAmelCase						)

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

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

					@slow
					def     lowerCamelCase__	(self       :		str						)		->  Tuple:




							"""simple docstring"""


							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     lowerCamelCase__	(self       :		List[str]						)		->  List[Any]:




							"""simple docstring"""


							lowercase__	     =						BarkProcessor.from_pretrained(
							    pretrained_processor_name_or_path=self.checkpoint ,   speaker_embeddings_dict_path=self.speaker_embeddings_dict_path ,   )

							lowercase__	     =						35
							lowercase__	     =						2
							lowercase__	     =						8

							lowercase__	     =						{
							    """semantic_prompt""": np.ones(_UpperCAmelCase						),
							    """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=_UpperCAmelCase						)

							lowercase__	     =						inputs["""history_prompt"""]
							for key in voice_preset:
									self.assertListEqual(voice_preset[key].tolist() ,   processed_voice_preset.get(_UpperCAmelCase ,   np.array([]						)						).tolist()						)

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

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

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


					def     lowerCamelCase__	(self       :		int						)		->  Tuple:




							"""simple docstring"""


							lowercase__	     =						self.get_tokenizer()

							lowercase__	     =						BarkProcessor(tokenizer=_UpperCAmelCase						)

							lowercase__	     =						processor(text=self.input_string						)

							lowercase__	     =						tokenizer(
							    self.input_string ,   padding="""max_length""" ,   max_length=256 ,   add_special_tokens=_UpperCAmelCase ,   return_attention_mask=_UpperCAmelCase ,   return_token_type_ids=_UpperCAmelCase ,   )

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

