






from typing import TYPE_CHECKING

from ...utils import (
    OptionalDependencyNotAvailable,
    _LazyModule,
    is_torch_available,
)


_UpperCAmelCase			:		str   				=    {
    "configuration_swiftformer": [
        "SWIFTFORMER_PRETRAINED_CONFIG_ARCHIVE_MAP",
        "SwiftFormerConfig",
        "SwiftFormerOnnxConfig",
    ]
}

try:
			if not is_torch_available():
						raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
			pass
else:
			_UpperCAmelCase			:		Optional[int]   				=    [
			    "SWIFTFORMER_PRETRAINED_MODEL_ARCHIVE_LIST",
			    "SwiftFormerForImageClassification",
			    "SwiftFormerModel",
			    "SwiftFormerPreTrainedModel",
			]

if TYPE_CHECKING:
			from .configuration_swiftformer import (
			    SWIFTFORMER_PRETRAINED_CONFIG_ARCHIVE_MAP,
			    SwiftFormerConfig,
			    SwiftFormerOnnxConfig,
			)

			try:
						if not is_torch_available():
									raise OptionalDependencyNotAvailable()
			except OptionalDependencyNotAvailable:
						pass
			else:
						from .modeling_swiftformer import (
						    SWIFTFORMER_PRETRAINED_MODEL_ARCHIVE_LIST,
						    SwiftFormerForImageClassification,
						    SwiftFormerModel,
						    SwiftFormerPreTrainedModel,
						)

else:
			import sys

			_UpperCAmelCase			:		List[str]   				=    _LazyModule(__name__, globals()["__file__"], _import_structure, module_spec=__spec__)













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  lowerCAmelCase_       (				unittest.TestCase					):




							def 						__snake_case					(   self     :   Optional[int]	):
											lowerCAmelCase__      			=						'''ylacombe/bark-small'''
											lowerCAmelCase__      			=						tempfile.mkdtemp()
											lowerCAmelCase__      			=						'''en_speaker_1'''
											lowerCAmelCase__      			=						'''This is a test string'''
											lowerCAmelCase__      			=						'''speaker_embeddings_path.json'''
											lowerCAmelCase__      			=						'''speaker_embeddings'''




							def 						__snake_case					(   self     :   Optional[Any] ,							**SCREAMING_SNAKE_CASE_     :   Optional[int]	):
											return AutoTokenizer.from_pretrained(self.checkpoint ,							**SCREAMING_SNAKE_CASE_	)




							def 						__snake_case					(   self     :   List[str]	):
											shutil.rmtree(self.tmpdirname	)




							def 						__snake_case					(   self     :   Optional[Any]	):
											lowerCAmelCase__      			=						self.get_tokenizer()

											lowerCAmelCase__      			=						BarkProcessor(tokenizer=SCREAMING_SNAKE_CASE_	)

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

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




							@slow
							def 						__snake_case					(   self     :   Any	):
											lowerCAmelCase__      			=						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 ,							)

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

											lowerCAmelCase__      			=						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 						__snake_case					(   self     :   Dict	):
											lowerCAmelCase__      			=						BarkProcessor.from_pretrained(
											    pretrained_processor_name_or_path=self.checkpoint ,							speaker_embeddings_dict_path=self.speaker_embeddings_dict_path ,							)

											lowerCAmelCase__      			=						35
											lowerCAmelCase__      			=						2
											lowerCAmelCase__      			=						8

											lowerCAmelCase__      			=						{
											    '''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
											lowerCAmelCase__      			=						processor(text=self.input_string ,							voice_preset=SCREAMING_SNAKE_CASE_	)

											lowerCAmelCase__      			=						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
											lowerCAmelCase__      			=						os.path.join(self.tmpdirname ,							'''file.npz'''	)
											np.savez(SCREAMING_SNAKE_CASE_ ,							**SCREAMING_SNAKE_CASE_	)
											lowerCAmelCase__      			=						processor(text=self.input_string ,							voice_preset=SCREAMING_SNAKE_CASE_	)
											lowerCAmelCase__      			=						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
											lowerCAmelCase__      			=						processor(text=self.input_string ,							voice_preset=self.voice_preset	)




							def 						__snake_case					(   self     :   Optional[int]	):
											lowerCAmelCase__      			=						self.get_tokenizer()

											lowerCAmelCase__      			=						BarkProcessor(tokenizer=SCREAMING_SNAKE_CASE_	)

											lowerCAmelCase__      			=						processor(text=self.input_string	)

											lowerCAmelCase__      			=						tokenizer(
											    self.input_string ,							padding='''max_length''' ,							max_length=256 ,							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()	)





