


import json
import os
import shutil
import tempfile
import unittest

import numpy as np
import pytest

from transformers import CLIPTokenizer, CLIPTokenizerFast
from transformers.models.clip.tokenization_clip import VOCAB_FILES_NAMES
from transformers.testing_utils import require_vision
from transformers.utils import IMAGE_PROCESSOR_NAME, is_vision_available


if is_vision_available():
	from PIL import Image

	from transformers import CLIPImageProcessor, CLIPProcessor



@require_vision
class 				A       (			unittest.TestCase				):
					'''simple docstring'''






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




							"""simple docstring"""


							lowercase__	     =						tempfile.mkdtemp()

							# fmt: off
							lowercase__	     =						["""l""", """o""", """w""", """e""", """r""", """s""", """t""", """i""", """d""", """n""", """lo""", """l</w>""", """w</w>""", """r</w>""", """t</w>""", """low</w>""", """er</w>""", """lowest</w>""", """newer</w>""", """wider""", """<unk>""", """<|startoftext|>""", """<|endoftext|>"""]
							# fmt: on
							lowercase__	     =						dict(zip(_UpperCAmelCase ,   range(len(_UpperCAmelCase						)						)						)						)
							lowercase__	     =						["""#version: 0.2""", """l o""", """lo w</w>""", """e r</w>""", """"""]
							lowercase__	     =						{"""unk_token""": """<unk>"""}

							lowercase__	     =						os.path.join(self.tmpdirname ,   VOCAB_FILES_NAMES["""vocab_file"""]						)
							lowercase__	     =						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""" ,   encoding="""utf-8"""						) as fp:
									fp.write("""\n""".join(_UpperCAmelCase						)						)

							lowercase__	     =						{
							    """do_resize""": True,
							    """size""": 20,
							    """do_center_crop""": True,
							    """crop_size""": 18,
							    """do_normalize""": True,
							    """image_mean""": [0.48_145_466, 0.4_578_275, 0.40_821_073],
							    """image_std""": [0.26_862_954, 0.26_130_258, 0.27_577_711],
							}
							lowercase__	     =						os.path.join(self.tmpdirname ,   _UpperCAmelCase						)
							with open(self.image_processor_file ,   """w""" ,   encoding="""utf-8"""						) as fp:
									json.dump(_UpperCAmelCase ,   _UpperCAmelCase						)

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




							"""simple docstring"""


							return CLIPTokenizer.from_pretrained(self.tmpdirname ,   **_UpperCAmelCase						)

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




							"""simple docstring"""


							return CLIPTokenizerFast.from_pretrained(self.tmpdirname ,   **_UpperCAmelCase						)

					def     lowerCamelCase__	(self       :		Union[str, Any] ,   **_UpperCAmelCase       :		str						)		->  Union[str, Any]:




							"""simple docstring"""


							return CLIPImageProcessor.from_pretrained(self.tmpdirname ,   **_UpperCAmelCase						)

					def     lowerCamelCase__	(self       :		Dict						)		->  Union[str, Any]:




							"""simple docstring"""


							shutil.rmtree(self.tmpdirname						)

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




							"""simple docstring"""


							lowercase__	     =						[np.random.randint(255 ,   size=(3, 30, 400) ,   dtype=np.uinta						)]

							lowercase__	     =						[Image.fromarray(np.moveaxis(_UpperCAmelCase ,   0 ,   -1						)						) for x in image_inputs]

							return image_inputs

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




							"""simple docstring"""


							lowercase__	     =						self.get_tokenizer()
							lowercase__	     =						self.get_rust_tokenizer()
							lowercase__	     =						self.get_image_processor()

							lowercase__	     =						CLIPProcessor(tokenizer=_UpperCAmelCase ,   image_processor=_UpperCAmelCase						)
							processor_slow.save_pretrained(self.tmpdirname						)
							lowercase__	     =						CLIPProcessor.from_pretrained(self.tmpdirname ,   use_fast=_UpperCAmelCase						)

							lowercase__	     =						CLIPProcessor(tokenizer=_UpperCAmelCase ,   image_processor=_UpperCAmelCase						)
							processor_fast.save_pretrained(self.tmpdirname						)
							lowercase__	     =						CLIPProcessor.from_pretrained(self.tmpdirname						)

							self.assertEqual(processor_slow.tokenizer.get_vocab() ,   tokenizer_slow.get_vocab()						)
							self.assertEqual(processor_fast.tokenizer.get_vocab() ,   tokenizer_fast.get_vocab()						)
							self.assertEqual(tokenizer_slow.get_vocab() ,   tokenizer_fast.get_vocab()						)
							self.assertIsInstance(processor_slow.tokenizer ,   _UpperCAmelCase						)
							self.assertIsInstance(processor_fast.tokenizer ,   _UpperCAmelCase						)

							self.assertEqual(processor_slow.image_processor.to_json_string() ,   image_processor.to_json_string()						)
							self.assertEqual(processor_fast.image_processor.to_json_string() ,   image_processor.to_json_string()						)
							self.assertIsInstance(processor_slow.image_processor ,   _UpperCAmelCase						)
							self.assertIsInstance(processor_fast.image_processor ,   _UpperCAmelCase						)

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




							"""simple docstring"""


							lowercase__	     =						CLIPProcessor(tokenizer=self.get_tokenizer() ,   image_processor=self.get_image_processor()						)
							processor.save_pretrained(self.tmpdirname						)

							lowercase__	     =						self.get_tokenizer(bos_token="""(BOS)""" ,   eos_token="""(EOS)"""						)
							lowercase__	     =						self.get_image_processor(do_normalize=_UpperCAmelCase ,   padding_value=1.0						)

							lowercase__	     =						CLIPProcessor.from_pretrained(
							    self.tmpdirname ,   bos_token="""(BOS)""" ,   eos_token="""(EOS)""" ,   do_normalize=_UpperCAmelCase ,   padding_value=1.0						)

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

							self.assertEqual(processor.image_processor.to_json_string() ,   image_processor_add_kwargs.to_json_string()						)
							self.assertIsInstance(processor.image_processor ,   _UpperCAmelCase						)

					def     lowerCamelCase__	(self       :		str						)		->  Tuple:




							"""simple docstring"""


							lowercase__	     =						self.get_image_processor()
							lowercase__	     =						self.get_tokenizer()

							lowercase__	     =						CLIPProcessor(tokenizer=_UpperCAmelCase ,   image_processor=_UpperCAmelCase						)

							lowercase__	     =						self.prepare_image_inputs()

							lowercase__	     =						image_processor(_UpperCAmelCase ,   return_tensors="""np"""						)
							lowercase__	     =						processor(images=_UpperCAmelCase ,   return_tensors="""np"""						)

							for key in input_image_proc.keys():
									self.assertAlmostEqual(input_image_proc[key].sum() ,   input_processor[key].sum() ,   delta=1E-2						)

					def     lowerCamelCase__	(self       :		Tuple						)		->  str:




							"""simple docstring"""


							lowercase__	     =						self.get_image_processor()
							lowercase__	     =						self.get_tokenizer()

							lowercase__	     =						CLIPProcessor(tokenizer=_UpperCAmelCase ,   image_processor=_UpperCAmelCase						)

							lowercase__	     =						"""lower newer"""

							lowercase__	     =						processor(text=_UpperCAmelCase						)

							lowercase__	     =						tokenizer(_UpperCAmelCase						)

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

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




							"""simple docstring"""


							lowercase__	     =						self.get_image_processor()
							lowercase__	     =						self.get_tokenizer()

							lowercase__	     =						CLIPProcessor(tokenizer=_UpperCAmelCase ,   image_processor=_UpperCAmelCase						)

							lowercase__	     =						"""lower newer"""
							lowercase__	     =						self.prepare_image_inputs()

							lowercase__	     =						processor(text=_UpperCAmelCase ,   images=_UpperCAmelCase						)

							self.assertListEqual(list(inputs.keys()						) ,   ["""input_ids""", """attention_mask""", """pixel_values"""]						)

							# test if it raises when no input is passed
							with pytest.raises(_UpperCAmelCase						):
									processor()

					def     lowerCamelCase__	(self       :		int						)		->  Dict:




							"""simple docstring"""


							lowercase__	     =						self.get_image_processor()
							lowercase__	     =						self.get_tokenizer()

							lowercase__	     =						CLIPProcessor(tokenizer=_UpperCAmelCase ,   image_processor=_UpperCAmelCase						)

							lowercase__	     =						[[1, 4, 5, 8, 1, 0, 8], [3, 4, 3, 1, 1, 8, 9]]

							lowercase__	     =						processor.batch_decode(_UpperCAmelCase						)
							lowercase__	     =						tokenizer.batch_decode(_UpperCAmelCase						)

							self.assertListEqual(_UpperCAmelCase ,   _UpperCAmelCase						)


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




							"""simple docstring"""


							lowercase__	     =						self.get_image_processor()
							lowercase__	     =						self.get_tokenizer()

							lowercase__	     =						CLIPProcessor(tokenizer=_UpperCAmelCase ,   image_processor=_UpperCAmelCase						)

							lowercase__	     =						"""lower newer"""
							lowercase__	     =						self.prepare_image_inputs()

							lowercase__	     =						processor(text=_UpperCAmelCase ,   images=_UpperCAmelCase						)

							self.assertListEqual(list(inputs.keys()						) ,   processor.model_input_names						)





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()						)

