






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 		lowerCAmelCase     ( unittest.TestCase			):

					'''simple docstring'''

					def       lowerCAmelCase				(  self				:	List[str]							)			->  Union[str, Any]:


												"""simple docstring"""

												__lowercase      :							Union[str, Any]				=     tempfile.mkdtemp()

												# fmt: off
												__lowercase      :							List[str]				=     ["""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      :							Any				=     dict(zip(_A		,     range(len(_A							)							)							)							)
												__lowercase      :							str				=     ["""#version: 0.2""", """l o""", """lo w</w>""", """e r</w>""", """"""]
												__lowercase      :							List[Any]				=     {"""unk_token""": """<unk>"""}

												__lowercase      :							Tuple				=     os.path.join(self.tmpdirname		,     VOCAB_FILES_NAMES["""vocab_file"""]							)
												__lowercase      :							Any				=     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(_A							) + """\n"""							)
												with open(self.merges_file		,     """w"""		,     encoding="""utf-8"""							) as fp:
																			fp.write("""\n""".join(_A							)							)

												__lowercase      :							Optional[Any]				=     {
												    """do_resize""": True,
												    """size""": 20,
												    """do_center_crop""": True,
												    """crop_size""": 18,
												    """do_normalize""": True,
												    """image_mean""": [0.48145466, 0.4578275, 0.40821073],
												    """image_std""": [0.26862954, 0.26130258, 0.27577711],
												}
												__lowercase      :							Any				=     os.path.join(self.tmpdirname		,     _A							)
												with open(self.image_processor_file		,     """w"""		,     encoding="""utf-8"""							) as fp:
																			json.dump(_A		,     _A							)



					def       lowerCAmelCase				(  self				:	str		,     **__a				:	Union[str, Any]							)			->  List[str]:


												"""simple docstring"""

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



					def       lowerCAmelCase				(  self				:	Union[str, Any]		,     **__a				:	int							)			->  int:


												"""simple docstring"""

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



					def       lowerCAmelCase				(  self				:	Optional[Any]		,     **__a				:	int							)			->  List[str]:


												"""simple docstring"""

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



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


												"""simple docstring"""

												shutil.rmtree(self.tmpdirname							)



					def       lowerCAmelCase				(  self				:	Dict							)			->  Tuple:


												"""simple docstring"""

												__lowercase      :							List[str]				=     [np.random.randint(255		,     size=(3, 30, 400)		,     dtype=np.uinta							)]

												__lowercase      :							int				=     [Image.fromarray(np.moveaxis(_A		,     0		,     -1							)							) for x in image_inputs]

												return image_inputs



					def       lowerCAmelCase				(  self				:	int							)			->  Dict:


												"""simple docstring"""

												__lowercase      :							str				=     self.get_tokenizer()
												__lowercase      :							int				=     self.get_rust_tokenizer()
												__lowercase      :							Any				=     self.get_image_processor()

												__lowercase      :							Tuple				=     CLIPProcessor(tokenizer=_A		,     image_processor=_A							)
												processor_slow.save_pretrained(self.tmpdirname							)
												__lowercase      :							Any				=     CLIPProcessor.from_pretrained(self.tmpdirname		,     use_fast=_A							)

												__lowercase      :							Union[str, Any]				=     CLIPProcessor(tokenizer=_A		,     image_processor=_A							)
												processor_fast.save_pretrained(self.tmpdirname							)
												__lowercase      :							Optional[Any]				=     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		,     _A							)
												self.assertIsInstance(processor_fast.tokenizer		,     _A							)

												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		,     _A							)
												self.assertIsInstance(processor_fast.image_processor		,     _A							)



					def       lowerCAmelCase				(  self				:	Dict							)			->  Dict:


												"""simple docstring"""

												__lowercase      :							int				=     CLIPProcessor(tokenizer=self.get_tokenizer()		,     image_processor=self.get_image_processor()							)
												processor.save_pretrained(self.tmpdirname							)

												__lowercase      :							int				=     self.get_tokenizer(bos_token="""(BOS)"""		,     eos_token="""(EOS)"""							)
												__lowercase      :							List[str]				=     self.get_image_processor(do_normalize=_A		,     padding_value=1.0							)

												__lowercase      :							int				=     CLIPProcessor.from_pretrained(
												    self.tmpdirname		,     bos_token="""(BOS)"""		,     eos_token="""(EOS)"""		,     do_normalize=_A		,     padding_value=1.0							)

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

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



					def       lowerCAmelCase				(  self				:	Dict							)			->  List[str]:


												"""simple docstring"""

												__lowercase      :							int				=     self.get_image_processor()
												__lowercase      :							Any				=     self.get_tokenizer()

												__lowercase      :							Optional[Any]				=     CLIPProcessor(tokenizer=_A		,     image_processor=_A							)

												__lowercase      :							Dict				=     self.prepare_image_inputs()

												__lowercase      :							List[str]				=     image_processor(_A		,     return_tensors="""np"""							)
												__lowercase      :							Tuple				=     processor(images=_A		,     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				:	int							)			->  Tuple:


												"""simple docstring"""

												__lowercase      :							str				=     self.get_image_processor()
												__lowercase      :							Any				=     self.get_tokenizer()

												__lowercase      :							str				=     CLIPProcessor(tokenizer=_A		,     image_processor=_A							)

												__lowercase      :							Optional[int]				=     """lower newer"""

												__lowercase      :							List[Any]				=     processor(text=_A							)

												__lowercase      :							Union[str, Any]				=     tokenizer(_A							)

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



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


												"""simple docstring"""

												__lowercase      :							Any				=     self.get_image_processor()
												__lowercase      :							List[str]				=     self.get_tokenizer()

												__lowercase      :							List[str]				=     CLIPProcessor(tokenizer=_A		,     image_processor=_A							)

												__lowercase      :							Optional[Any]				=     """lower newer"""
												__lowercase      :							Any				=     self.prepare_image_inputs()

												__lowercase      :							Optional[Any]				=     processor(text=_A		,     images=_A							)

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

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



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


												"""simple docstring"""

												__lowercase      :							Optional[int]				=     self.get_image_processor()
												__lowercase      :							Dict				=     self.get_tokenizer()

												__lowercase      :							Optional[Any]				=     CLIPProcessor(tokenizer=_A		,     image_processor=_A							)

												__lowercase      :							Optional[int]				=     [[1, 4, 5, 8, 1, 0, 8], [3, 4, 3, 1, 1, 8, 9]]

												__lowercase      :							Optional[int]				=     processor.batch_decode(_A							)
												__lowercase      :							Any				=     tokenizer.batch_decode(_A							)

												self.assertListEqual(_A		,     _A							)



					def       lowerCAmelCase				(  self				:	Dict							)			->  Dict:


												"""simple docstring"""

												__lowercase      :							int				=     self.get_image_processor()
												__lowercase      :							Any				=     self.get_tokenizer()

												__lowercase      :							Tuple				=     CLIPProcessor(tokenizer=_A		,     image_processor=_A							)

												__lowercase      :							int				=     """lower newer"""
												__lowercase      :							Tuple				=     self.prepare_image_inputs()

												__lowercase      :							Union[str, Any]				=     processor(text=_A		,     images=_A							)

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







import warnings

from ...utils import logging
from .image_processing_beit import BeitImageProcessor


lowerCamelCase : Union[str, Any]						   =       logging.get_logger(__name__)

class 		lowerCAmelCase     ( __a			):

					'''simple docstring'''

					def __init__(  self				:	int		,     *__a				:	Dict		,     **__a				:	Optional[Any]							)			->  None:


												"""simple docstring"""

												warnings.warn(
												    """The class BeitFeatureExtractor is deprecated and will be removed in version 5 of Transformers. Please"""
												    """ use BeitImageProcessor instead."""		,     __a		,     )
												super().__init__(*__a		,     **__a							)