




"""simple docstring"""




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    UpperCAmelCase_  (       unittest.TestCase						):
		def      _lowerCamelCase				(		self    )		->    Union[str, Any]:
					__lowercase       :   Dict        =    tempfile.mkdtemp()

					# fmt: off
					__lowercase       :   Optional[Any]        =    ['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       :   Optional[int]        =    dict(zip(lowercase_							,		range(len(lowercase_    )    )    )    )
					__lowercase       :   Tuple        =    ['#version: 0.2', 'l o', 'lo w</w>', 'e r</w>', '']
					__lowercase       :   Optional[Any]        =    {'unk_token': '<unk>'}

					__lowercase       :   Optional[int]        =    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(lowercase_    ) + '''\n'''    )
					with open(self.merges_file							,		'''w'''							,		encoding='''utf-8'''    ) as fp:
								fp.write('''\n'''.join(lowercase_    )    )

					__lowercase       :   List[str]        =    {
					    'do_resize': True,
					    'size': 20,
					    'do_center_crop': True,
					    'crop_size': 18,
					    'do_normalize': True,
					    'image_mean': [0.4_8_1_4_5_4_6_6, 0.4_5_7_8_2_7_5, 0.4_0_8_2_1_0_7_3],
					    'image_std': [0.2_6_8_6_2_9_5_4, 0.2_6_1_3_0_2_5_8, 0.2_7_5_7_7_7_1_1],
					}
					__lowercase       :   List[Any]        =    os.path.join(self.tmpdirname							,		lowercase_    )
					with open(self.image_processor_file							,		'''w'''							,		encoding='''utf-8'''    ) as fp:
								json.dump(lowercase_							,		lowercase_    )
		def      _lowerCamelCase				(		self							,		**UpperCamelCase_    )		->    List[str]:
					return CLIPTokenizer.from_pretrained(self.tmpdirname							,		**lowercase_    )
		def      _lowerCamelCase				(		self							,		**UpperCamelCase_    )		->    Tuple:
					return CLIPTokenizerFast.from_pretrained(self.tmpdirname							,		**lowercase_    )
		def      _lowerCamelCase				(		self							,		**UpperCamelCase_    )		->    str:
					return CLIPImageProcessor.from_pretrained(self.tmpdirname							,		**lowercase_    )
		def      _lowerCamelCase				(		self    )		->    str:
					shutil.rmtree(self.tmpdirname    )
		def      _lowerCamelCase				(		self    )		->    Any:
					__lowercase       :   Dict        =    [np.random.randint(2_55							,		size=(3, 30, 4_00)							,		dtype=np.uinta    )]

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

					return image_inputs
		def      _lowerCamelCase				(		self    )		->    Tuple:
					__lowercase       :   Optional[Any]        =    self.get_tokenizer()
					__lowercase       :   str        =    self.get_rust_tokenizer()
					__lowercase       :   Dict        =    self.get_image_processor()

					__lowercase       :   List[Any]        =    CLIPProcessor(tokenizer=lowercase_							,		image_processor=lowercase_    )
					processor_slow.save_pretrained(self.tmpdirname    )
					__lowercase       :   Tuple        =    CLIPProcessor.from_pretrained(self.tmpdirname							,		use_fast=lowercase_    )

					__lowercase       :   int        =    CLIPProcessor(tokenizer=lowercase_							,		image_processor=lowercase_    )
					processor_fast.save_pretrained(self.tmpdirname    )
					__lowercase       :   Union[str, 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							,		lowercase_    )
					self.assertIsInstance(processor_fast.tokenizer							,		lowercase_    )

					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							,		lowercase_    )
					self.assertIsInstance(processor_fast.image_processor							,		lowercase_    )
		def      _lowerCamelCase				(		self    )		->    List[Any]:
					__lowercase       :   List[str]        =    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=lowercase_							,		padding_value=1.0    )

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

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

					self.assertEqual(processor.image_processor.to_json_string()							,		image_processor_add_kwargs.to_json_string()    )
					self.assertIsInstance(processor.image_processor							,		lowercase_    )
		def      _lowerCamelCase				(		self    )		->    List[Any]:
					__lowercase       :   Union[str, Any]        =    self.get_image_processor()
					__lowercase       :   int        =    self.get_tokenizer()

					__lowercase       :   List[Any]        =    CLIPProcessor(tokenizer=lowercase_							,		image_processor=lowercase_    )

					__lowercase       :   int        =    self.prepare_image_inputs()

					__lowercase       :   str        =    image_processor(lowercase_							,		return_tensors='''np'''    )
					__lowercase       :   Dict        =    processor(images=lowercase_							,		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    )		->    Optional[Any]:
					__lowercase       :   List[Any]        =    self.get_image_processor()
					__lowercase       :   Dict        =    self.get_tokenizer()

					__lowercase       :   Any        =    CLIPProcessor(tokenizer=lowercase_							,		image_processor=lowercase_    )

					__lowercase       :   Any        =    'lower newer'

					__lowercase       :   Dict        =    processor(text=lowercase_    )

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

					for key in encoded_tok.keys():
								self.assertListEqual(encoded_tok[key]							,		encoded_processor[key]    )
		def      _lowerCamelCase				(		self    )		->    Dict:
					__lowercase       :   Tuple        =    self.get_image_processor()
					__lowercase       :   int        =    self.get_tokenizer()

					__lowercase       :   Dict        =    CLIPProcessor(tokenizer=lowercase_							,		image_processor=lowercase_    )

					__lowercase       :   List[Any]        =    'lower newer'
					__lowercase       :   List[Any]        =    self.prepare_image_inputs()

					__lowercase       :   List[Any]        =    processor(text=lowercase_							,		images=lowercase_    )

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

					# test if it raises when no input is passed
					with pytest.raises(lowercase_    ):
								processor()
		def      _lowerCamelCase				(		self    )		->    int:
					__lowercase       :   Union[str, Any]        =    self.get_image_processor()
					__lowercase       :   List[Any]        =    self.get_tokenizer()

					__lowercase       :   Optional[int]        =    CLIPProcessor(tokenizer=lowercase_							,		image_processor=lowercase_    )

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

					__lowercase       :   Optional[int]        =    processor.batch_decode(lowercase_    )
					__lowercase       :   List[str]        =    tokenizer.batch_decode(lowercase_    )

					self.assertListEqual(lowercase_							,		lowercase_    )
		def      _lowerCamelCase				(		self    )		->    Any:
					__lowercase       :   Union[str, Any]        =    self.get_image_processor()
					__lowercase       :   Tuple        =    self.get_tokenizer()

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

					__lowercase       :   Any        =    'lower newer'
					__lowercase       :   str        =    self.prepare_image_inputs()

					__lowercase       :   Any        =    processor(text=lowercase_							,		images=lowercase_    )

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







import sys

from .dependency_versions_table import deps
from .utils.versions import require_version, require_version_core


# define which module versions we always want to check at run time
# (usually the ones defined in `install_requires` in setup.py)
#
# order specific notes:
# - tqdm must be checked before tokenizers

lowerCamelCase											=       'python tqdm regex requests packaging filelock numpy tokenizers'.split()
if sys.version_info < (3, 7):
 pkgs_to_check_at_runtime.append('dataclasses')
if sys.version_info < (3, 8):
 pkgs_to_check_at_runtime.append('importlib_metadata')

for pkg in pkgs_to_check_at_runtime:
 if pkg in deps:
  if pkg == "tokenizers":
   # must be loaded here, or else tqdm check may fail
   from .utils import is_tokenizers_available

   if not is_tokenizers_available():
    continue  # not required, check version only if installed

  require_version_core(deps[pkg])
 else:
  raise ValueError(F"""can't find {pkg} in {deps.keys()}, check dependency_versions_table.py""")




def 	a_      (    SCREAMING_SNAKE_CASE__					:      int		,			SCREAMING_SNAKE_CASE__					:      str=None     ):
       '''simple docstring'''





       require_version(deps[pkg]		,			SCREAMING_SNAKE_CASE__     )


