


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 CLIPSegProcessor, ViTImageProcessor
@require_vision
class 						lowerCamelCase_							(					unittest.TestCase					):



					'''simple docstring'''







					def A   (					self    ) ->      List[Any]:







								'''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(snake_case_			,							range(len(snake_case_    )    )    )    )
								__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(snake_case_    ) + '''\n'''    )
								with open(self.merges_file			,							'''w'''			,							encoding='''utf-8'''    ) as fp:
											fp.write('''\n'''.join(snake_case_    )    )

								__lowercase			       = {
								    '''do_resize''': True,
								    '''size''': 2_0,
								    '''do_center_crop''': True,
								    '''crop_size''': 1_8,
								    '''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			       = os.path.join(self.tmpdirname			,							snake_case_    )
								with open(self.image_processor_file			,							'''w'''			,							encoding='''utf-8'''    ) as fp:
											json.dump(snake_case_			,							snake_case_    )






					def A   (					self			,							**snake_case_    ) ->      List[Any]:







								'''simple docstring'''

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






					def A   (					self			,							**snake_case_    ) ->      Any:







								'''simple docstring'''

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






					def A   (					self			,							**snake_case_    ) ->      str:







								'''simple docstring'''

								return ViTImageProcessor.from_pretrained(self.tmpdirname			,							**snake_case_    )






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







								'''simple docstring'''

								shutil.rmtree(self.tmpdirname    )






					def A   (					self    ) ->      int:







								'''simple docstring'''

								__lowercase			       = [np.random.randint(2_5_5			,							size=(3, 3_0, 4_0_0)			,							dtype=np.uinta    )]

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

								return image_inputs






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







								'''simple docstring'''

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

								__lowercase			       = CLIPSegProcessor(tokenizer=snake_case_			,							image_processor=snake_case_    )
								processor_slow.save_pretrained(self.tmpdirname    )
								__lowercase			       = CLIPSegProcessor.from_pretrained(self.tmpdirname			,							use_fast=snake_case_    )

								__lowercase			       = CLIPSegProcessor(tokenizer=snake_case_			,							image_processor=snake_case_    )
								processor_fast.save_pretrained(self.tmpdirname    )
								__lowercase			       = CLIPSegProcessor.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			,							snake_case_    )
								self.assertIsInstance(processor_fast.tokenizer			,							snake_case_    )

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






					def A   (					self    ) ->      int:







								'''simple docstring'''

								__lowercase			       = CLIPSegProcessor(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=snake_case_			,							padding_value=1.0    )

								__lowercase			       = CLIPSegProcessor.from_pretrained(
								    self.tmpdirname			,							bos_token='''(BOS)'''			,							eos_token='''(EOS)'''			,							do_normalize=snake_case_			,							padding_value=1.0    )

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

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






					def A   (					self    ) ->      Dict:







								'''simple docstring'''

								__lowercase			       = self.get_image_processor()
								__lowercase			       = self.get_tokenizer()

								__lowercase			       = CLIPSegProcessor(tokenizer=snake_case_			,							image_processor=snake_case_    )

								__lowercase			       = self.prepare_image_inputs()

								__lowercase			       = image_processor(snake_case_			,							return_tensors='''np'''    )
								__lowercase			       = processor(images=snake_case_			,							return_tensors='''np'''    )

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






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







								'''simple docstring'''

								__lowercase			       = self.get_image_processor()
								__lowercase			       = self.get_tokenizer()

								__lowercase			       = CLIPSegProcessor(tokenizer=snake_case_			,							image_processor=snake_case_    )

								__lowercase			       = '''lower newer'''

								__lowercase			       = processor(text=snake_case_    )

								__lowercase			       = tokenizer(snake_case_    )

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






					def A   (					self    ) ->      int:







								'''simple docstring'''

								__lowercase			       = self.get_image_processor()
								__lowercase			       = self.get_tokenizer()

								__lowercase			       = CLIPSegProcessor(tokenizer=snake_case_			,							image_processor=snake_case_    )

								__lowercase			       = '''lower newer'''
								__lowercase			       = self.prepare_image_inputs()

								__lowercase			       = processor(text=snake_case_			,							images=snake_case_    )

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

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






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







								'''simple docstring'''

								__lowercase			       = self.get_image_processor()
								__lowercase			       = self.get_tokenizer()

								__lowercase			       = CLIPSegProcessor(tokenizer=snake_case_			,							image_processor=snake_case_    )

								__lowercase			       = self.prepare_image_inputs()
								__lowercase			       = self.prepare_image_inputs()

								__lowercase			       = processor(images=snake_case_			,							visual_prompt=snake_case_    )

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

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






					def A   (					self    ) ->      Dict:







								'''simple docstring'''

								__lowercase			       = self.get_image_processor()
								__lowercase			       = self.get_tokenizer()

								__lowercase			       = CLIPSegProcessor(tokenizer=snake_case_			,							image_processor=snake_case_    )

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

								__lowercase			       = processor.batch_decode(snake_case_    )
								__lowercase			       = tokenizer.batch_decode(snake_case_    )

								self.assertListEqual(snake_case_			,							snake_case_    )






import copy
from dataclasses import dataclass
from pathlib import Path
from typing import Dict, Optional, Union
@dataclass
class 						lowerCamelCase_							:



					'''simple docstring'''







					__UpperCAmelCase							  =					None
					__UpperCAmelCase							  =					False
					__UpperCAmelCase							  =					False
					__UpperCAmelCase							  =					False
					__UpperCAmelCase							  =					None
					__UpperCAmelCase							  =					None
					__UpperCAmelCase							  =					False
					__UpperCAmelCase							  =					False
					__UpperCAmelCase							  =					False
					__UpperCAmelCase							  =					True
					__UpperCAmelCase							  =					None
					__UpperCAmelCase							  =					1
					__UpperCAmelCase							  =					None
					__UpperCAmelCase							  =					False
					__UpperCAmelCase							  =					None
					__UpperCAmelCase							  =					None






					def A   (					self    ) ->      "DownloadConfig":







								'''simple docstring'''

								return self.__class__(**{k: copy.deepcopy(snake_case_    ) for k, v in self.__dict__.items()}    )


