


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        a	(unittest.TestCase   ):




							"""simple docstring"""


							def 					__snake_case      (	self :						List[str]       )			->					Dict:
														__snake_case	:    List[Any]											=     tempfile.mkdtemp()

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

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

														__snake_case	:    Dict											=     {
														    'do_resize': True,
														    'size': 20,
														    'do_center_crop': True,
														    'crop_size': 18,
														    'do_normalize': True,
														    'image_mean': [0.48_14_54_66, 0.4_57_82_75, 0.40_82_10_73],
														    'image_std': [0.26_86_29_54, 0.26_13_02_58, 0.27_57_77_11],
														}
														__snake_case	:    List[str]											=     os.path.join(self.tmpdirname					,			UpperCamelCase__       )
														with open(self.image_processor_file					,			"w"					,			encoding="utf-8"       ) as fp:
																					json.dump(UpperCamelCase__					,			UpperCamelCase__       )

							def 					__snake_case      (	self :						Optional[Any]					,			**lowerCamelCase :						List[Any]       )			->					Union[str, Any]:
														return CLIPTokenizer.from_pretrained(self.tmpdirname					,			**UpperCamelCase__       )

							def 					__snake_case      (	self :						Dict					,			**lowerCamelCase :						List[str]       )			->					Optional[int]:
														return CLIPTokenizerFast.from_pretrained(self.tmpdirname					,			**UpperCamelCase__       )

							def 					__snake_case      (	self :						str					,			**lowerCamelCase :						List[Any]       )			->					Union[str, Any]:
														return ViTImageProcessor.from_pretrained(self.tmpdirname					,			**UpperCamelCase__       )

							def 					__snake_case      (	self :						Optional[int]       )			->					Dict:
														shutil.rmtree(self.tmpdirname       )

							def 					__snake_case      (	self :						List[Any]       )			->					Tuple:
														__snake_case	:    Tuple											=     [np.random.randint(255					,			size=(3, 30, 400)					,			dtype=np.uinta       )]

														__snake_case	:    Union[str, Any]											=     [Image.fromarray(np.moveaxis(UpperCamelCase__					,			0					,			-1       )       ) for x in image_inputs]

														return image_inputs

							def 					__snake_case      (	self :						Union[str, Any]       )			->					List[Any]:
														__snake_case	:    str											=     self.get_tokenizer()
														__snake_case	:    str											=     self.get_rust_tokenizer()
														__snake_case	:    Union[str, Any]											=     self.get_image_processor()

														__snake_case	:    str											=     CLIPSegProcessor(tokenizer=UpperCamelCase__					,			image_processor=UpperCamelCase__       )
														processor_slow.save_pretrained(self.tmpdirname       )
														__snake_case	:    Tuple											=     CLIPSegProcessor.from_pretrained(self.tmpdirname					,			use_fast=UpperCamelCase__       )

														__snake_case	:    List[str]											=     CLIPSegProcessor(tokenizer=UpperCamelCase__					,			image_processor=UpperCamelCase__       )
														processor_fast.save_pretrained(self.tmpdirname       )
														__snake_case	:    List[Any]											=     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					,			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 					__snake_case      (	self :						Union[str, Any]       )			->					Optional[int]:
														__snake_case	:    str											=     CLIPSegProcessor(tokenizer=self.get_tokenizer()					,			image_processor=self.get_image_processor()       )
														processor.save_pretrained(self.tmpdirname       )

														__snake_case	:    str											=     self.get_tokenizer(bos_token="(BOS)"					,			eos_token="(EOS)"       )
														__snake_case	:    List[Any]											=     self.get_image_processor(do_normalize=UpperCamelCase__					,			padding_value=1.0       )

														__snake_case	:    int											=     CLIPSegProcessor.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 					__snake_case      (	self :						int       )			->					Tuple:
														__snake_case	:    Optional[Any]											=     self.get_image_processor()
														__snake_case	:    Any											=     self.get_tokenizer()

														__snake_case	:    int											=     CLIPSegProcessor(tokenizer=UpperCamelCase__					,			image_processor=UpperCamelCase__       )

														__snake_case	:    str											=     self.prepare_image_inputs()

														__snake_case	:    Optional[int]											=     image_processor(UpperCamelCase__					,			return_tensors="np"       )
														__snake_case	:    Union[str, Any]											=     processor(images=UpperCamelCase__					,			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 					__snake_case      (	self :						List[str]       )			->					List[str]:
														__snake_case	:    Optional[int]											=     self.get_image_processor()
														__snake_case	:    Optional[int]											=     self.get_tokenizer()

														__snake_case	:    List[str]											=     CLIPSegProcessor(tokenizer=UpperCamelCase__					,			image_processor=UpperCamelCase__       )

														__snake_case	:    Tuple											=     'lower newer'

														__snake_case	:    Dict											=     processor(text=UpperCamelCase__       )

														__snake_case	:    List[str]											=     tokenizer(UpperCamelCase__       )

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

							def 					__snake_case      (	self :						Optional[int]       )			->					Optional[int]:
														__snake_case	:    List[str]											=     self.get_image_processor()
														__snake_case	:    Union[str, Any]											=     self.get_tokenizer()

														__snake_case	:    str											=     CLIPSegProcessor(tokenizer=UpperCamelCase__					,			image_processor=UpperCamelCase__       )

														__snake_case	:    Optional[Any]											=     'lower newer'
														__snake_case	:    Optional[Any]											=     self.prepare_image_inputs()

														__snake_case	:    Optional[Any]											=     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 					__snake_case      (	self :						Union[str, Any]       )			->					List[str]:
														__snake_case	:    Union[str, Any]											=     self.get_image_processor()
														__snake_case	:    Optional[Any]											=     self.get_tokenizer()

														__snake_case	:    Dict											=     CLIPSegProcessor(tokenizer=UpperCamelCase__					,			image_processor=UpperCamelCase__       )

														__snake_case	:    Optional[Any]											=     self.prepare_image_inputs()
														__snake_case	:    List[Any]											=     self.prepare_image_inputs()

														__snake_case	:    Optional[Any]											=     processor(images=UpperCamelCase__					,			visual_prompt=UpperCamelCase__       )

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

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






							def 					__snake_case      (	self :						List[Any]       )			->					Optional[Any]:
														__snake_case	:    List[str]											=     self.get_image_processor()
														__snake_case	:    Any											=     self.get_tokenizer()

														__snake_case	:    List[Any]											=     CLIPSegProcessor(tokenizer=UpperCamelCase__					,			image_processor=UpperCamelCase__       )

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

														__snake_case	:    Union[str, Any]											=     processor.batch_decode(UpperCamelCase__       )
														__snake_case	:    List[Any]											=     tokenizer.batch_decode(UpperCamelCase__       )

														self.assertListEqual(UpperCamelCase__					,			UpperCamelCase__       )





import unittest

from transformers import DonutProcessor


_snake_case  :	Dict			      =       "naver-clova-ix/donut-base"

class        a	(unittest.TestCase   ):




							"""simple docstring"""


							def 					__snake_case      (							self :						Dict       )			->					int:
														__snake_case	:    Any											=     DonutProcessor.from_pretrained(lowerCamelCase       )






							def 					__snake_case      (							self :						str       )			->					List[Any]:
														__snake_case	:    Union[str, Any]											=     {
														    "name": "John Doe",
														    "age": "99",
														    "city": "Atlanta",
														    "state": "GA",
														    "zip": "30301",
														    "phone": "123-4567",
														    "nicknames": [{"nickname": "Johnny"}, {"nickname": "JD"}],
														}

														__snake_case	:    Union[str, Any]											=     (
														    "<s_name>John Doe</s_name><s_age>99</s_age><s_city>Atlanta</s_city>"
														    "<s_state>GA</s_state><s_zip>30301</s_zip><s_phone>123-4567</s_phone>"
														    "<s_nicknames><s_nickname>Johnny</s_nickname>"
														    "<sep/><s_nickname>JD</s_nickname></s_nicknames>"
														)
														__snake_case	:    Tuple											=     self.processor.tokenajson(lowerCamelCase       )

														self.assertDictEqual(lowerCamelCase					,			lowerCamelCase       )

