




import shutil
import tempfile
import unittest

import numpy as np
import pytest

from transformers.testing_utils import require_torch, require_vision
from transformers.utils import is_torch_available, is_vision_available


if is_torch_available():
		from transformers.pytorch_utils import is_torch_greater_or_equal_than_1_11
else:
		lowercase__    :					Optional[Any]					=						False

if is_vision_available():
		from PIL import Image

		from transformers import (
		    AutoProcessor,
		    PixaStructImageProcessor,
		    PixaStructProcessor,
		    PreTrainedTokenizerFast,
		    TaTokenizer,
		)
@unittest.skipIf(
    not is_torch_greater_or_equal_than_1_11	,       reason='''`Pix2StructImageProcessor` requires `torch>=1.11.0`.'''	,       )
@require_vision
@require_torch
class 		UpperCAmelCase       (    unittest.TestCase      ):







						'''simple docstring'''





						def 	snake_case__						(						self							:					Union[str, Any]						):






							"""simple docstring"""






							snake_case_		   =					tempfile.mkdtemp()

							snake_case_		   =					PixaStructImageProcessor()
							snake_case_		   =					TaTokenizer.from_pretrained("t5-small"						)

							snake_case_		   =					PixaStructProcessor(__lowercase	,     __lowercase						)

							processor.save_pretrained(self.tmpdirname						)






						def 	snake_case__						(						self							:					List[Any]	,     **__lowercase							:					int						):






							"""simple docstring"""






							return AutoProcessor.from_pretrained(self.tmpdirname	,     **__lowercase						).tokenizer






						def 	snake_case__						(						self							:					List[Any]	,     **__lowercase							:					Union[str, Any]						):






							"""simple docstring"""






							return AutoProcessor.from_pretrained(self.tmpdirname	,     **__lowercase						).image_processor






						def 	snake_case__						(						self							:					Dict						):






							"""simple docstring"""






							shutil.rmtree(self.tmpdirname						)






						def 	snake_case__						(						self							:					int						):






							"""simple docstring"""






							snake_case_		   =					[np.random.randint(2_55	,     size=(3, 30, 4_00)	,     dtype=np.uinta						)]

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

							return image_inputs






						def 	snake_case__						(						self							:					Any						):






							"""simple docstring"""






							snake_case_		   =					PixaStructProcessor(tokenizer=self.get_tokenizer()	,     image_processor=self.get_image_processor()						)
							processor.save_pretrained(self.tmpdirname						)

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

							snake_case_		   =					PixaStructProcessor.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 	snake_case__						(						self							:					int						):






							"""simple docstring"""






							snake_case_		   =					self.get_image_processor()
							snake_case_		   =					self.get_tokenizer()

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

							snake_case_		   =					self.prepare_image_inputs()

							snake_case_		   =					image_processor(__lowercase	,     return_tensors="np"						)
							snake_case_		   =					processor(images=__lowercase	,     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							:					str						):






							"""simple docstring"""






							snake_case_		   =					self.get_image_processor()
							snake_case_		   =					self.get_tokenizer()

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

							snake_case_		   =					"lower newer"

							snake_case_		   =					processor(text=__lowercase						)

							snake_case_		   =					tokenizer(__lowercase	,     return_token_type_ids=__lowercase	,     add_special_tokens=__lowercase						)

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






						def 	snake_case__						(						self							:					Any						):






							"""simple docstring"""






							snake_case_		   =					self.get_image_processor()
							snake_case_		   =					self.get_tokenizer()

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

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

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

							self.assertListEqual(
							    list(inputs.keys()						)	,     ["flattened_patches", "attention_mask", "decoder_attention_mask", "decoder_input_ids"]						)

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






						def 	snake_case__						(						self							:					Dict						):






							"""simple docstring"""






							snake_case_		   =					self.get_image_processor()
							snake_case_		   =					self.get_tokenizer()

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

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

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

							snake_case_		   =					[5_12, 10_24, 20_48, 40_96]
							snake_case_		   =					[7_70, 7_70, 7_70, 7_70]
							# with text
							for i, max_patch in enumerate(__lowercase						):
								snake_case_		   =					processor(text=__lowercase	,     images=__lowercase	,     max_patches=__lowercase						)
								self.assertEqual(inputs["flattened_patches"][0].shape[0]	,     __lowercase						)
								self.assertEqual(inputs["flattened_patches"][0].shape[1]	,     expected_hidden_size[i]						)

							# without text input
							for i, max_patch in enumerate(__lowercase						):
								snake_case_		   =					processor(images=__lowercase	,     max_patches=__lowercase						)
								self.assertEqual(inputs["flattened_patches"][0].shape[0]	,     __lowercase						)
								self.assertEqual(inputs["flattened_patches"][0].shape[1]	,     expected_hidden_size[i]						)






						def 	snake_case__						(						self							:					Tuple						):






							"""simple docstring"""






							snake_case_		   =					self.get_image_processor()
							snake_case_		   =					self.get_tokenizer()

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

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

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

							self.assertListEqual(__lowercase	,     __lowercase						)






						def 	snake_case__						(						self							:					Any						):






							"""simple docstring"""






							snake_case_		   =					self.get_image_processor()
							snake_case_		   =					self.get_tokenizer()

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

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

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

							# For now the processor supports only ["flattened_patches", "input_ids", "attention_mask", "decoder_attention_mask"]
							self.assertListEqual(
							    list(inputs.keys()						)	,     ["flattened_patches", "attention_mask", "decoder_attention_mask", "decoder_input_ids"]						)

							snake_case_		   =					processor(text=__lowercase						)

							# For now the processor supports only ["flattened_patches", "input_ids", "attention_mask", "decoder_attention_mask"]
							self.assertListEqual(list(inputs.keys()						)	,     ["input_ids", "attention_mask"]						)






def 						lowerCamelCase__   (		_A					,     _A					,     _A							):







	'''simple docstring'''





	if right <= left:
		return
	snake_case_		   =					snake_case_		   =					left
	snake_case_		   =					right
	snake_case_		   =					sorting[left]
	while i <= b:
		if sorting[i] < pivot:
			snake_case_   ,				snake_case_		   =					sorting[i], sorting[a]
			a += 1
			i += 1
		elif sorting[i] > pivot:
			snake_case_   ,				snake_case_		   =					sorting[i], sorting[b]
			b -= 1
		else:
			i += 1
	quick_sort_apartition(_A					,     _A					,     a - 1							)
	quick_sort_apartition(_A					,     b + 1					,     _A							)


def 						lowerCamelCase__   (		_A					,     _A					,     _A							):







	'''simple docstring'''





	if left < right:
		snake_case_		   =					lomuto_partition(_A					,     _A					,     _A							)
		quick_sort_lomuto_partition(_A					,     _A					,     pivot_index - 1							)
		quick_sort_lomuto_partition(_A					,     pivot_index + 1					,     _A							)


def 						lowerCamelCase__   (		_A					,     _A					,     _A							):







	'''simple docstring'''





	snake_case_		   =					sorting[right]
	snake_case_		   =					left
	for i in range(_A					,     _A							):
		if sorting[i] < pivot:
			snake_case_   ,				snake_case_		   =					sorting[i], sorting[store_index]
			store_index += 1
	snake_case_   ,				snake_case_		   =					sorting[store_index], sorting[right]
	return store_index


def 						lowerCamelCase__   (		_A							):







	'''simple docstring'''





	if len(_A							) <= 1:
		return sorting
	return (
	    three_way_radix_quicksort([i for i in sorting if i < sorting[0]]							)
	    + [i for i in sorting if i == sorting[0]]
	    + three_way_radix_quicksort([i for i in sorting if i > sorting[0]]							)
	)


if __name__ == "__main__":
		import doctest

		doctest.testmod(verbose=True)

		lowercase__    :					Tuple					=						input("Enter numbers separated by a comma:\n").strip()
		lowercase__    :					int					=						[int(item) for item in user_input.split(",")]
		quick_sort_apartition(unsorted, 0, len(unsorted) - 1)
		print(unsorted)
