






'''simple docstring'''


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:
					lowerCamelCase_					:			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  _SCREAMING_SNAKE_CASE				(		unittest.TestCase						):


			'''simple docstring'''





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

									'''simple docstring'''







									UpperCamelCase__       =			tempfile.mkdtemp()

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

									UpperCamelCase__       =			PixaStructProcessor(lowercase			,   lowercase      )

									processor.save_pretrained(self.tmpdirname      )






			def 					A   ( self				:    int			,   **lowercase				:    Dict      )				->     Dict:

									'''simple docstring'''







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






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

									'''simple docstring'''







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






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

									'''simple docstring'''







									shutil.rmtree(self.tmpdirname      )






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

									'''simple docstring'''







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

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

									return image_inputs






			def 					A   ( self				:    Optional[int]      )				->     Dict:

									'''simple docstring'''







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

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

									UpperCamelCase__       =			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 					A   ( self				:    Optional[int]      )				->     Any:

									'''simple docstring'''







									UpperCamelCase__       =			self.get_image_processor()
									UpperCamelCase__       =			self.get_tokenizer()

									UpperCamelCase__       =			PixaStructProcessor(tokenizer=lowercase			,   image_processor=lowercase      )

									UpperCamelCase__       =			self.prepare_image_inputs()

									UpperCamelCase__       =			image_processor(lowercase			,   return_tensors="""np"""      )
									UpperCamelCase__       =			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 					A   ( self				:    List[Any]      )				->     int:

									'''simple docstring'''







									UpperCamelCase__       =			self.get_image_processor()
									UpperCamelCase__       =			self.get_tokenizer()

									UpperCamelCase__       =			PixaStructProcessor(tokenizer=lowercase			,   image_processor=lowercase      )

									UpperCamelCase__       =			"""lower newer"""

									UpperCamelCase__       =			processor(text=lowercase      )

									UpperCamelCase__       =			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 					A   ( self				:    int      )				->     Any:

									'''simple docstring'''







									UpperCamelCase__       =			self.get_image_processor()
									UpperCamelCase__       =			self.get_tokenizer()

									UpperCamelCase__       =			PixaStructProcessor(tokenizer=lowercase			,   image_processor=lowercase      )

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

									UpperCamelCase__       =			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 					A   ( self				:    List[str]      )				->     Optional[Any]:

									'''simple docstring'''







									UpperCamelCase__       =			self.get_image_processor()
									UpperCamelCase__       =			self.get_tokenizer()

									UpperCamelCase__       =			PixaStructProcessor(tokenizer=lowercase			,   image_processor=lowercase      )

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

									UpperCamelCase__       =			processor(text=lowercase			,   images=lowercase      )

									UpperCamelCase__       =			[5_1_2, 1_0_2_4, 2_0_4_8, 4_0_9_6]
									UpperCamelCase__       =			[7_7_0, 7_7_0, 7_7_0, 7_7_0]
									# with text
									for i, max_patch in enumerate(lowercase      ):
															UpperCamelCase__       =			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      ):
															UpperCamelCase__       =			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 					A   ( self				:    List[str]      )				->     str:

									'''simple docstring'''







									UpperCamelCase__       =			self.get_image_processor()
									UpperCamelCase__       =			self.get_tokenizer()

									UpperCamelCase__       =			PixaStructProcessor(tokenizer=lowercase			,   image_processor=lowercase      )

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

									UpperCamelCase__       =			processor.batch_decode(lowercase      )
									UpperCamelCase__       =			tokenizer.batch_decode(lowercase      )

									self.assertListEqual(lowercase			,   lowercase      )







			def 					A   ( self				:    Tuple      )				->     Optional[int]:

									'''simple docstring'''







									UpperCamelCase__       =			self.get_image_processor()
									UpperCamelCase__       =			self.get_tokenizer()

									UpperCamelCase__       =			PixaStructProcessor(tokenizer=lowercase			,   image_processor=lowercase      )

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

									UpperCamelCase__       =			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"""]      )

									UpperCamelCase__       =			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"""]      )








'''simple docstring'''


from itertools import combinations_with_replacement







def 						__magic_name__(			_A = 100       ):
						'''simple docstring'''





						UpperCamelCase__       =			[*list(range(1    ,   21       )       ), 25]
						UpperCamelCase__       =			[2 * x for x in range(1    ,   21       )] + [50]
						UpperCamelCase__       =			[3 * x for x in range(1    ,   21       )]
						UpperCamelCase__       =			singles + doubles + triples + [0]

						UpperCamelCase__       =			0
						UpperCamelCase__       =			42
						UpperCamelCase__       =			42
						UpperCamelCase__       =			42
						UpperCamelCase__       =			42

						for double in doubles:
												for throwa, throwa in combinations_with_replacement(_A    ,   2       ):
																		UpperCamelCase__       =			double + throwa + throwa
																		if checkout_total < limit:
																								num_checkouts += 1

						return num_checkouts


if __name__ == "__main__":
					print(f"""{solution() = }""")
