"""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__  :  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     snake_case	(			unittest.TestCase    ):




					"""simple docstring"""

					def 		__lowerCAmelCase						(    self       :     List[Any]      ):
									UpperCAmelCase__					=							tempfile.mkdtemp()

									UpperCAmelCase__					=							PixaStructImageProcessor()
									UpperCAmelCase__					=							TaTokenizer.from_pretrained('t5-small'      )

									UpperCAmelCase__					=							PixaStructProcessor(lowerCamelCase__   ,lowerCamelCase__      )

									processor.save_pretrained(self.tmpdirname      )







					def 		__lowerCAmelCase						(    self       :     List[str]   ,**lowerCamelCase__       :     int      ):
									return AutoProcessor.from_pretrained(self.tmpdirname   ,**lowerCamelCase__      ).tokenizer







					def 		__lowerCAmelCase						(    self       :     Dict   ,**lowerCamelCase__       :     List[Any]      ):
									return AutoProcessor.from_pretrained(self.tmpdirname   ,**lowerCamelCase__      ).image_processor







					def 		__lowerCAmelCase						(    self       :     Optional[int]      ):
									shutil.rmtree(self.tmpdirname      )







					def 		__lowerCAmelCase						(    self       :     Optional[int]      ):
									UpperCAmelCase__					=							[np.random.randint(255   ,size=(3, 30, 400)   ,dtype=np.uinta      )]

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

									return image_inputs







					def 		__lowerCAmelCase						(    self       :     List[str]      ):
									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=lowerCamelCase__   ,padding_value=1.0      )

									UpperCAmelCase__					=							PixaStructProcessor.from_pretrained(
									    self.tmpdirname   ,bos_token='(BOS)'   ,eos_token='(EOS)'   ,do_normalize=lowerCamelCase__   ,padding_value=1.0      )

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

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







					def 		__lowerCAmelCase						(    self       :     Union[str, Any]      ):
									UpperCAmelCase__					=							self.get_image_processor()
									UpperCAmelCase__					=							self.get_tokenizer()

									UpperCAmelCase__					=							PixaStructProcessor(tokenizer=lowerCamelCase__   ,image_processor=lowerCamelCase__      )

									UpperCAmelCase__					=							self.prepare_image_inputs()

									UpperCAmelCase__					=							image_processor(lowerCamelCase__   ,return_tensors='np'      )
									UpperCAmelCase__					=							processor(images=lowerCamelCase__   ,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 		__lowerCAmelCase						(    self       :     List[str]      ):
									UpperCAmelCase__					=							self.get_image_processor()
									UpperCAmelCase__					=							self.get_tokenizer()

									UpperCAmelCase__					=							PixaStructProcessor(tokenizer=lowerCamelCase__   ,image_processor=lowerCamelCase__      )

									UpperCAmelCase__					=							'lower newer'

									UpperCAmelCase__					=							processor(text=lowerCamelCase__      )

									UpperCAmelCase__					=							tokenizer(lowerCamelCase__   ,return_token_type_ids=lowerCamelCase__   ,add_special_tokens=lowerCamelCase__      )

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







					def 		__lowerCAmelCase						(    self       :     str      ):
									UpperCAmelCase__					=							self.get_image_processor()
									UpperCAmelCase__					=							self.get_tokenizer()

									UpperCAmelCase__					=							PixaStructProcessor(tokenizer=lowerCamelCase__   ,image_processor=lowerCamelCase__      )

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

									UpperCAmelCase__					=							processor(text=lowerCamelCase__   ,images=lowerCamelCase__      )

									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(lowerCamelCase__      ):
													processor()







					def 		__lowerCAmelCase						(    self       :     List[str]      ):
									UpperCAmelCase__					=							self.get_image_processor()
									UpperCAmelCase__					=							self.get_tokenizer()

									UpperCAmelCase__					=							PixaStructProcessor(tokenizer=lowerCamelCase__   ,image_processor=lowerCamelCase__      )

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

									UpperCAmelCase__					=							processor(text=lowerCamelCase__   ,images=lowerCamelCase__      )

									UpperCAmelCase__					=							[512, 1_024, 2_048, 4_096]
									UpperCAmelCase__					=							[770, 770, 770, 770]
									# with text
									for i, max_patch in enumerate(lowerCamelCase__      ):
													UpperCAmelCase__					=							processor(text=lowerCamelCase__   ,images=lowerCamelCase__   ,max_patches=lowerCamelCase__      )
													self.assertEqual(inputs['flattened_patches'][0].shape[0]   ,lowerCamelCase__      )
													self.assertEqual(inputs['flattened_patches'][0].shape[1]   ,expected_hidden_size[i]      )

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







					def 		__lowerCAmelCase						(    self       :     List[Any]      ):
									UpperCAmelCase__					=							self.get_image_processor()
									UpperCAmelCase__					=							self.get_tokenizer()

									UpperCAmelCase__					=							PixaStructProcessor(tokenizer=lowerCamelCase__   ,image_processor=lowerCamelCase__      )

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

									UpperCAmelCase__					=							processor.batch_decode(lowerCamelCase__      )
									UpperCAmelCase__					=							tokenizer.batch_decode(lowerCamelCase__      )

									self.assertListEqual(lowerCamelCase__   ,lowerCamelCase__      )







					def 		__lowerCAmelCase						(    self       :     List[str]      ):
									UpperCAmelCase__					=							self.get_image_processor()
									UpperCAmelCase__					=							self.get_tokenizer()

									UpperCAmelCase__					=							PixaStructProcessor(tokenizer=lowerCamelCase__   ,image_processor=lowerCamelCase__      )

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

									UpperCAmelCase__					=							processor(text=lowerCamelCase__   ,images=lowerCamelCase__      )

									# 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=lowerCamelCase__      )

									# 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 __future__ import annotations
class     snake_case	:




					"""simple docstring"""

					def __init__(    self       :     Tuple   ,lowerCamelCase__       :     int      ):
									UpperCAmelCase__					=							vertices
									UpperCAmelCase__					=							[[0] * vertices for _ in range(lowerCamelCase__      )]







					def 		__lowerCAmelCase						(    self       :     Dict   ,lowerCamelCase__       :     list[int]      ):
									print('Vertex \t Distance from Source'      )
									for vertex in range(self.vertices      ):
													print(lowerCamelCase__   ,'\t\t'   ,distances_from_source[vertex]      )







					def 		__lowerCAmelCase						(    self       :     List[Any]   ,lowerCamelCase__       :     list[int]   ,lowerCamelCase__       :     list[bool]      ):
									UpperCAmelCase__					=							1e7
									UpperCAmelCase__					=							0

									# Search not nearest vertex not in the shortest path tree
									for vertex in range(self.vertices      ):
													if distances_from_source[vertex] < minimum and visited[vertex] is False:
																	UpperCAmelCase__					=							distances_from_source[vertex]
																	UpperCAmelCase__					=							vertex
									return min_index







					def 		__lowerCAmelCase						(    self       :     List[Any]   ,lowerCamelCase__       :     int      ):
									UpperCAmelCase__					=							[int(1e7      )] * self.vertices  # distances from the source
									UpperCAmelCase__					=							0
									UpperCAmelCase__					=							[False] * self.vertices

									for _ in range(self.vertices      ):
													UpperCAmelCase__					=							self.minimum_distance(lowerCamelCase__   ,lowerCamelCase__      )
													UpperCAmelCase__					=							True

													# Update dist value of the adjacent vertices
													# of the picked vertex only if the current
													# distance is greater than new distance and
													# the vertex in not in the shortest path tree
													for v in range(self.vertices      ):
																	if (
																	    self.graph[u][v] > 0
																	    and visited[v] is False
																	    and distances[v] > distances[u] + self.graph[u][v]
																	):
																					UpperCAmelCase__					=							distances[u] + self.graph[u][v]

									self.print_solution(lowerCamelCase__      )


if __name__ == "__main__":
						lowerCAmelCase__  :  List[str]											=     Graph(9)
						lowerCAmelCase__  :  Tuple											=     [
						    [0, 4, 0, 0, 0, 0, 0, 8, 0],
						    [4, 0, 8, 0, 0, 0, 0, 11, 0],
						    [0, 8, 0, 7, 0, 4, 0, 0, 2],
						    [0, 0, 7, 0, 9, 14, 0, 0, 0],
						    [0, 0, 0, 9, 0, 10, 0, 0, 0],
						    [0, 0, 4, 14, 10, 0, 2, 0, 0],
						    [0, 0, 0, 0, 0, 2, 0, 1, 6],
						    [8, 11, 0, 0, 0, 0, 1, 0, 7],
						    [0, 0, 2, 0, 0, 0, 6, 7, 0],
						]
						graph.dijkstra(0)



