






import json
import os
import shutil
import tempfile
import unittest

import numpy as np
import pytest

from transformers import MgpstrTokenizer
from transformers.models.mgp_str.tokenization_mgp_str import VOCAB_FILES_NAMES
from transformers.testing_utils import require_torch, require_vision
from transformers.utils import IMAGE_PROCESSOR_NAME, is_torch_available, is_vision_available


if is_torch_available():
					import torch


if is_vision_available():
					from PIL import Image

					from transformers import MgpstrProcessor, ViTImageProcessor


@require_torch
@require_vision
class     __SCREAMING_SNAKE_CASE					(   unittest.TestCase):
						_SCREAMING_SNAKE_CASE	:       Optional[int]   =					ViTImageProcessor if is_vision_available() else None






						@property
						def       UpperCamelCase__      (	self   ):






												"""simple docstring"""
												return self.image_processor_tester.prepare_image_processor_dict()






						def       UpperCamelCase__      (	self   ):






												"""simple docstring"""
												lowerCAmelCase__    						=						(3, 32, 1_28)
												lowerCAmelCase__    						=						tempfile.mkdtemp()

												# fmt: off
												lowerCAmelCase__    						=						["""[GO]""", """[s]""", """0""", """1""", """2""", """3""", """4""", """5""", """6""", """7""", """8""", """9""", """a""", """b""", """c""", """d""", """e""", """f""", """g""", """h""", """i""", """j""", """k""", """l""", """m""", """n""", """o""", """p""", """q""", """r""", """s""", """t""", """u""", """v""", """w""", """x""", """y""", """z"""]
												# fmt: on
												lowerCAmelCase__    						=						dict(zip(_UpperCamelCase     ,						range(len(_UpperCamelCase   )   )   )   )

												lowerCAmelCase__    						=						os.path.join(self.tmpdirname     ,						VOCAB_FILES_NAMES['vocab_file']   )
												with open(self.vocab_file     ,						'w'     ,						encoding='utf-8'   ) as fp:
																		fp.write(json.dumps(_UpperCamelCase   ) + '\n'   )

												lowerCAmelCase__    						=						{
												    """do_normalize""": False,
												    """do_resize""": True,
												    """image_processor_type""": """ViTImageProcessor""",
												    """resample""": 3,
												    """size""": {"""height""": 32, """width""": 1_28},
												}
												lowerCAmelCase__    						=						os.path.join(self.tmpdirname     ,						_UpperCamelCase   )
												with open(self.image_processor_file     ,						'w'     ,						encoding='utf-8'   ) as fp:
																		json.dump(_UpperCamelCase     ,						_UpperCamelCase   )






						def       UpperCamelCase__      (	self     ,						**_UpperCamelCase   ):






												"""simple docstring"""
												return MgpstrTokenizer.from_pretrained(self.tmpdirname     ,						**_UpperCamelCase   )






						def       UpperCamelCase__      (	self     ,						**_UpperCamelCase   ):






												"""simple docstring"""
												return ViTImageProcessor.from_pretrained(self.tmpdirname     ,						**_UpperCamelCase   )






						def       UpperCamelCase__      (	self   ):






												"""simple docstring"""
												shutil.rmtree(self.tmpdirname   )






						def       UpperCamelCase__      (	self   ):






												"""simple docstring"""
												lowerCAmelCase__    						=						np.random.randint(2_55     ,						size=(3, 30, 4_00)     ,						dtype=np.uinta   )

												lowerCAmelCase__    						=						Image.fromarray(np.moveaxis(_UpperCamelCase     ,						0     ,						-1   )   )

												return image_input






						def       UpperCamelCase__      (	self   ):






												"""simple docstring"""
												lowerCAmelCase__    						=						self.get_tokenizer()
												lowerCAmelCase__    						=						self.get_image_processor()

												lowerCAmelCase__    						=						MgpstrProcessor(tokenizer=_UpperCamelCase     ,						image_processor=_UpperCamelCase   )
												processor.save_pretrained(self.tmpdirname   )
												lowerCAmelCase__    						=						MgpstrProcessor.from_pretrained(self.tmpdirname     ,						use_fast=_UpperCamelCase   )

												self.assertEqual(processor.char_tokenizer.get_vocab()     ,						tokenizer.get_vocab()   )
												self.assertIsInstance(processor.char_tokenizer     ,						_UpperCamelCase   )

												self.assertEqual(processor.image_processor.to_json_string()     ,						image_processor.to_json_string()   )
												self.assertIsInstance(processor.image_processor     ,						_UpperCamelCase   )






						def       UpperCamelCase__      (	self   ):






												"""simple docstring"""
												lowerCAmelCase__    						=						self.get_tokenizer()
												lowerCAmelCase__    						=						self.get_image_processor()

												lowerCAmelCase__    						=						MgpstrProcessor(tokenizer=_UpperCamelCase     ,						image_processor=_UpperCamelCase   )
												processor.save_pretrained(self.tmpdirname   )

												lowerCAmelCase__    						=						self.get_tokenizer(bos_token='(BOS)'     ,						eos_token='(EOS)'   )
												lowerCAmelCase__    						=						self.get_image_processor(do_normalize=_UpperCamelCase     ,						padding_value=1.0   )

												lowerCAmelCase__    						=						MgpstrProcessor.from_pretrained(
												    self.tmpdirname     ,						bos_token='(BOS)'     ,						eos_token='(EOS)'     ,						do_normalize=_UpperCamelCase     ,						padding_value=1.0   )

												self.assertEqual(processor.char_tokenizer.get_vocab()     ,						tokenizer_add_kwargs.get_vocab()   )
												self.assertIsInstance(processor.char_tokenizer     ,						_UpperCamelCase   )

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






						def       UpperCamelCase__      (	self   ):






												"""simple docstring"""
												lowerCAmelCase__    						=						self.get_image_processor()
												lowerCAmelCase__    						=						self.get_tokenizer()

												lowerCAmelCase__    						=						MgpstrProcessor(tokenizer=_UpperCamelCase     ,						image_processor=_UpperCamelCase   )

												lowerCAmelCase__    						=						self.prepare_image_inputs()

												lowerCAmelCase__    						=						image_processor(_UpperCamelCase     ,						return_tensors='np'   )
												lowerCAmelCase__    						=						processor(images=_UpperCamelCase     ,						return_tensors='np'   )

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






						def       UpperCamelCase__      (	self   ):






												"""simple docstring"""
												lowerCAmelCase__    						=						self.get_image_processor()
												lowerCAmelCase__    						=						self.get_tokenizer()

												lowerCAmelCase__    						=						MgpstrProcessor(tokenizer=_UpperCamelCase     ,						image_processor=_UpperCamelCase   )

												lowerCAmelCase__    						=						"""test"""

												lowerCAmelCase__    						=						processor(text=_UpperCamelCase   )

												lowerCAmelCase__    						=						tokenizer(_UpperCamelCase   )
												for key in encoded_tok.keys():
																		self.assertListEqual(encoded_tok[key]     ,						encoded_processor[key]   )






						def       UpperCamelCase__      (	self   ):






												"""simple docstring"""
												lowerCAmelCase__    						=						self.get_image_processor()
												lowerCAmelCase__    						=						self.get_tokenizer()

												lowerCAmelCase__    						=						MgpstrProcessor(tokenizer=_UpperCamelCase     ,						image_processor=_UpperCamelCase   )

												lowerCAmelCase__    						=						"""test"""
												lowerCAmelCase__    						=						self.prepare_image_inputs()

												lowerCAmelCase__    						=						processor(text=_UpperCamelCase     ,						images=_UpperCamelCase   )

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

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






						def       UpperCamelCase__      (	self   ):






												"""simple docstring"""
												lowerCAmelCase__    						=						self.get_image_processor()
												lowerCAmelCase__    						=						self.get_tokenizer()

												lowerCAmelCase__    						=						MgpstrProcessor(tokenizer=_UpperCamelCase     ,						image_processor=_UpperCamelCase   )

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

												lowerCAmelCase__    						=						processor.char_decode(_UpperCamelCase   )
												lowerCAmelCase__    						=						tokenizer.batch_decode(_UpperCamelCase   )
												lowerCAmelCase__    						=						[seq.replace(' '     ,						''   ) for seq in decoded_tok]

												self.assertListEqual(_UpperCamelCase     ,						_UpperCamelCase   )






						def       UpperCamelCase__      (	self   ):






												"""simple docstring"""
												lowerCAmelCase__    						=						self.get_image_processor()
												lowerCAmelCase__    						=						self.get_tokenizer()

												lowerCAmelCase__    						=						MgpstrProcessor(tokenizer=_UpperCamelCase     ,						image_processor=_UpperCamelCase   )

												lowerCAmelCase__    						=						None
												lowerCAmelCase__    						=						self.prepare_image_inputs()

												lowerCAmelCase__    						=						processor(text=_UpperCamelCase     ,						images=_UpperCamelCase   )

												self.assertListEqual(list(inputs.keys()   )     ,						processor.model_input_names   )







						def       UpperCamelCase__      (	self   ):






												"""simple docstring"""
												lowerCAmelCase__    						=						self.get_image_processor()
												lowerCAmelCase__    						=						self.get_tokenizer()

												lowerCAmelCase__    						=						MgpstrProcessor(tokenizer=_UpperCamelCase     ,						image_processor=_UpperCamelCase   )

												lowerCAmelCase__    						=						torch.randn(1     ,						27     ,						38   )
												lowerCAmelCase__    						=						torch.randn(1     ,						27     ,						5_02_57   )
												lowerCAmelCase__    						=						torch.randn(1     ,						27     ,						3_05_22   )

												lowerCAmelCase__    						=						processor.batch_decode([char_input, bpe_input, wp_input]   )

												self.assertListEqual(list(results.keys()   )     ,						['generated_text', 'scores', 'char_preds', 'bpe_preds', 'wp_preds']   )







from __future__ import annotations

__snake_case    :    Any         =     {
    """A""": ["""B""", """C""", """E"""],
    """B""": ["""A""", """D""", """E"""],
    """C""": ["""A""", """F""", """G"""],
    """D""": ["""B"""],
    """E""": ["""A""", """B""", """D"""],
    """F""": ["""C"""],
    """G""": ["""C"""],
}


class     __SCREAMING_SNAKE_CASE					:






						def __init__(	self     ,						_UpperCamelCase     ,						_UpperCamelCase   ):






												"""simple docstring"""
												lowerCAmelCase__    						=						graph
												# mapping node to its parent in resulting breadth first tree
												lowerCAmelCase__    						=						{}
												lowerCAmelCase__    						=						source_vertex






						def       UpperCamelCase__      (	self   ):






												"""simple docstring"""
												lowerCAmelCase__    						=						{self.source_vertex}
												lowerCAmelCase__    						=						None
												lowerCAmelCase__    						=						[self.source_vertex]  # first in first out queue

												while queue:
																		lowerCAmelCase__    						=						queue.pop(0   )
																		for adjacent_vertex in self.graph[vertex]:
																								if adjacent_vertex not in visited:
																														visited.add(_UpperCamelCase   )
																														lowerCAmelCase__    						=						vertex
																														queue.append(_UpperCamelCase   )







						def       UpperCamelCase__      (	self     ,						_UpperCamelCase   ):






												"""simple docstring"""
												if target_vertex == self.source_vertex:
																		return self.source_vertex

												lowerCAmelCase__    						=						self.parent.get(_UpperCamelCase   )
												if target_vertex_parent is None:
																		lowerCAmelCase__    						=						(
																		    F"No path from vertex: {self.source_vertex} to vertex: {target_vertex}"
																		)
																		raise ValueError(_UpperCamelCase   )

												return self.shortest_path(_UpperCamelCase   ) + F"->{target_vertex}"


if __name__ == "__main__":
					__snake_case    :    Optional[Any]         =     Graph(graph, """G""")
					g.breath_first_search()
					print(g.shortest_path("""D"""))
					print(g.shortest_path("""G"""))
					print(g.shortest_path("""Foo"""))





