




"""simple docstring"""




import json
import os
import shutil
import tempfile
import unittest

import numpy as np

from transformers import BertTokenizerFast
from transformers.models.bert.tokenization_bert import VOCAB_FILES_NAMES, BertTokenizer
from transformers.testing_utils import require_tokenizers, require_vision
from transformers.utils import IMAGE_PROCESSOR_NAME, is_vision_available


if is_vision_available():
					from PIL import Image

					from transformers import VisionTextDualEncoderProcessor, ViTImageProcessor






@require_tokenizers
@require_vision
class     __magic_name__							(       unittest.TestCase				):






				'''simple docstring'''





				def    _lowerCAmelCase				(       self ):





							"""simple docstring"""
							lowerCamelCase			      =					tempfile.mkdtemp()

							# fmt: off
							lowerCamelCase			      =					["""[UNK]""", """[CLS]""", """[SEP]""", """[PAD]""", """[MASK]""", """want""", """##want""", """##ed""", """wa""", """un""", """runn""", """##ing""", """,""", """low""", """lowest"""]
							# fmt: on
							lowerCamelCase			      =					os.path.join(self.tmpdirname		, VOCAB_FILES_NAMES["""vocab_file"""] )
							with open(self.vocab_file		, """w"""		, encoding="""utf-8""" ) as vocab_writer:
										vocab_writer.write("""""".join([x + """\n""" for x in vocab_tokens] ) )

							lowerCamelCase			      =					{
							    """do_resize""": True,
							    """size""": {"""height""": 18, """width""": 18},
							    """do_normalize""": True,
							    """image_mean""": [0.5, 0.5, 0.5],
							    """image_std""": [0.5, 0.5, 0.5],
							}
							lowerCamelCase			      =					os.path.join(self.tmpdirname		, _a )
							with open(self.image_processor_file		, """w"""		, encoding="""utf-8""" ) as fp:
										json.dump(_a		, _a )





				def    _lowerCAmelCase				(       self		, **_a ):





							"""simple docstring"""
							return BertTokenizer.from_pretrained(self.tmpdirname		, **_a )





				def    _lowerCAmelCase				(       self		, **_a ):





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





				def    _lowerCAmelCase				(       self ):





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





				def    _lowerCAmelCase				(       self ):





							"""simple docstring"""
							lowerCamelCase			      =					[np.random.randint(255		, size=(3, 30, 400)		, dtype=np.uinta )]

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

							return image_inputs





				def    _lowerCAmelCase				(       self ):





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

							lowerCamelCase			      =					VisionTextDualEncoderProcessor(tokenizer=_a		, image_processor=_a )

							processor.save_pretrained(self.tmpdirname )
							lowerCamelCase			      =					VisionTextDualEncoderProcessor.from_pretrained(self.tmpdirname )

							self.assertEqual(processor.tokenizer.get_vocab()		, tokenizer.get_vocab() )
							self.assertIsInstance(processor.tokenizer		, (BertTokenizer, BertTokenizerFast) )

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





				def    _lowerCAmelCase				(       self ):





							"""simple docstring"""
							lowerCamelCase			      =					VisionTextDualEncoderProcessor(
							    tokenizer=self.get_tokenizer()		, image_processor=self.get_image_processor() )
							processor.save_pretrained(self.tmpdirname )

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

							lowerCamelCase			      =					VisionTextDualEncoderProcessor.from_pretrained(
							    self.tmpdirname		, bos_token="""(BOS)"""		, eos_token="""(EOS)"""		, do_normalize=_a		, padding_value=1.0 )

							self.assertEqual(processor.tokenizer.get_vocab()		, tokenizer_add_kwargs.get_vocab() )
							self.assertIsInstance(processor.tokenizer		, (BertTokenizer, BertTokenizerFast) )

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





				def    _lowerCAmelCase				(       self ):





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

							lowerCamelCase			      =					VisionTextDualEncoderProcessor(tokenizer=_a		, image_processor=_a )

							lowerCamelCase			      =					self.prepare_image_inputs()

							lowerCamelCase			      =					image_processor(_a		, return_tensors="""np""" )
							lowerCamelCase			      =					processor(images=_a		, 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 ):





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

							lowerCamelCase			      =					VisionTextDualEncoderProcessor(tokenizer=_a		, image_processor=_a )

							lowerCamelCase			      =					"""lower newer"""

							lowerCamelCase			      =					processor(text=_a )

							lowerCamelCase			      =					tokenizer(_a )

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





				def    _lowerCAmelCase				(       self ):





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

							lowerCamelCase			      =					VisionTextDualEncoderProcessor(tokenizer=_a		, image_processor=_a )

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

							lowerCamelCase			      =					processor(text=_a		, images=_a )

							self.assertListEqual(list(inputs.keys() )		, ["""input_ids""", """token_type_ids""", """attention_mask""", """pixel_values"""] )

							# test if it raises when no input is passed
							with self.assertRaises(_a ):
										processor()





				def    _lowerCAmelCase				(       self ):





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

							lowerCamelCase			      =					VisionTextDualEncoderProcessor(tokenizer=_a		, image_processor=_a )

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

							lowerCamelCase			      =					processor.batch_decode(_a )
							lowerCamelCase			      =					tokenizer.batch_decode(_a )

							self.assertListEqual(_a		, _a )





				def    _lowerCAmelCase				(       self ):





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

							lowerCamelCase			      =					VisionTextDualEncoderProcessor(tokenizer=_a		, image_processor=_a )

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

							lowerCamelCase			      =					processor(text=_a		, images=_a )

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









"""simple docstring"""




from typing import Any



def     a__ (				snake_case__       , snake_case__       , snake_case__       , snake_case__       , snake_case__       , )						->					list:
			_validation(
			    snake_case__       , snake_case__       , snake_case__       , snake_case__       , snake_case__       , )
			# Creates data structures and fill initial step
			lowerCamelCase			      =					{}
			lowerCamelCase			      =					{}
			for state in states_space:
						lowerCamelCase			      =					observations_space[0]
						lowerCamelCase			      =					(
						    initial_probabilities[state] * emission_probabilities[state][observation]
						)
						lowerCamelCase			      =					None

			# Fills the data structure with the probabilities of
			# different transitions and pointers to previous states
			for o in range(1       , len(snake_case__				)				):
						lowerCamelCase			      =					observations_space[o]
						lowerCamelCase			      =					observations_space[o - 1]
						for state in states_space:
									# Calculates the argmax for probability function
									lowerCamelCase			      =					""""""
									lowerCamelCase			      =					-1
									for k_state in states_space:
												lowerCamelCase			      =					(
												    probabilities[(k_state, prior_observation)]
												    * transition_probabilities[k_state][state]
												    * emission_probabilities[state][observation]
												)
												if probability > max_probability:
															lowerCamelCase			      =					probability
															lowerCamelCase			      =					k_state

            # Update probabilities and pointers dicts
									lowerCamelCase			      =					(
									    probabilities[(arg_max, prior_observation)]
									    * transition_probabilities[arg_max][state]
									    * emission_probabilities[state][observation]
									)

									lowerCamelCase			      =					arg_max

    # The final observation
			lowerCamelCase			      =					observations_space[len(snake_case__				) - 1]

			# argmax for given final observation
			lowerCamelCase			      =					""""""
			lowerCamelCase			      =					-1
			for k_state in states_space:
						lowerCamelCase			      =					probabilities[(k_state, final_observation)]
						if probability > max_probability:
									lowerCamelCase			      =					probability
									lowerCamelCase			      =					k_state
			lowerCamelCase			      =					arg_max

			# Process pointers backwards
			lowerCamelCase			      =					last_state
			lowerCamelCase			      =					[]
			for o in range(len(snake_case__				) - 1       , -1       , -1				):
						result.append(snake_case__				)
						lowerCamelCase			      =					pointers[previous, observations_space[o]]
			result.reverse()

			return result



def     a__ (				snake_case__       , snake_case__       , snake_case__       , snake_case__       , snake_case__       , )						->					None:
			_validate_not_empty(
			    snake_case__       , snake_case__       , snake_case__       , snake_case__       , snake_case__       , )
			_validate_lists(snake_case__       , snake_case__				)
			_validate_dicts(
			    snake_case__       , snake_case__       , snake_case__				)



def     a__ (				snake_case__       , snake_case__       , snake_case__       , snake_case__       , snake_case__       , )						->					None:
			if not all(
			    [
			        observations_space,
			        states_space,
			        initial_probabilities,
			        transition_probabilities,
			        emission_probabilities,
			    ]				):
						raise ValueError("""There's an empty parameter"""				)



def     a__ (				snake_case__       , snake_case__				)						->					None:
			_validate_list(snake_case__       , """observations_space"""				)
			_validate_list(snake_case__       , """states_space"""				)



def     a__ (				snake_case__       , snake_case__				)						->					None:
			if not isinstance(_object       , snake_case__				):
						lowerCamelCase			      =					F'{var_name} must be a list'
						raise ValueError(snake_case__				)
			else:
						for x in _object:
									if not isinstance(snake_case__       , snake_case__				):
												lowerCamelCase			      =					F'{var_name} must be a list of strings'
												raise ValueError(snake_case__				)



def     a__ (				snake_case__       , snake_case__       , snake_case__       , )						->					None:
			_validate_dict(snake_case__       , """initial_probabilities"""       , snake_case__				)
			_validate_nested_dict(snake_case__       , """transition_probabilities"""				)
			_validate_nested_dict(snake_case__       , """emission_probabilities"""				)



def     a__ (				snake_case__       , snake_case__				)						->					None:
			_validate_dict(_object       , snake_case__       , snake_case__				)
			for x in _object.values():
						_validate_dict(snake_case__       , snake_case__       , snake_case__       , snake_case__				)



def     a__ (				snake_case__       , snake_case__       , snake_case__       , snake_case__ = False				)						->					None:
			if not isinstance(_object       , snake_case__				):
						lowerCamelCase			      =					F'{var_name} must be a dict'
						raise ValueError(snake_case__				)
			if not all(isinstance(snake_case__       , snake_case__				) for x in _object				):
						lowerCamelCase			      =					F'{var_name} all keys must be strings'
						raise ValueError(snake_case__				)
			if not all(isinstance(snake_case__       , snake_case__				) for x in _object.values()				):
						lowerCamelCase			      =					"""nested dictionary """ if nested else """"""
						lowerCamelCase			      =					F'{var_name} {nested_text}all values must be {value_type.__name__}'
						raise ValueError(snake_case__				)


if __name__ == "__main__":
					from doctest import testmod

					testmod()



