






import unittest

from transformers import MODEL_FOR_VISUAL_QUESTION_ANSWERING_MAPPING, is_vision_available
from transformers.pipelines import pipeline
from transformers.testing_utils import (
    is_pipeline_test,
    nested_simplify,
    require_tf,
    require_torch,
    require_vision,
    slow,
)

from .test_pipelines_common import ANY


if is_vision_available():
	from PIL import Image
else:


	class 					_snake_case						:






		@staticmethod
		def    lowerCAmelCase_							(		*UpperCamelCase					,**UpperCamelCase       )						->    List[str]:
						pass


@is_pipeline_test
@require_torch
@require_vision
class 					_snake_case						(			unittest.TestCase ):
	_A          =   MODEL_FOR_VISUAL_QUESTION_ANSWERING_MAPPING






	def    lowerCAmelCase_							(		self					,UpperCamelCase					,UpperCamelCase					,UpperCamelCase       )						->    Optional[Any]:
					snake_case__      :str         =   pipeline("visual-question-answering"					,model="hf-internal-testing/tiny-vilt-random-vqa"       )
					snake_case__      :str         =   [
					    {
					        "image": Image.open("./tests/fixtures/tests_samples/COCO/000000039769.png"       ),
					        "question": "How many cats are there?",
					    },
					    {
					        "image": "./tests/fixtures/tests_samples/COCO/000000039769.png",
					        "question": "How many cats are there?",
					    },
					]
					return vqa_pipeline, examples






	def    lowerCAmelCase_							(		self					,UpperCamelCase					,UpperCamelCase       )						->    List[str]:
					snake_case__      :Dict         =   vqa_pipeline(UpperCamelCase					,top_k=1       )
					self.assertEqual(
					    UpperCamelCase					,[
					        [{"score": ANY(UpperCamelCase       ), "answer": ANY(UpperCamelCase       )}],
					        [{"score": ANY(UpperCamelCase       ), "answer": ANY(UpperCamelCase       )}],
					    ]					,)






	@require_torch
	def    lowerCAmelCase_							(		self       )						->    int:
					snake_case__      :List[Any]         =   pipeline("visual-question-answering"					,model="hf-internal-testing/tiny-vilt-random-vqa"       )
					snake_case__      :Optional[int]         =   "./tests/fixtures/tests_samples/COCO/000000039769.png"
					snake_case__      :Optional[int]         =   "How many cats are there?"

					snake_case__      :str         =   vqa_pipeline(image=UpperCamelCase					,question="How many cats are there?"					,top_k=2       )
					self.assertEqual(
					    UpperCamelCase					,[{"score": ANY(UpperCamelCase       ), "answer": ANY(UpperCamelCase       )}, {"score": ANY(UpperCamelCase       ), "answer": ANY(UpperCamelCase       )}]       )

					snake_case__      :Optional[Any]         =   vqa_pipeline({"image": image, "question": question}					,top_k=2       )
					self.assertEqual(
					    UpperCamelCase					,[{"score": ANY(UpperCamelCase       ), "answer": ANY(UpperCamelCase       )}, {"score": ANY(UpperCamelCase       ), "answer": ANY(UpperCamelCase       )}]       )






	@slow
	@require_torch
	def    lowerCAmelCase_							(		self       )						->    List[Any]:
					snake_case__      :List[str]         =   pipeline("visual-question-answering"					,model="dandelin/vilt-b32-finetuned-vqa"       )
					snake_case__      :Tuple         =   "./tests/fixtures/tests_samples/COCO/000000039769.png"
					snake_case__      :Union[str, Any]         =   "How many cats are there?"

					snake_case__      :List[Any]         =   vqa_pipeline(image=UpperCamelCase					,question=UpperCamelCase					,top_k=2       )
					self.assertEqual(
					    nested_simplify(UpperCamelCase					,decimals=4       )					,[{"score": 0.8799, "answer": "2"}, {"score": 0.296, "answer": "1"}]       )

					snake_case__      :Optional[Any]         =   vqa_pipeline({"image": image, "question": question}					,top_k=2       )
					self.assertEqual(
					    nested_simplify(UpperCamelCase					,decimals=4       )					,[{"score": 0.8799, "answer": "2"}, {"score": 0.296, "answer": "1"}]       )

					snake_case__      :Tuple         =   vqa_pipeline(
					    [{"image": image, "question": question}, {"image": image, "question": question}]					,top_k=2       )
					self.assertEqual(
					    nested_simplify(UpperCamelCase					,decimals=4       )					,[[{"score": 0.8799, "answer": "2"}, {"score": 0.296, "answer": "1"}]] * 2					,)






	@require_tf
	@unittest.skip("Visual question answering not implemented in TF"       )
	def    lowerCAmelCase_							(		self       )						->    List[Any]:
					pass







from typing import Any





def 					lowercase_ (    __snake_case     :							list	,	__snake_case     :							list	,	__snake_case     :							dict	,	__snake_case     :							dict	,	__snake_case     :							dict	,	)     -> list:





				'''simple docstring'''


				_validation(
				    __snake_case	,	__snake_case	,	__snake_case	,	__snake_case	,	__snake_case	,	)
				# Creates data structures and fill initial step
				snake_case__      :dict         =   {}
				snake_case__      :dict         =   {}
				for state in states_space:
								snake_case__      :List[Any]         =   observations_space[0]
								snake_case__      :str         =   (
								    initial_probabilities[state] * emission_probabilities[state][observation]
								)
								snake_case__      :str         =   None

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

            # Update probabilities and pointers dicts
												snake_case__      :List[str]         =   (
												    probabilities[(arg_max, prior_observation)]
												    * transition_probabilities[arg_max][state]
												    * emission_probabilities[state][observation]
												)

												snake_case__      :List[str]         =   arg_max

    # The final observation
				snake_case__      :str         =   observations_space[len(__snake_case      ) - 1]

				# argmax for given final observation
				snake_case__      :Optional[int]         =   ""
				snake_case__      :List[str]         =   -1
				for k_state in states_space:
								snake_case__      :List[str]         =   probabilities[(k_state, final_observation)]
								if probability > max_probability:
												snake_case__      :List[str]         =   probability
												snake_case__      :int         =   k_state
				snake_case__      :Any         =   arg_max

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

				return result





def 					lowercase_ (    __snake_case     :							Any	,	__snake_case     :							Any	,	__snake_case     :							Any	,	__snake_case     :							Any	,	__snake_case     :							Any	,	)     -> None:





				'''simple docstring'''


				_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 					lowercase_ (    __snake_case     :							Any	,	__snake_case     :							Any	,	__snake_case     :							Any	,	__snake_case     :							Any	,	__snake_case     :							Any	,	)     -> None:





				'''simple docstring'''


				if not all(
				    [
				        observations_space,
				        states_space,
				        initial_probabilities,
				        transition_probabilities,
				        emission_probabilities,
				    ]      ):
								raise ValueError("There's an empty parameter"      )





def 					lowercase_ (    __snake_case     :							Any	,	__snake_case     :							Any      )     -> None:





				'''simple docstring'''


				_validate_list(__snake_case	,	"observations_space"      )
				_validate_list(__snake_case	,	"states_space"      )





def 					lowercase_ (    __snake_case     :							Any	,	__snake_case     :							str      )     -> None:





				'''simple docstring'''


				if not isinstance(_object	,	__snake_case      ):
								snake_case__      :Optional[int]         =   F'{var_name} must be a list'
								raise ValueError(__snake_case      )
				else:
								for x in _object:
												if not isinstance(__snake_case	,	__snake_case      ):
																snake_case__      :Any         =   F'{var_name} must be a list of strings'
																raise ValueError(__snake_case      )





def 					lowercase_ (    __snake_case     :							Any	,	__snake_case     :							Any	,	__snake_case     :							Any	,	)     -> None:





				'''simple docstring'''


				_validate_dict(__snake_case	,	"initial_probabilities"	,	__snake_case      )
				_validate_nested_dict(__snake_case	,	"transition_probabilities"      )
				_validate_nested_dict(__snake_case	,	"emission_probabilities"      )





def 					lowercase_ (    __snake_case     :							Any	,	__snake_case     :							str      )     -> None:





				'''simple docstring'''


				_validate_dict(_object	,	__snake_case	,	__snake_case      )
				for x in _object.values():
								_validate_dict(__snake_case	,	__snake_case	,	__snake_case	,	__snake_case      )





def 					lowercase_ (    __snake_case     :							Any	,	__snake_case     :							str	,	__snake_case     :							type	,	__snake_case     :							bool = False      )     -> None:





				'''simple docstring'''


				if not isinstance(_object	,	__snake_case      ):
								snake_case__      :str         =   F'{var_name} must be a dict'
								raise ValueError(__snake_case      )
				if not all(isinstance(__snake_case	,	__snake_case      ) for x in _object      ):
								snake_case__      :List[Any]         =   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()      ):
								snake_case__      :Optional[int]         =   "nested dictionary " if nested else ""
								snake_case__      :int         =   F'{var_name} {nested_text}all values must be {value_type.__name__}'
								raise ValueError(__snake_case      )


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

	testmod()