



import unittest

from transformers import MODEL_FOR_ZERO_SHOT_OBJECT_DETECTION_MAPPING, is_vision_available, 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        lowerCamelCase__			:




									'''simple docstring'''



									@staticmethod
									def 		lowerCAmelCase__      (*__lowerCamelCase		,**__lowerCamelCase )     ->			List[str]:

													"""simple docstring"""






													pass



@is_pipeline_test
@require_vision
@require_torch
class        lowerCamelCase__			(							unittest.TestCase):




		'''simple docstring'''



		snake_case_	=MODEL_FOR_ZERO_SHOT_OBJECT_DETECTION_MAPPING



		def 		lowerCAmelCase__      (self		,__lowerCamelCase		,__lowerCamelCase		,__lowerCamelCase )     ->			Optional[Any]:

						"""simple docstring"""






						lowerCAmelCase__     :				Dict												=     pipeline(
						    '''zero-shot-object-detection'''		,model='''hf-internal-testing/tiny-random-owlvit-object-detection''' )

						lowerCAmelCase__     :				Any												=     [
						    {
						        'image': './tests/fixtures/tests_samples/COCO/000000039769.png',
						        'candidate_labels': ['cat', 'remote', 'couch'],
						    }
						]
						return object_detector, examples



		def 		lowerCAmelCase__      (self		,__lowerCamelCase		,__lowerCamelCase )     ->			int:

						"""simple docstring"""






						lowerCAmelCase__     :				int												=     object_detector(examples[0]		,threshold=0.0 )

						lowerCAmelCase__     :				int												=     len(__lowerCamelCase )
						self.assertGreater(__lowerCamelCase		,0 )
						self.assertEqual(
						    __lowerCamelCase		,[
						        {
						            '''score''': ANY(__lowerCamelCase ),
						            '''label''': ANY(__lowerCamelCase ),
						            '''box''': {'''xmin''': ANY(__lowerCamelCase ), '''ymin''': ANY(__lowerCamelCase ), '''xmax''': ANY(__lowerCamelCase ), '''ymax''': ANY(__lowerCamelCase )},
						        }
						        for i in range(__lowerCamelCase )
						    ]		,)



		@require_tf
		@unittest.skip('''Zero Shot Object Detection not implemented in TF''' )
		def 		lowerCAmelCase__      (self )     ->			Union[str, Any]:

						"""simple docstring"""






						pass



		@require_torch
		def 		lowerCAmelCase__      (self )     ->			Any:

						"""simple docstring"""






						lowerCAmelCase__     :				str												=     pipeline(
						    '''zero-shot-object-detection'''		,model='''hf-internal-testing/tiny-random-owlvit-object-detection''' )

						lowerCAmelCase__     :				Tuple												=     object_detector(
						    '''./tests/fixtures/tests_samples/COCO/000000039769.png'''		,candidate_labels=['''cat''', '''remote''', '''couch''']		,threshold=0.64		,)

						self.assertEqual(
						    nested_simplify(__lowerCamelCase		,decimals=4 )		,[
						        {'''score''': 0.7235, '''label''': '''cat''', '''box''': {'''xmin''': 2_04, '''ymin''': 1_67, '''xmax''': 2_32, '''ymax''': 1_90}},
						        {'''score''': 0.7218, '''label''': '''remote''', '''box''': {'''xmin''': 2_04, '''ymin''': 1_67, '''xmax''': 2_32, '''ymax''': 1_90}},
						        {'''score''': 0.7184, '''label''': '''couch''', '''box''': {'''xmin''': 2_04, '''ymin''': 1_67, '''xmax''': 2_32, '''ymax''': 1_90}},
						        {'''score''': 0.6748, '''label''': '''remote''', '''box''': {'''xmin''': 5_71, '''ymin''': 83, '''xmax''': 5_98, '''ymax''': 1_03}},
						        {'''score''': 0.6656, '''label''': '''cat''', '''box''': {'''xmin''': 5_71, '''ymin''': 83, '''xmax''': 5_98, '''ymax''': 1_03}},
						        {'''score''': 0.6614, '''label''': '''couch''', '''box''': {'''xmin''': 5_71, '''ymin''': 83, '''xmax''': 5_98, '''ymax''': 1_03}},
						        {'''score''': 0.6456, '''label''': '''remote''', '''box''': {'''xmin''': 4_94, '''ymin''': 1_05, '''xmax''': 5_21, '''ymax''': 1_27}},
						        {'''score''': 0.642, '''label''': '''remote''', '''box''': {'''xmin''': 67, '''ymin''': 2_74, '''xmax''': 93, '''ymax''': 2_97}},
						        {'''score''': 0.6419, '''label''': '''cat''', '''box''': {'''xmin''': 4_94, '''ymin''': 1_05, '''xmax''': 5_21, '''ymax''': 1_27}},
						    ]		,)

						lowerCAmelCase__     :				str												=     object_detector(
						    [
						        {
						            '''image''': '''./tests/fixtures/tests_samples/COCO/000000039769.png''',
						            '''candidate_labels''': ['''cat''', '''remote''', '''couch'''],
						        }
						    ]		,threshold=0.64		,)

						self.assertEqual(
						    nested_simplify(__lowerCamelCase		,decimals=4 )		,[
						        [
						            {'''score''': 0.7235, '''label''': '''cat''', '''box''': {'''xmin''': 2_04, '''ymin''': 1_67, '''xmax''': 2_32, '''ymax''': 1_90}},
						            {'''score''': 0.7218, '''label''': '''remote''', '''box''': {'''xmin''': 2_04, '''ymin''': 1_67, '''xmax''': 2_32, '''ymax''': 1_90}},
						            {'''score''': 0.7184, '''label''': '''couch''', '''box''': {'''xmin''': 2_04, '''ymin''': 1_67, '''xmax''': 2_32, '''ymax''': 1_90}},
						            {'''score''': 0.6748, '''label''': '''remote''', '''box''': {'''xmin''': 5_71, '''ymin''': 83, '''xmax''': 5_98, '''ymax''': 1_03}},
						            {'''score''': 0.6656, '''label''': '''cat''', '''box''': {'''xmin''': 5_71, '''ymin''': 83, '''xmax''': 5_98, '''ymax''': 1_03}},
						            {'''score''': 0.6614, '''label''': '''couch''', '''box''': {'''xmin''': 5_71, '''ymin''': 83, '''xmax''': 5_98, '''ymax''': 1_03}},
						            {'''score''': 0.6456, '''label''': '''remote''', '''box''': {'''xmin''': 4_94, '''ymin''': 1_05, '''xmax''': 5_21, '''ymax''': 1_27}},
						            {'''score''': 0.642, '''label''': '''remote''', '''box''': {'''xmin''': 67, '''ymin''': 2_74, '''xmax''': 93, '''ymax''': 2_97}},
						            {'''score''': 0.6419, '''label''': '''cat''', '''box''': {'''xmin''': 4_94, '''ymin''': 1_05, '''xmax''': 5_21, '''ymax''': 1_27}},
						        ]
						    ]		,)



		@require_torch
		@slow
		def 		lowerCAmelCase__      (self )     ->			List[Any]:

						"""simple docstring"""






						lowerCAmelCase__     :				Any												=     pipeline('''zero-shot-object-detection''' )

						lowerCAmelCase__     :				Dict												=     object_detector(
						    '''http://images.cocodataset.org/val2017/000000039769.jpg'''		,candidate_labels=['''cat''', '''remote''', '''couch''']		,)
						self.assertEqual(
						    nested_simplify(__lowerCamelCase		,decimals=4 )		,[
						        {'''score''': 0.2868, '''label''': '''cat''', '''box''': {'''xmin''': 3_24, '''ymin''': 20, '''xmax''': 6_40, '''ymax''': 3_73}},
						        {'''score''': 0.277, '''label''': '''remote''', '''box''': {'''xmin''': 40, '''ymin''': 72, '''xmax''': 1_77, '''ymax''': 1_15}},
						        {'''score''': 0.2537, '''label''': '''cat''', '''box''': {'''xmin''': 1, '''ymin''': 55, '''xmax''': 3_15, '''ymax''': 4_72}},
						        {'''score''': 0.1474, '''label''': '''remote''', '''box''': {'''xmin''': 3_35, '''ymin''': 74, '''xmax''': 3_71, '''ymax''': 1_87}},
						        {'''score''': 0.1208, '''label''': '''couch''', '''box''': {'''xmin''': 4, '''ymin''': 0, '''xmax''': 6_42, '''ymax''': 4_76}},
						    ]		,)

						lowerCAmelCase__     :				List[Any]												=     object_detector(
						    [
						        {
						            '''image''': '''http://images.cocodataset.org/val2017/000000039769.jpg''',
						            '''candidate_labels''': ['''cat''', '''remote''', '''couch'''],
						        },
						        {
						            '''image''': '''http://images.cocodataset.org/val2017/000000039769.jpg''',
						            '''candidate_labels''': ['''cat''', '''remote''', '''couch'''],
						        },
						    ]		,)
						self.assertEqual(
						    nested_simplify(__lowerCamelCase		,decimals=4 )		,[
						        [
						            {'''score''': 0.2868, '''label''': '''cat''', '''box''': {'''xmin''': 3_24, '''ymin''': 20, '''xmax''': 6_40, '''ymax''': 3_73}},
						            {'''score''': 0.277, '''label''': '''remote''', '''box''': {'''xmin''': 40, '''ymin''': 72, '''xmax''': 1_77, '''ymax''': 1_15}},
						            {'''score''': 0.2537, '''label''': '''cat''', '''box''': {'''xmin''': 1, '''ymin''': 55, '''xmax''': 3_15, '''ymax''': 4_72}},
						            {'''score''': 0.1474, '''label''': '''remote''', '''box''': {'''xmin''': 3_35, '''ymin''': 74, '''xmax''': 3_71, '''ymax''': 1_87}},
						            {'''score''': 0.1208, '''label''': '''couch''', '''box''': {'''xmin''': 4, '''ymin''': 0, '''xmax''': 6_42, '''ymax''': 4_76}},
						        ],
						        [
						            {'''score''': 0.2868, '''label''': '''cat''', '''box''': {'''xmin''': 3_24, '''ymin''': 20, '''xmax''': 6_40, '''ymax''': 3_73}},
						            {'''score''': 0.277, '''label''': '''remote''', '''box''': {'''xmin''': 40, '''ymin''': 72, '''xmax''': 1_77, '''ymax''': 1_15}},
						            {'''score''': 0.2537, '''label''': '''cat''', '''box''': {'''xmin''': 1, '''ymin''': 55, '''xmax''': 3_15, '''ymax''': 4_72}},
						            {'''score''': 0.1474, '''label''': '''remote''', '''box''': {'''xmin''': 3_35, '''ymin''': 74, '''xmax''': 3_71, '''ymax''': 1_87}},
						            {'''score''': 0.1208, '''label''': '''couch''', '''box''': {'''xmin''': 4, '''ymin''': 0, '''xmax''': 6_42, '''ymax''': 4_76}},
						        ],
						    ]		,)



		@require_tf
		@unittest.skip('''Zero Shot Object Detection not implemented in TF''' )
		def 		lowerCAmelCase__      (self )     ->			List[Any]:

						"""simple docstring"""






						pass



		@require_torch
		@slow
		def 		lowerCAmelCase__      (self )     ->			List[Any]:

						"""simple docstring"""






						lowerCAmelCase__     :				List[str]												=     0.2
						lowerCAmelCase__     :				Union[str, Any]												=     pipeline('''zero-shot-object-detection''' )

						lowerCAmelCase__     :				Union[str, Any]												=     object_detector(
						    '''http://images.cocodataset.org/val2017/000000039769.jpg'''		,candidate_labels=['''cat''', '''remote''', '''couch''']		,threshold=__lowerCamelCase		,)
						self.assertEqual(
						    nested_simplify(__lowerCamelCase		,decimals=4 )		,[
						        {'''score''': 0.2868, '''label''': '''cat''', '''box''': {'''xmin''': 3_24, '''ymin''': 20, '''xmax''': 6_40, '''ymax''': 3_73}},
						        {'''score''': 0.277, '''label''': '''remote''', '''box''': {'''xmin''': 40, '''ymin''': 72, '''xmax''': 1_77, '''ymax''': 1_15}},
						        {'''score''': 0.2537, '''label''': '''cat''', '''box''': {'''xmin''': 1, '''ymin''': 55, '''xmax''': 3_15, '''ymax''': 4_72}},
						    ]		,)



		@require_torch
		@slow
		def 		lowerCAmelCase__      (self )     ->			List[Any]:

						"""simple docstring"""






						lowerCAmelCase__     :				Tuple												=     2
						lowerCAmelCase__     :				Any												=     pipeline('''zero-shot-object-detection''' )

						lowerCAmelCase__     :				Optional[Any]												=     object_detector(
						    '''http://images.cocodataset.org/val2017/000000039769.jpg'''		,candidate_labels=['''cat''', '''remote''', '''couch''']		,top_k=__lowerCamelCase		,)
						self.assertEqual(
						    nested_simplify(__lowerCamelCase		,decimals=4 )		,[
						        {'''score''': 0.2868, '''label''': '''cat''', '''box''': {'''xmin''': 3_24, '''ymin''': 20, '''xmax''': 6_40, '''ymax''': 3_73}},
						        {'''score''': 0.277, '''label''': '''remote''', '''box''': {'''xmin''': 40, '''ymin''': 72, '''xmax''': 1_77, '''ymax''': 1_15}},
						    ]		,)




from __future__ import annotations

from typing import Any


class       SCREAMING_SNAKE_CASE__					:





    def __init__(      self						,   a						,   a						,   a = 0):
         lowercase__      , lowercase__    :   Dict      =       row, column
         lowercase__    :   Optional[Any]      =       [[default_value for c in range(a)] for r in range(a)]





    def __str__(      self):
         lowercase__    :   Tuple      =       f"""Matrix consist of {self.row} rows and {self.column} columns\n"""

         # Make string identifier
         lowercase__    :   Optional[int]      =       0
         for row_vector in self.array:
              for obj in row_vector:
                   lowercase__    :   List[str]      =       max(a						,   len(str(a)))
         lowercase__    :   Optional[int]      =       f"""%{max_element_length}s"""

         # Make string and return
         def single_line(a) -> str:
              nonlocal string_format_identifier
              lowercase__    :   Tuple      =       '['
              line += ", ".join(string_format_identifier % (obj,) for obj in row_vector)
              line += "]"
              return line

         s += "\n".join(single_line(a) for row_vector in self.array)
         return s





    def __repr__(      self):
         return str(self)





    def       snake_case_				(      self						,   a):
         if not (isinstance(a						,   (list, tuple)) and len(a) == 2):
              return False
         elif not (0 <= loc[0] < self.row and 0 <= loc[1] < self.column):
              return False
         else:
              return True





    def __getitem__(      self						,   a):
         assert self.validate_indicies(a)
         return self.array[loc[0]][loc[1]]





    def __setitem__(      self						,   a						,   a):
         assert self.validate_indicies(a)
         lowercase__    :   List[str]      =       value





    def __add__(      self						,   a):
         assert isinstance(a						,   a)
         assert self.row == another.row and self.column == another.column

         # Add
         lowercase__    :   List[str]      =       Matrix(self.row						,   self.column)
         for r in range(self.row):
              for c in range(self.column):
                   lowercase__    :   Dict      =       self[r, c] + another[r, c]
         return result





    def __neg__(      self):
         lowercase__    :   List[Any]      =       Matrix(self.row						,   self.column)
         for r in range(self.row):
              for c in range(self.column):
                   lowercase__    :   int      =       -self[r, c]
         return result





    def __sub__(      self						,   a):
         return self + (-another)





    def __mul__(      self						,   a):

         if isinstance(a						,   (int, float)):  # Scalar multiplication
              lowercase__    :   Optional[Any]      =       Matrix(self.row						,   self.column)
              for r in range(self.row):
                   for c in range(self.column):
                        lowercase__    :   Union[str, Any]      =       self[r, c] * another
              return result
         elif isinstance(a						,   a):  # Matrix multiplication
              assert self.column == another.row
              lowercase__    :   List[Any]      =       Matrix(self.row						,   another.column)
              for r in range(self.row):
                   for c in range(another.column):
                        for i in range(self.column):
                             result[r, c] += self[r, i] * another[i, c]
              return result
         else:
              lowercase__    :   Optional[Any]      =       f"""Unsupported type given for another ({type(a)})"""
              raise TypeError(a)





    def       snake_case_				(      self):
         lowercase__    :   Optional[int]      =       Matrix(self.column						,   self.row)
         for r in range(self.row):
              for c in range(self.column):
                   lowercase__    :   str      =       self[r, c]
         return result





    def       snake_case_				(      self						,   a						,   a):
         assert isinstance(a						,   a) and isinstance(a						,   a)
         assert self.row == self.column == u.row == v.row  # u, v should be column vector
         assert u.column == v.column == 1  # u, v should be column vector

         # Calculate
         lowercase__    :   int      =       v.transpose()
         lowercase__    :   Tuple      =       (v_t * self * u)[0, 0] + 1
         if numerator_factor == 0:
              return None  # It's not invertable
         return self - ((self * u) * (v_t * self) * (1.0 / numerator_factor))


# Testing
if __name__ == "__main__":

       def 	snake_case__			(    ):



            '''simple docstring'''





            lowercase__    :   Any      =       Matrix(3	,     3	,     0			)
            for i in range(3			):
                 lowercase__    :   str      =       1
            print(f"""a^(-1) is {ainv}"""			)
            # u, v
            lowercase__    :   Optional[Any]      =       Matrix(3	,     1	,     0			)
            lowercase__      , lowercase__      , lowercase__    :   List[Any]      =       1, 2, -3
            lowercase__    :   Union[str, Any]      =       Matrix(3	,     1	,     0			)
            lowercase__      , lowercase__      , lowercase__    :   Any      =       4, -2, 5
            print(f"""u is {u}"""			)
            print(f"""v is {v}"""			)
            print(f"""uv^T is {u * v.transpose()}"""			)
            # Sherman Morrison
            print(f"""(a + uv^T)^(-1) is {ainv.sherman_morrison(SCREAMING_SNAKE_CASE_	,     SCREAMING_SNAKE_CASE_			)}"""			)

       def 	snake_case__			(    ):



            '''simple docstring'''





            import doctest

            doctest.testmod()

       testa()

