






'''simple docstring'''
import hashlib
import unittest
from typing import Dict

import numpy as np

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


if is_vision_available():
 from PIL import Image
else:


 class 							_UpperCAmelCase    :




     @staticmethod
     def 					lowerCAmelCase__					(      *a	:							Tuple	,  **a	:							List[Any]      ):






        '''simple docstring'''






        pass




def 		__SCREAMING_SNAKE_CASE       (	_UpperCamelCase				):


   """simple docstring"""




   lowercase_						:     Union[str, Any]							     =  hashlib.mda(image.tobytes()				)
   return m.hexdigest()[:10]




def 		__SCREAMING_SNAKE_CASE       (	_UpperCamelCase				):


   """simple docstring"""




   lowercase_						:     Optional[int]							     =  np.array(_UpperCamelCase				)
   lowercase_						:     Tuple							     =  npimg.shape
   return {"hash": hashimage(_UpperCamelCase				), "shape": shape}





@is_pipeline_test
@require_vision
@require_torch
class 							_UpperCAmelCase    (		unittest.TestCase      ):
    __lowerCamelCase: Any									=     dict(
        (list(MODEL_FOR_MASK_GENERATION_MAPPING.items()      ) if MODEL_FOR_MASK_GENERATION_MAPPING else [])      )
    __lowerCamelCase: str									=     dict(
        (list(TF_MODEL_FOR_MASK_GENERATION_MAPPING.items()      ) if TF_MODEL_FOR_MASK_GENERATION_MAPPING else [])      )




    def 					lowerCAmelCase__					(      self	:							str	,  a	:							List[str]	,  a	:							int	,  a	:							str      ):






       '''simple docstring'''






       lowercase_						:     Union[str, Any]							     =  MaskGenerationPipeline(model=a	,  image_processor=a      )
       return image_segmenter, [
           "./tests/fixtures/tests_samples/COCO/000000039769.png",
           "./tests/fixtures/tests_samples/COCO/000000039769.png",
       ]




    def 					lowerCAmelCase__					(      self	:							List[Any]	,  a	:							Union[str, Any]	,  a	:							str      ):






       '''simple docstring'''






       pass




    @require_tf
    @unittest.skip("Image segmentation not implemented in TF"      )
    def 					lowerCAmelCase__					(      self	:							Union[str, Any]      ):






       '''simple docstring'''






       pass




    @slow
    @require_torch
    def 					lowerCAmelCase__					(      self	:							Optional[int]      ):






       '''simple docstring'''






       lowercase_						:     List[str]							     =  pipeline("mask-generation"	,  model="facebook/sam-vit-huge"      )

       lowercase_						:     Optional[Any]							     =  image_segmenter("http://images.cocodataset.org/val2017/000000039769.jpg"	,  points_per_batch=2_5_6      )

       # Shortening by hashing
       lowercase_						:     Optional[int]							     =  []
       for i, o in enumerate(outputs["masks"]      ):
          new_outupt += [{"mask": mask_to_test_readable(a      ), "scores": outputs["scores"][i]}]

       # fmt: off
       self.assertEqual(
           nested_simplify(a	,  decimals=4      )	,  [
               {"mask": {"hash": "115ad19f5f", "shape": (4_8_0, 6_4_0)}, "scores": 1.0444},
               {"mask": {"hash": "6affa964c6", "shape": (4_8_0, 6_4_0)}, "scores": 1.021},
               {"mask": {"hash": "dfe28a0388", "shape": (4_8_0, 6_4_0)}, "scores": 1.0167},
               {"mask": {"hash": "c0a5f4a318", "shape": (4_8_0, 6_4_0)}, "scores": 1.0132},
               {"mask": {"hash": "fe8065c197", "shape": (4_8_0, 6_4_0)}, "scores": 1.0053},
               {"mask": {"hash": "e2d0b7a0b7", "shape": (4_8_0, 6_4_0)}, "scores": 0.9967},
               {"mask": {"hash": "453c7844bd", "shape": (4_8_0, 6_4_0)}, "scores": 0.993},
               {"mask": {"hash": "3d44f2926d", "shape": (4_8_0, 6_4_0)}, "scores": 0.9909},
               {"mask": {"hash": "64033ddc3f", "shape": (4_8_0, 6_4_0)}, "scores": 0.9879},
               {"mask": {"hash": "801064ff79", "shape": (4_8_0, 6_4_0)}, "scores": 0.9834},
               {"mask": {"hash": "6172f276ef", "shape": (4_8_0, 6_4_0)}, "scores": 0.9716},
               {"mask": {"hash": "b49e60e084", "shape": (4_8_0, 6_4_0)}, "scores": 0.9612},
               {"mask": {"hash": "a811e775fd", "shape": (4_8_0, 6_4_0)}, "scores": 0.9599},
               {"mask": {"hash": "a6a8ebcf4b", "shape": (4_8_0, 6_4_0)}, "scores": 0.9552},
               {"mask": {"hash": "9d8257e080", "shape": (4_8_0, 6_4_0)}, "scores": 0.9532},
               {"mask": {"hash": "32de6454a8", "shape": (4_8_0, 6_4_0)}, "scores": 0.9516},
               {"mask": {"hash": "af3d4af2c8", "shape": (4_8_0, 6_4_0)}, "scores": 0.9499},
               {"mask": {"hash": "3c6db475fb", "shape": (4_8_0, 6_4_0)}, "scores": 0.9483},
               {"mask": {"hash": "c290813fb9", "shape": (4_8_0, 6_4_0)}, "scores": 0.9464},
               {"mask": {"hash": "b6f0b8f606", "shape": (4_8_0, 6_4_0)}, "scores": 0.943},
               {"mask": {"hash": "92ce16bfdf", "shape": (4_8_0, 6_4_0)}, "scores": 0.943},
               {"mask": {"hash": "c749b25868", "shape": (4_8_0, 6_4_0)}, "scores": 0.9408},
               {"mask": {"hash": "efb6cab859", "shape": (4_8_0, 6_4_0)}, "scores": 0.9335},
               {"mask": {"hash": "1ff2eafb30", "shape": (4_8_0, 6_4_0)}, "scores": 0.9326},
               {"mask": {"hash": "788b798e24", "shape": (4_8_0, 6_4_0)}, "scores": 0.9262},
               {"mask": {"hash": "abea804f0e", "shape": (4_8_0, 6_4_0)}, "scores": 0.8999},
               {"mask": {"hash": "7b9e8ddb73", "shape": (4_8_0, 6_4_0)}, "scores": 0.8986},
               {"mask": {"hash": "cd24047c8a", "shape": (4_8_0, 6_4_0)}, "scores": 0.8984},
               {"mask": {"hash": "6943e6bcbd", "shape": (4_8_0, 6_4_0)}, "scores": 0.8873},
               {"mask": {"hash": "b5f47c9191", "shape": (4_8_0, 6_4_0)}, "scores": 0.8871}
           ]	,  )
       # fmt: on





    @require_torch
    @slow
    def 					lowerCAmelCase__					(      self	:							int      ):






       '''simple docstring'''






       lowercase_						:     Dict							     =  "facebook/sam-vit-huge"
       lowercase_						:     Optional[int]							     =  pipeline("mask-generation"	,  model=a      )

       lowercase_						:     int							     =  image_segmenter(
           "http://images.cocodataset.org/val2017/000000039769.jpg"	,  pred_iou_thresh=1	,  points_per_batch=2_5_6      )

       # Shortening by hashing
       lowercase_						:     List[Any]							     =  []
       for i, o in enumerate(outputs["masks"]      ):
          new_outupt += [{"mask": mask_to_test_readable(a      ), "scores": outputs["scores"][i]}]

       self.assertEqual(
           nested_simplify(a	,  decimals=4      )	,  [
               {"mask": {"hash": "115ad19f5f", "shape": (4_8_0, 6_4_0)}, "scores": 1.0444},
               {"mask": {"hash": "6affa964c6", "shape": (4_8_0, 6_4_0)}, "scores": 1.0210},
               {"mask": {"hash": "dfe28a0388", "shape": (4_8_0, 6_4_0)}, "scores": 1.0167},
               {"mask": {"hash": "c0a5f4a318", "shape": (4_8_0, 6_4_0)}, "scores": 1.0132},
               {"mask": {"hash": "fe8065c197", "shape": (4_8_0, 6_4_0)}, "scores": 1.0053},
           ]	,  )












'''simple docstring'''
import contextlib
import importlib
import io
import unittest

import transformers

# Try to import everything from transformers to ensure every object can be loaded.
from transformers import *  # noqa F406
from transformers.testing_utils import DUMMY_UNKNOWN_IDENTIFIER, require_flax, require_tf, require_torch
from transformers.utils import ContextManagers, find_labels, is_flax_available, is_tf_available, is_torch_available


if is_torch_available():
 from transformers import BertForPreTraining, BertForQuestionAnswering, BertForSequenceClassification

if is_tf_available():
 from transformers import TFBertForPreTraining, TFBertForQuestionAnswering, TFBertForSequenceClassification

if is_flax_available():
 from transformers import FlaxBertForPreTraining, FlaxBertForQuestionAnswering, FlaxBertForSequenceClassification


UpperCamelCase__			=      DUMMY_UNKNOWN_IDENTIFIER
# An actual model hosted on huggingface.co

UpperCamelCase__			=      'main'
# Default branch name
UpperCamelCase__			=      'f2c752cfc5c0ab6f4bdec59acea69eefbee381c2'
# One particular commit (not the top of `main`)
UpperCamelCase__			=      'aaaaaaa'
# This commit does not exist, so we should 404.

UpperCamelCase__			=      'd9e9f15bc825e4b2c9249e9578f884bbcb5e3684'
# Sha-1 of config.json on the top of `main`, for checking purposes
UpperCamelCase__			=      '4b243c475af8d0a7754e87d7d096c92e5199ec2fe168a2ee7998e3b8e9bcb1d3'




@contextlib.contextmanager
def 		__SCREAMING_SNAKE_CASE       (	):


   """simple docstring"""




   print("Welcome!"				)
   yield
   print("Bye!"				)




@contextlib.contextmanager
def 		__SCREAMING_SNAKE_CASE       (	):


   """simple docstring"""




   print("Bonjour!"				)
   yield
   print("Au revoir!"				)


class 							_UpperCAmelCase    (		unittest.TestCase      ):




    def 					lowerCAmelCase__					(      self	:							int      ):






       '''simple docstring'''






       assert transformers.__spec__ is not None
       assert importlib.util.find_spec("transformers"      ) is not None


class 							_UpperCAmelCase    (		unittest.TestCase      ):




    @unittest.mock.patch("sys.stdout"	,  new_callable=io.StringIO      )
    def 					lowerCAmelCase__					(      self	:							str	,  a	:							List[str]      ):






       '''simple docstring'''






       with ContextManagers([]      ):
          print("Transformers are awesome!"      )
       # The print statement adds a new line at the end of the output
       self.assertEqual(mock_stdout.getvalue()	,  "Transformers are awesome!\n"      )




    @unittest.mock.patch("sys.stdout"	,  new_callable=io.StringIO      )
    def 					lowerCAmelCase__					(      self	:							List[str]	,  a	:							Optional[int]      ):






       '''simple docstring'''






       with ContextManagers([context_en()]      ):
          print("Transformers are awesome!"      )
       # The output should be wrapped with an English welcome and goodbye
       self.assertEqual(mock_stdout.getvalue()	,  "Welcome!\nTransformers are awesome!\nBye!\n"      )




    @unittest.mock.patch("sys.stdout"	,  new_callable=io.StringIO      )
    def 					lowerCAmelCase__					(      self	:							Tuple	,  a	:							List[Any]      ):






       '''simple docstring'''






       with ContextManagers([context_fr(), context_en()]      ):
          print("Transformers are awesome!"      )
       # The output should be wrapped with an English and French welcome and goodbye
       self.assertEqual(mock_stdout.getvalue()	,  "Bonjour!\nWelcome!\nTransformers are awesome!\nBye!\nAu revoir!\n"      )




    @require_torch
    def 					lowerCAmelCase__					(      self	:							Tuple      ):






       '''simple docstring'''






       self.assertEqual(find_labels(a      )	,  ["labels"]      )
       self.assertEqual(find_labels(a      )	,  ["labels", "next_sentence_label"]      )
       self.assertEqual(find_labels(a      )	,  ["start_positions", "end_positions"]      )


       class 							_UpperCAmelCase    (		snake_case      ):
           pass


       self.assertEqual(find_labels(a      )	,  ["labels"]      )




    @require_tf
    def 					lowerCAmelCase__					(      self	:							int      ):






       '''simple docstring'''






       self.assertEqual(find_labels(a      )	,  ["labels"]      )
       self.assertEqual(find_labels(a      )	,  ["labels", "next_sentence_label"]      )
       self.assertEqual(find_labels(a      )	,  ["start_positions", "end_positions"]      )


       class 							_UpperCAmelCase    (		snake_case      ):
           pass


       self.assertEqual(find_labels(a      )	,  ["labels"]      )





    @require_flax
    def 					lowerCAmelCase__					(      self	:							str      ):






       '''simple docstring'''






       self.assertEqual(find_labels(a      )	,  []      )
       self.assertEqual(find_labels(a      )	,  []      )
       self.assertEqual(find_labels(a      )	,  []      )


       class 							_UpperCAmelCase    (		snake_case      ):
           pass


       self.assertEqual(find_labels(a      )	,  []      )




