





"""simple docstring"""






import importlib
import os
import sys


# This is required to make the module import works (when the python process is running from the root of the repo)
sys.path.append('''.''')

def       __lowerCamelCase    (       SCREAMING_SNAKE_CASE							)		->       Any:






       """simple docstring"""




       _UpperCAmelCase     =     test_file.split(os.path.sep							)
       if components[0:2] != ["tests", "models"]:
              raise ValueError(
                  '`test_file` should start with `tests/models/` (with `/` being the OS specific path separator). Got '
                  F"""{test_file} instead."""							)
       _UpperCAmelCase     =     components[-1]
       if not test_fn.endswith('py'							):
              raise ValueError(F"""`test_file` should be a python file. Got {test_fn} instead."""							)
       if not test_fn.startswith('test_modeling_'							):
              raise ValueError(
                  F"""`test_file` should point to a file name of the form `test_modeling_*.py`. Got {test_fn} instead."""							)

       _UpperCAmelCase     =     components[:-1] + [test_fn.replace('.py',''							)]
       _UpperCAmelCase     =     '.'.join(_SCREAMING_SNAKE_CASE							)

       return test_module_path

def       __lowerCamelCase    (       SCREAMING_SNAKE_CASE							)		->       Any:






       """simple docstring"""




       _UpperCAmelCase     =     get_module_path(_SCREAMING_SNAKE_CASE							)
       _UpperCAmelCase     =     importlib.import_module(_SCREAMING_SNAKE_CASE							)

       return test_module

def       __lowerCamelCase    (       SCREAMING_SNAKE_CASE							)		->       List[str]:






       """simple docstring"""




       _UpperCAmelCase     =     []
       _UpperCAmelCase     =     get_test_module(_SCREAMING_SNAKE_CASE							)
       for attr in dir(_SCREAMING_SNAKE_CASE							):
              if attr.endswith('ModelTester'							):
                     tester_classes.append(getattr(_SCREAMING_SNAKE_CASE,_SCREAMING_SNAKE_CASE							)							)

    # sort with class names
       return sorted(_SCREAMING_SNAKE_CASE,key=lambda SCREAMING_SNAKE_CASE							: x.__name__							)

def       __lowerCamelCase    (       SCREAMING_SNAKE_CASE							)		->       Optional[Any]:






       """simple docstring"""




       _UpperCAmelCase     =     []
       _UpperCAmelCase     =     get_test_module(_SCREAMING_SNAKE_CASE							)
       for attr in dir(_SCREAMING_SNAKE_CASE							):
              _UpperCAmelCase     =     getattr(_SCREAMING_SNAKE_CASE,_SCREAMING_SNAKE_CASE							)
              # (TF/Flax)ModelTesterMixin is also an attribute in specific model test module. Let's exclude them by checking
              # `all_model_classes` is not empty (which also excludes other special classes).
              _UpperCAmelCase     =     getattr(_SCREAMING_SNAKE_CASE,'all_model_classes',[]							)
              if len(_SCREAMING_SNAKE_CASE							) > 0:
                     test_classes.append(_SCREAMING_SNAKE_CASE							)

    # sort with class names
       return sorted(_SCREAMING_SNAKE_CASE,key=lambda SCREAMING_SNAKE_CASE							: x.__name__							)

def       __lowerCamelCase    (       SCREAMING_SNAKE_CASE							)		->       Any:






       """simple docstring"""




       _UpperCAmelCase     =     get_test_classes(_SCREAMING_SNAKE_CASE							)
       _UpperCAmelCase     =     set()
       for test_class in test_classes:
              model_classes.update(test_class.all_model_classes							)

       # sort with class names
       return sorted(_SCREAMING_SNAKE_CASE,key=lambda SCREAMING_SNAKE_CASE							: x.__name__							)

def       __lowerCamelCase    (       SCREAMING_SNAKE_CASE							)		->       Any:






       """simple docstring"""




       _UpperCAmelCase     =     test_class()
       if hasattr(_SCREAMING_SNAKE_CASE,'setUp'							):
              test.setUp()

       _UpperCAmelCase     =     None
       if hasattr(_SCREAMING_SNAKE_CASE,'model_tester'							):
              # `(TF/Flax)ModelTesterMixin` has this attribute default to `None`. Let's skip this case.
              if test.model_tester is not None:
                     _UpperCAmelCase     =     test.model_tester.__class__

       return model_tester

def       __lowerCamelCase    (       SCREAMING_SNAKE_CASE,SCREAMING_SNAKE_CASE							)		->       Tuple:






       """simple docstring"""




       _UpperCAmelCase     =     get_test_classes(_SCREAMING_SNAKE_CASE							)

       _UpperCAmelCase     =     []
       for test_class in test_classes:
              if model_class in test_class.all_model_classes:
                     target_test_classes.append(_SCREAMING_SNAKE_CASE							)

    # sort with class names
       return sorted(_SCREAMING_SNAKE_CASE,key=lambda SCREAMING_SNAKE_CASE							: x.__name__							)

def       __lowerCamelCase    (       SCREAMING_SNAKE_CASE,SCREAMING_SNAKE_CASE							)		->       int:






       """simple docstring"""




       _UpperCAmelCase     =     get_test_classes_for_model(_SCREAMING_SNAKE_CASE,_SCREAMING_SNAKE_CASE							)

       _UpperCAmelCase     =     []
       for test_class in test_classes:
              _UpperCAmelCase     =     get_model_tester_from_test_class(_SCREAMING_SNAKE_CASE							)
              if tester_class is not None:
                     tester_classes.append(_SCREAMING_SNAKE_CASE							)

    # sort with class names
       return sorted(_SCREAMING_SNAKE_CASE,key=lambda SCREAMING_SNAKE_CASE							: x.__name__							)

def       __lowerCamelCase    (       SCREAMING_SNAKE_CASE							)		->       Dict:






       """simple docstring"""




       _UpperCAmelCase     =     get_test_classes(_SCREAMING_SNAKE_CASE							)
       _UpperCAmelCase     =     {test_class: get_model_tester_from_test_class(_SCREAMING_SNAKE_CASE							) for test_class in test_classes}
       return test_tester_mapping

def       __lowerCamelCase    (       SCREAMING_SNAKE_CASE							)		->       List[Any]:






       """simple docstring"""




       _UpperCAmelCase     =     get_model_classes(_SCREAMING_SNAKE_CASE							)
       _UpperCAmelCase     =     {
           model_class: get_test_classes_for_model(_SCREAMING_SNAKE_CASE,_SCREAMING_SNAKE_CASE							) for model_class in model_classes
       }
       return model_test_mapping

def       __lowerCamelCase    (       SCREAMING_SNAKE_CASE							)		->       Union[str, Any]:






       """simple docstring"""




       _UpperCAmelCase     =     get_model_classes(_SCREAMING_SNAKE_CASE							)
       _UpperCAmelCase     =     {
           model_class: get_tester_classes_for_model(_SCREAMING_SNAKE_CASE,_SCREAMING_SNAKE_CASE							) for model_class in model_classes
       }
       return model_to_tester_mapping


def       __lowerCamelCase    (       SCREAMING_SNAKE_CASE							)		->       Any:






       """simple docstring"""




       if isinstance(_SCREAMING_SNAKE_CASE,_SCREAMING_SNAKE_CASE							):
              return o
       elif isinstance(_SCREAMING_SNAKE_CASE,_SCREAMING_SNAKE_CASE							):
              return o.__name__
       elif isinstance(_SCREAMING_SNAKE_CASE,(list, tuple)							):
              return [to_json(_SCREAMING_SNAKE_CASE							) for x in o]
       elif isinstance(_SCREAMING_SNAKE_CASE,_SCREAMING_SNAKE_CASE							):
              return {to_json(_SCREAMING_SNAKE_CASE							): to_json(_SCREAMING_SNAKE_CASE							) for k, v in o.items()}
       else:
              return o













"""simple docstring"""






# Copyright 2023 The HuggingFace Inc. team. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
#     http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
import numpy as np
import torch

from ..models.clipseg import CLIPSegForImageSegmentation
from ..utils import is_vision_available, requires_backends
from .base import PipelineTool


if is_vision_available():
    from PIL import Image



class 	lowerCAmelCase					(      snake_case							):
       lowerCAmelCase__						 =  (
           """This is a tool that creates a segmentation mask of an image according to a label. It cannot create an image."""
           """It takes two arguments named `image` which should be the original image, and `label` which should be a text """
           """describing the elements what should be identified in the segmentation mask. The tool returns the mask."""
       )
       lowerCAmelCase__						 =  """CIDAS/clipseg-rd64-refined"""
       lowerCAmelCase__						 =  """image_segmenter"""
       lowerCAmelCase__						 =  CLIPSegForImageSegmentation

       lowerCAmelCase__						 =  ["""image""", """text"""]
       lowerCAmelCase__						 =  ["""image"""]






       def __init__(   self    ,  *a__    ,  **a__     ):
              requires_backends(self    ,  ['vision']     )
              super().__init__(*a__    ,  **a__     )






       def 							__A (   self    ,  a__    ,  a__     ):
              return self.pre_processor(text=[label]    ,  images=[image]    ,  padding=a__    ,  return_tensors='pt'     )






       def 							__A (   self    ,  a__     ):
              with torch.no_grad():
                     _UpperCAmelCase     =     self.model(**a__     ).logits
              return logits






       def 							__A (   self    ,  a__     ):
              _UpperCAmelCase     =     outputs.cpu().detach().numpy()
              _UpperCAmelCase     =     0
              _UpperCAmelCase     =     1
              return Image.fromarray((array * 2_55).astype(np.uinta     )     )






