class_docstr: To run: "python -m saliency.core.xrai_test" from the top-level directory.
class_docstr_tok: ["To","run",":","``","python","-m","saliency.core.xrai_test","''","from","the","top-level","directory","."]
code: def testBaseAttributionMismatchedShape(self):
      # Create base_attribution that shape doesn't match the input.
      base_attribution = np.random.rand(IMAGE_SIZE, IMAGE_SIZE + 1, 3)
  
      # Verify that the exception was raised.
      with self.assertRaisesRegex(
          ValueError, "The base attribution shape should"
      ):
          # Calling GetMask(...) should result in exception.
          self.xrai.GetMask(
              x_value=self.input_image,
              call_model_function=self.call_model_function,
              base_attribution=base_attribution,
          )
  
imports: import unittest
  import unittest.mock
  import numpy
  import skimage.draw
  from .None import xrai
  from .xrai import XRAI
  from .xrai import XRAIParameters
label_desc: Use image node_id 11 for calling the XraiTest obj's underlying member method code with example usage: obj.testBaseAttributionMismatchedShape() without return types