code: def test_optimizer_with_bad_shape_input_passed(self):
      optimizer = algorithms.GradientDescent(
          [
              layers.Input((10, 10, 3)),
              layers.Convolution((3, 3, 7)),
              layers.Reshape(),
              layers.Sigmoid(1),
          ],
          batch_size=None,
          verbose=False,
          loss="mse",
      )
  
      image = np.random.random((10, 10, 3))
      optimizer.train(image, [1], epochs=1)
  
      retrieved_score = optimizer.score(image, [1])
      self.assertLessEqual(0, retrieved_score)
      self.assertGreaterEqual(1, retrieved_score)
  
      prediction = optimizer.predict(image)
      self.assertEqual(prediction.ndim, 2)
  
file_path: neupy/tests/algorithms/gd/test_gd.py
imports: import pickle
  import numpy
  import tensorflow
  from neupy import algorithms, layers
  from neupy.algorithms.gd import objectives
  from neupy.exceptions import InvalidConnection
  from base import BaseTestCase
  from helpers import simple_classification
label_desc: Use image node_id 6 for calling the GradientDescentTestCase obj's underlying member method code with example usage: obj.test_optimizer_with_bad_shape_input_passed() without return types