code: def testAvgPoolGradSamePaddingZeroStrideZeroSize(self):
      output_gradient_vals = np.array([0.39117979], dtype=np.float32)
      output_gradient_vals = output_gradient_vals.reshape([1, 1, 1, 1])
      with self.session() as sess:
          with self.test_scope():
              output_gradients = array_ops.placeholder(
                  dtypes.float32, shape=output_gradient_vals.shape
              )
              t = gen_nn_ops.avg_pool_grad(
                  orig_input_shape=[1, 0, 0, 0],
                  grad=output_gradients,
                  ksize=[1, 0, 0, 0],
                  strides=[1, 0, 0, 0],
                  padding="SAME",
                  data_format="NCHW",
              )
          with self.assertRaisesRegex(
              errors.InvalidArgumentError,
              (
                  "Sliding window ksize field for dimension 1 must be positive but"
                  " is 0"
              ),
          ):
              sess.run(t, {output_gradients: output_gradient_vals})
  
imports: import numpy
  from tensorflow.compiler.tests import xla_test
  from tensorflow.python.framework import dtypes
  from tensorflow.python.framework import errors
  from tensorflow.python.framework import ops
  from tensorflow.python.framework import tensor
  from tensorflow.python.framework import test_util
  from tensorflow.python.ops import array_ops
  from tensorflow.python.ops import gen_nn_ops
  from tensorflow.python.ops import nn_ops
  from tensorflow.python.platform import googletest
label_desc: Use image node_id 6 for calling the PoolGradTest obj's underlying member method code with example usage: obj.testAvgPoolGradSamePaddingZeroStrideZeroSize() without return types