code: def testSimpleOneDimensional(self):
      # Test various datatypes in the simple case to ensure that the op was
      # registered under those types.
      dtypes_to_test = [
          dtypes.float32,
          dtypes.float16,
          dtypes.bfloat16,
          dtypes.qint8,
          dtypes.quint8,
          dtypes.qint32,
      ]
      for dtype in dtypes_to_test:
          indices = [
              constant_op.constant([0, 4, 7]),
              constant_op.constant([1, 6, 2, 3, 5]),
          ]
          data = [
              math_ops.cast(
                  constant_op.constant([0, 40, 70]), dtype=dtype
              ),
              math_ops.cast(
                  constant_op.constant([10, 60, 20, 30, 50]),
                  dtype=dtype,
              ),
          ]
          stitched_t = self.stitch_op(indices, data)
          stitched_val = self.evaluate(stitched_t)
          self.assertAllEqual(
              [0, 10, 20, 30, 40, 50, 60, 70], stitched_val
          )
          # Dimension 0 is max(flatten(indices))+1.
          self.assertEqual([8], stitched_t.get_shape().as_list())
  
imports: import numpy
  from tensorflow.python.framework import constant_op
  from tensorflow.python.framework import dtypes
  from tensorflow.python.framework import errors
  from tensorflow.python.framework import test_util
  from tensorflow.python.ops import array_ops
  from tensorflow.python.ops import data_flow_ops
  from tensorflow.python.ops import math_ops
  from tensorflow.python.ops import gradients_impl
  import tensorflow.python.ops.data_flow_grad
  from tensorflow.python.platform import test
label_desc: Use image node_id 4 for calling the DynamicStitchTestBase obj's underlying member method code with example usage: obj.testSimpleOneDimensional() without return types