code: def testGradientWithUnknownInputDim(self):
      with self.session():
          x = array_ops.placeholder(dtypes.float32)
          y = array_ops.placeholder(dtypes.float32)
          c = array_ops.concat([x, y], 2)
  
          output_shape = [10, 2, 9]
          grad_inp = np.random.rand(*output_shape).astype("f")
          grad_tensor = constant_op.constant(
              grad_inp.flatten(), shape=output_shape
          )
  
          grad = gradients_impl.gradients([c], [x, y], [grad_tensor])
          concated_grad = array_ops.concat(grad, 2)
          params = {
              x: np.random.rand(10, 2, 3).astype("f"),
              y: np.random.rand(10, 2, 6).astype("f"),
          }
          result = concated_grad.eval(feed_dict=params)
  
          self.assertAllEqual(result, grad_inp)
  
imports: import numpy
  from tensorflow.python.eager import def_function
  from tensorflow.python.framework import constant_op
  from tensorflow.python.framework import dtypes
  from tensorflow.python.framework import errors_impl
  from tensorflow.python.framework import ops
  from tensorflow.python.framework import test_util
  from tensorflow.python.ops import array_ops
  from tensorflow.python.ops import gen_array_ops
  from tensorflow.python.ops import gradient_checker
  from tensorflow.python.ops import gradients_impl
  from tensorflow.python.ops import math_ops
  from tensorflow.python.ops import nn_ops
  from tensorflow.python.ops import variables
  from tensorflow.python.platform import test
label_desc: Use image node_id 19 for calling the ConcatOpTest obj's underlying member method code with example usage: obj.testGradientWithUnknownInputDim() without return types