key: "_output_shapes"
            value {
              list {
              }
            }
          }
        }
        ret {
          key: "identity_1"
          value: "Identity_1:output:0"
        }
        attr {
          key: "_construction_context"
          value {
            s: "kEagerRuntime"
          }
        }
        attr {

such that dx = g(dy). In Python,

```python
with tf.get_default_graph().gradient_override_map(
    {'IdentityN': 'OverrideGradientWithG'}):
  y, _ = identity_n([f(x), x])

@tf.RegisterGradient('OverrideGradientWithG')
def ApplyG(op, dy, _):
  return [None, g(dy)]  # Do not backprop to f(x).
```
  }];

  let arguments = (ins