```python
tf.cumprod([a, b, c], exclusive=True)  # => [1, a, a * b]
```

By setting the `reverse` kwarg to `True`, the cumprod is performed in the
opposite direction:

```python
tf.cumprod([a, b, c], reverse=True)  # => [a * b * c, b * c, c]
```

This is more efficient than using separate `tf.reverse` ops.

The `reverse` and `exclusive` kwargs can also be combined:

```python

`tf.divide()` is now the recommended division function. `tf.div()` will remain,
but its semantics do not respond to Python 3 or `from future` mechanisms. *
tf.reverse() now takes indices of axes to be reversed. E.g. `tf.reverse(a,
[True, False, True])` must now be written as `tf.reverse(a, [0, 2])`.
`tf.reverse_v2()` will remain until 1.0 final. * `tf.mul`, `tf.sub` and `tf.neg`

			if diff := cmp.Diff(tt.wantFieldErrors, errs); diff != "" {
				t.Errorf("unexpected field errors (-want, +got):\n%s", diff)
			}
		})
	}
}

// collectResourcePaths traverses the object, computing all the struct paths.
func collectResourcePaths(t *testing.T, skipRecurseList sets.String, tp reflect.Type, path *field.Path) sets.String {