type: number
                              type: object
                          type: object
                        delay:
                          description: Delay requests before forwarding, emulating
                            various failures such as network issues, overloaded upstream
                            service, etc.
                          oneOf:

                                  type: number
                              type: object
                          type: object
                        delay:
                          description: Delay requests before forwarding, emulating
                            various failures such as network issues, overloaded upstream
                            service, etc.
                          oneOf:

`result[i] = range(starts[i], limits[i], deltas[i])`.

```python
(rt_nested_splits, rt_dense_values) = ragged_range(
      starts=[2, 5, 8], limits=[3, 5, 12], deltas=1)
result = tf.ragged.from_row_splits(rt_dense_values, rt_nested_splits)
print(result)
<tf.RaggedTensor [[2], [], [8, 9, 10, 11]] >
```

The input tensors `starts`, `limits`, and `deltas` may be scalars or vectors.

		}
		if v.ExpectError {
			if len(errs) == 0 {
				t.Errorf("Testcase %s - expected error, got success", k)
			}
			delta := cmp.Diff(errs, v.Errors)
			if delta != "" {
				t.Errorf("Testcase %s - expected errors '%v', got '%v', diff: '%v'", k, v.Errors, errs, delta)
			}
		}
	}
}

func getResourceLimits(cpu, memory string) core.ResourceList {
	res := core.ResourceList{}

## Breaking Changes to the API

*   `AdjustContrast` kernel deprecated, new kernel `AdjustContrastv2` takes and
    outputs float only. `adjust_contrast` now takes all data types.
*   `adjust_brightness`'s `delta` argument is now always assumed to be in
    `[0,1]` (as is the norm for images in floating point formats), independent
    of the data type of the input image.