tfdbg core: add configurable attributes to debug ops, DebugNumericSummary

Added three attributes to the debug op "DebugNumericSummary" used in tfdbg-based TensorBoard health pills:
1) lower_bound (type: float)
2) upper_bound (type: float)
3) mute_if_healthy (type: bool)

lower_bound and upper_bound make it possible to customize thresholds beyond which tensor elements are counted as -inf or inf. mute_if_healthy makes it possible to mute a DebugNumericSummary op unless there are nan, -inf or inf elements in the watched tensor, which is useful for reducing the amount of health pill data.

Changes are made in the C++ DebugNodeInserter class, so that these attributes can be directly set from Python methods such as tf_debug.watch_graph() using the following syntax in the debug_ops argument:
debug_ops=["DebugNumericSummary(attribute_name=attribute_value)"]

e.g.,
debug_ops=["DebugNumericSummary(lower_bound=-100.0; mute_if_healthy=true)"]

Currently, string, float, int, and bool attribute value types are supported.
Change: 150665493