Don't cluster nodes that have inputs with mismatching deadness

TensorFlow allows nodes to have some live inputs and some dead inputs.  The
executor does not execute these nodes but instead propagates a dead signal to
all their outputs (i.e. these nodes are treated as fully dead).

This is a problem for auto-clustering because it means auto-clustering can kill
nodes that used to be alive.  For instance say before clustering we have a graph
like

digraph {
  Alive0 -> P
  Alive1 -> Q
  Dead -> R
  P -> X
  Q -> X
  Q -> Y
  R -> Y
}

and we cluster P, Q, R, X and Y into a single XLA cluster.

Then after clustering both X and Y are dead because the cluster is a single node
as far as the executor is concerned and said node won't get scheduled if any of
its inputs are dead.

This CL introduces a static analysis pass that our auto-clustering code can use
to ensure nodes that have inputs with mismatching deadness (like "Y" in the
example graph) are not included in XLA clusters.

PiperOrigin-RevId: 205143316