implement lazy sublanguage
Before this commit, this computation would avoid materializing the iota
array at trace time:
@jit
def f(x):
m, n = x.shape
return x + np.arange(n)
But this one would materialize the iota array at trace time and stage it
into the computation as a potentially large array constant:
@jit
def f(x):
m, n = x.shape
return x + np.arange(m)[:, None]
The difference is that previously operations like broadcasts,
transposes, and reshapes that add singleton dimensions (as above) would
force otherwise lazy values to be materialized, while after this commit
broadcasts, transposes, and reshapes are all lazy operations that only
update metadata on their input rather than compiling and executing XLA
computations and producing new buffers.
Also, np.eye and np.tri become lazy (in addition to np.zeros, np.ones, np.full).
This commit replaces the ad-hoc "lazy device constant" system, which was
used to get the simpler behavior in the first example above.
Incidentally fixes #1431
See https://github.com/google/jax/pull/1668 for more.
