- Show `numpy.jax.vectorize` explicitly in the JAX docs, rather than the
original `numpy.vectorize.
- Updated regex for identifying function signatures in NumPy. This now correctly
parses `np.vectorize` and `np.einsum`.
- Removed docs for `jax.experimental.vectorize`. There's still some good
narrative content in the docstring but it should go somewhere else.
* Add jax.numpy.vectorize
This is basically a non-experimental version of the machinery in
`jax.experimental.vectorize`, except:
- It adds the `excluded` argument from NumPy, which works just like
`static_argnums` in `jax.jit`.
- It doesn't include the `axis` argument yet (which NumPy doesn't have).
Eventually we might want want to consolidate the specification of signatures
with signatures used by shape-checking machinery, but it's nice to emulate
NumPy's existing interface, and this is already useful (e.g., for writing
vectorized linear algebra routines).
* Add deprecation warning to jax.experimental.vectorize
* improve implementation
The current index of the API docs page seems to have broken links: when I
click on "Automatic differentiation" for example, I get sent to the "JIT"
section.
This change fixes the links.
Create a new library `jax.ops` for user-facing ops that don't exist in NumPy or SciPy.
Progress on issue #101. Fixes#122.
Reenable some disabled TPU indexing tests that now pass.
