[JAX] Update JAX users in preparation for a change that makes iterati…

…on over a JAX array return JAX arrays, instead of NumPy arrays.

See jax-ml/jax#8043 for context as to why we are making this change.

The upshot for most users is that the values returned by iteration over a JAX array are now themselves JAX arrays, with the semantics of JAX arrays, which sometimes differ from the semantics of NumPy scalars and arrays. In particular:

* Unlike NumPy scalars 0-dimensional JAX arrays are not hashable. This change updates users to call `.tolist()` or `np.asarray(...)` when the output of iterating over a JAX array is hashed, used as a dictionary key, or passed to `set(...)`. In some instances, we can just call `numpy` functions instead of `jax.numpy` functions to build the array in the first place.
* This change confuses Pandas and PIL when a JAX array is converted to a Pandas dataframe or a PIL image. For now, cast JAX arrays to a NumPy array first before passing them into those libraries.
* We now need to use `numpy.testing.assert_array_equal` instead of `numpy.testing.assert_equal` to compare JAX arrays.

PiperOrigin-RevId: 399922724

examples/seq2seq/train.py

@@ -98,7 +98,7 @@ def encode(self, inputs):
   def decode(self, inputs):
     """Decode from list of integers to string."""
     chars = []
-    for elem in inputs:
+    for elem in inputs.tolist():
       if elem == self.eos_id:
         break
       chars.append(self._indices_char[elem])