fix (JAX backend)(manipulation.py): adding a temp fix to workaround t…

…he issue wherein `jnp.broadcast_to` fails when passing an instance of `nnx.Variable`

ivy/functional/backends/jax/experimental/manipulation.py

@@ -340,6 +340,11 @@ def expand(
     for i, dim in enumerate(shape):
         if dim < 0:
             shape[i] = x.shape[i]
+
+    #TODO: remove this once JAX supports passing in nnx.Variables to
+    # jnp.broadcast_to
+    if hasattr(x, '__jax_array__'):
+        x = x.__jax_array__()
     return jnp.broadcast_to(x, tuple(shape))