Better repr of aval when shardings are present

Example: (for array for shape (8, 2) with dtype float32

```
P('x', 'y') -- float32[8@x,2@y]

P('x', None) -- float32[8@x,2]

P(('x', 'y'), None) -- float32[8@xy,2]

P(None, None) -- float32[8, 2]
```

PiperOrigin-RevId: 684996577

jax/_src/array.py

@@ -1030,7 +1030,7 @@ def _get_aval_array(self):
   if config.sharding_in_types.value and isinstance(self.sharding, NamedSharding):
     return self.aval.update(sharding=NamedSharding(
         self.sharding.mesh.abstract_mesh,
-        self.sharding.normalized_spec(self.ndim)))
+        self.sharding._normalized_spec(self.ndim)))
   else:
     return self.aval
 api_util._shaped_abstractify_handlers[ArrayImpl] = _get_aval_array

jax/_src/core.py

@@ -1755,6 +1755,8 @@ def __init__(self, shape, dtype, weak_type=False, sharding=None):
     self.dtype = _dtype_object(dtype)
     self.weak_type = weak_type
     if config.sharding_in_types.value:
+      if sharding is not None:
+        assert len(sharding.spec) == len(self.shape)
       self.sharding = sharding
 
   def update(self, shape=None, dtype=None, weak_type=None, sharding=None):
@@ -1805,12 +1807,14 @@ def join(self, other):
       raise TypeError(self, other)
 
   def str_short(self, short_dtypes=False):
-    dt_str =  dtypes.short_dtype_name(self.dtype) if short_dtypes else self.dtype.name
+    dt_str = (dtypes.short_dtype_name(self.dtype) if short_dtypes else
+              self.dtype.name)
     dt_str = dt_str.replace('void', 'float0')
-    shapestr = ','.join(map(str, self.shape))
     if hasattr(self, 'sharding'):
-      return f'{dt_str}[{shapestr}]({self.sharding})'
+      shapestr = ','.join(_get_shape_sharding_str(self.shape, self.sharding.spec))
+      return f'{dt_str}[{shapestr}]'
     else:
+      shapestr = ','.join(map(str, self.shape))
       return f'{dt_str}[{shapestr}]'
 
   def _len(self, ignored_tracer):
@@ -1820,6 +1824,17 @@ def _len(self, ignored_tracer):
       raise TypeError("len() of unsized object") from err  # same as numpy error
 
 
+def _get_shape_sharding_str(shape, spec):
+  for s1, s2 in zip(shape, spec):
+    if s2 is None:
+      yield f"{s1}"
+    elif isinstance(s2, tuple):
+      ss = ''.join(s for s in s2)
+      yield f"{s1}@{ss}"
+    else:
+      yield f"{s1}@{s2}"
+
+
 def _forward_to_value(self, fun, ignored_tracer, *args):
   return fun(self.val, *args)
 

jax/_src/sharding_impls.py

@@ -307,7 +307,7 @@ def is_fully_replicated(self) -> bool:
   def with_memory_kind(self, kind: str) -> NamedSharding:
     return NamedSharding(self.mesh, self.spec, memory_kind=kind)
 
-  def normalized_spec(self, ndim: int) -> PartitionSpec:
+  def _normalized_spec(self, ndim: int) -> PartitionSpec:
     out = []  # type: ignore
     for p in self._parsed_pspec:
       if p is None:

tests/pjit_test.py

@@ -4739,6 +4739,25 @@ def test_dot_general_batch_error(self):
         ' have the consistent sharding'):
       jnp.einsum('abc,acz->abz', arr1, arr2)
 
+  def test_aval_repr(self):
+    mesh = jtu.create_mesh((2, 2), ('x', 'y'))
+
+    aval = core.ShapedArray((8, 2), np.float32,
+                            sharding=NamedSharding(mesh, P('x', 'y')))
+    self.assertEqual(aval.str_short(), 'float32[8@x,2@y]')
+
+    aval = aval.update(sharding=NamedSharding(mesh, P('x', None)))
+    self.assertEqual(aval.str_short(), 'float32[8@x,2]')
+
+    aval = aval.update(sharding=NamedSharding(mesh, P(None, 'y')))
+    self.assertEqual(aval.str_short(), 'float32[8,2@y]')
+
+    aval = aval.update(sharding=NamedSharding(mesh, P(None, None)))
+    self.assertEqual(aval.str_short(), 'float32[8,2]')
+
+    aval = aval.update(sharding=NamedSharding(mesh, P(('x', 'y'), None)))
+    self.assertEqual(aval.str_short(), 'float32[8@xy,2]')
+
 
 @jtu.pytest_mark_if_available('multiaccelerator')
 class PJitErrorTest(jtu.JaxTestCase):