Stricter testing of sharding annotations after scan

For `init` and `final_carry`, the sharding spec should look like
`devices=[4]0,1,2,3`.

For `xs` and `ys`, the sharding spec should look like
`devices=[1,4]0,1,2,3`.

test/scan/test_scan_spmd.py

@@ -39,10 +39,19 @@ def fn(carry, x):
     # Check the input and output sharding. Note that we do this after
     # `torch_xla.sync()` to ensure the output tensors are materialized and
     # have taken on sharding annotations propagated by the compiler.
-    for tensor in [init, xs, final_carry, ys]:
-      self.assertIn('ShardingSpec: {devices=[',
+    N = xr.global_runtime_device_count()
+    for tensor in [init, final_carry]:
+      self.assertIn(f'devices=[{N}]0,',
+                    torch_xla._XLAC._get_xla_sharding_spec(tensor))
+      self.assertIn('OpSharding: {'
+                    f'devices=[{N}]0,',
                     torch_xla._XLAC._get_xla_tensor_debug_info(tensor))
-      self.assertIn('OpSharding: {devices=[',
+    # For xs and ys, they are replicated at the first dim and sharded at the second dim.
+    for tensor in [xs, ys]:
+      self.assertIn(f'devices=[1,{N}]0,',
+                    torch_xla._XLAC._get_xla_sharding_spec(tensor))
+      self.assertIn('OpSharding: {'
+                    f'devices=[1,{N}]0,',
                     torch_xla._XLAC._get_xla_tensor_debug_info(tensor))