Arm backend: Fix FuseConstantOps for Full

Previosuly such nodes where never fused into tensors due to a bug where
input_kind and persistent_buffer couldn't be determined since the fill
operator doesn't have any input nodes to copy the info from. The
if-statement in fuse_nodes() is reversed for linting purposes.

Additionally, since we only consider constant values for the Arm
backend, this will fuse all full ops and thus the op_full node vistitor
can be removed, and a previous xfail is removed.

Change-Id: I46052f6ebd58b02a61447ca5d70846f1d0d63cef

Author: Martin Lindström

backends/arm/_passes/fuse_constant_ops_pass.py

@@ -18,6 +18,7 @@
 from executorch.exir import ExportedProgram
 from executorch.exir.dialects._ops import ops as exir_ops
 from executorch.exir.pass_base import ExportPass, PassResult
+from torch.export.graph_signature import InputKind
 
 logger = logging.getLogger(__name__)
 
@@ -48,16 +49,8 @@ def fuse_nodes(self, node) -> bool:
         the operations already carried out on the data.
         """
 
-        if node.target == exir_ops.edge.aten.full.default:
-            # Create data from args
-            size, fill_value = node.args
-            dtype = node.kwargs["dtype"]
-            data = torch.full(size, float(fill_value), dtype=dtype)
-
-            insert_pos = list(node.graph.nodes)[0]
-        else:
+        if not node.target == exir_ops.edge.aten.full.default:
             # Extract tensors and args from the node
-
             if len(node.all_input_nodes) == 0:
                 raise RuntimeError("No inputs found")
 
@@ -104,9 +97,22 @@ def fuse_nodes(self, node) -> bool:
 
             insert_pos = list(node.all_input_nodes)[0]
 
-        # Make new node the same kind as the first constant input
-        input_kind = get_constant_placeholder_kind(self.exported_program, insert_pos)
-        persistent_buffer = is_persistent_buffer(self.exported_program, insert_pos)
+            # Make new node the same kind as the first constant input
+            input_kind = get_constant_placeholder_kind(
+                self.exported_program, insert_pos
+            )
+            persistent_buffer = is_persistent_buffer(self.exported_program, insert_pos)
+
+        else:
+            # Create data from args
+            size, fill_value = node.args
+            dtype = node.kwargs.get("dtype", torch.float32)
+            data = torch.full(size, float(fill_value), dtype=dtype)
+
+            insert_pos = list(node.graph.nodes)[0]
+
+            input_kind = InputKind.BUFFER
+            persistent_buffer = True
 
         # Create new node
         with node.graph.inserting_before(insert_pos):
@@ -159,6 +165,7 @@ def call(self, graph_module):
                     logger.warning(
                         f"\nFailed to fuse constant op {node.name} due to exception:\n{str(e)}"
                     )
+                    raise e
 
         if modified:
             graph_module.graph.eliminate_dead_code()

backends/arm/operators/__init__.py

@@ -20,7 +20,6 @@
     op_conv2d,
     op_eq,
     op_exp,
-    op_full,
     op_ge,
     op_get_item,
     op_gt,

backends/arm/operators/op_full.py

@@ -175,8 +175,6 @@ def test_full_u85_BI(self, test_tensor: Tuple):
             test_tensor,
         )
 
-    # This fails since full outputs int64 by default if 'fill_value' is integer, which our backend doesn't support.
-    @unittest.expectedFailure
     def test_integer_value(self):
         _input = torch.ones((2, 2))
         integer_fill_value = 1