add not decomposition into vulkan_partition

Differential Revision: D58900868

Author: huiyujie0105

backends/vulkan/partitioner/vulkan_partitioner.py

@@ -7,7 +7,7 @@
 # pyre-strict
 
 import logging
-from typing import Any, Dict, final, List, Mapping, Optional
+from typing import Any, Callable, Dict, final, List, Mapping, Optional, Tuple
 
 import executorch.backends.vulkan.serialization.vulkan_graph_schema as vk_graph_schema
 
@@ -33,6 +33,16 @@
 
 from torch.fx.passes.operator_support import OperatorSupportBase
 
+# pyre-ignore
+ops_not_to_decompose = [
+    torch.ops.aten.upsample_nearest2d.vec,
+]
+
+# pyre-ignore
+edge_ops_non_decomposed = [
+    exir_ops.edge.aten.upsample_nearest2d.vec,
+]
+
 
 class VulkanSupportedOperators(OperatorSupportBase):
     _ops: OpList = enumerate_supported_ops()
@@ -117,6 +127,9 @@ def _is_node_supported(
         if node.target not in VulkanSupportedOperators._ops:
             return False
 
+        if node.op == "call_function" and node.target in edge_ops_non_decomposed:
+            return True
+
         features = VulkanSupportedOperators._ops[node.target]
 
         if self.require_dynamic_shapes and not features.supports_dynamic_shape:
@@ -150,6 +163,11 @@ def __init__(self, compile_options: Optional[Dict[str, Any]] = None) -> None:
         compile_spec = parse_compile_options(self.options)
         self.delegation_spec = DelegationSpec(VulkanBackend.__name__, compile_spec)
 
+    def ops_to_not_decompose(
+        self, ep: ExportedProgram
+    ) -> Tuple[List[torch._ops.OpOverload], Optional[Callable[[torch.fx.Node], bool]]]:
+        return (ops_not_to_decompose, None)
+
     def partition(self, exported_program: ExportedProgram) -> PartitionResult:
         # Run the CapabilityBasedPartitioner to return the largest possible
         # subgraphs containing the nodes with the tags