Do not decompose view ops in CoreML partitioner (pytorch#12972)

We have some evidence that preserving view ops can hurt performance in
CoreML.

In addition, ET converts view ops to copy variants before lowering, but
after checking op support, so we sometimes run into an issue where a
view op is preserved, but its copy variant is unsupported. This can lead
to graph breaks.

Author: metascroy

backends/apple/coreml/partition/coreml_partitioner.py

@@ -26,6 +26,14 @@
 logger.setLevel(logging.INFO)
 
 
+def _is_view_op(op: torch._ops.OpOverload) -> bool:
+    schema = op._schema
+    if len(schema.arguments) == 0:
+        return False
+    alias_info = schema.arguments[0].alias_info
+    return (alias_info is not None) and (not alias_info.is_write)
+
+
 class _OperatorsSupportedForCoreMLBackend(OperatorSupportBase):
     def __init__(
         self,
@@ -119,6 +127,7 @@ class CoreMLPartitioner(Partitioner):
 
     def __init__(
         self,
+        *,
         skip_ops_for_coreml_delegation: Optional[List[str]] = None,
         compile_specs: Optional[List[CompileSpec]] = None,
         take_over_mutable_buffer: Optional[bool] = True,
@@ -209,6 +218,9 @@ def ops_to_not_decompose(
             torch.ops.aten.triu.default,
             # https://github.com/apple/coremltools/blob/release/8.3/coremltools/converters/mil/frontend/torch/ops.py#L6997-L6998
             torch.ops.aten.tril.default,
+            # CoreML's translation of repeat_interleave has poor perf
+            torch.ops.aten.repeat_interleave.self_int,
+            torch.ops.aten.repeat_interleave.self_Tensor,
         ]
         for node in ep.graph.nodes:
             if node.op == "call_function" and isinstance(
@@ -218,6 +230,7 @@ def ops_to_not_decompose(
                     if (
                         op_support.is_node_supported(None, node)
                         and node.target not in do_not_decompose_blocklist
+                        and not _is_view_op(node.target)
                     ):
                         do_not_decompose.append(node.target)
                 except Exception as e: