Fix linter errors in Core ML partitioner. (pytorch#1630)

Summary:
Pull Request resolved: pytorch#1630

.

Reviewed By: GregoryComer

Differential Revision: D52860966

fbshipit-source-id: d8d9eb62e5fddf155c7c766b3259e7a9aee8640f

backends/apple/coreml/partition/coreml_partitioner.py

@@ -3,28 +3,31 @@
 # Please refer to the license found in the LICENSE file in the root directory of the source tree.
 
 import logging
-from typing import List
+from typing import List, Optional
+
+import coremltools as ct
 
 import torch
-from torch._export.exported_program import ExportedProgram
-from torch.fx.passes.infra.partitioner import CapabilityBasedPartitioner
-from torch.fx.passes.operator_support import OperatorSupportBase
 
 from executorch.exir.backend.partitioner import (
     DelegationSpec,
     Partitioner,
     PartitionResult,
 )
-from executorch.backends.apple.coreml.compiler.coreml_preprocess import CoreMLBackend
-
-import coremltools as ct
+from torch._export.exported_program import ExportedProgram
+from torch.fx.passes.infra.partitioner import CapabilityBasedPartitioner
+from torch.fx.passes.operator_support import OperatorSupportBase
 
 logger = logging.getLogger(__name__)
 logger.setLevel(logging.WARNING)
 
 
 class OperatorsSupportedForCoreMLBackend(OperatorSupportBase):
-    def __init__(self, skip_ops_for_coreml_delegation: List[str] = []) -> None:
+    def __init__(
+        self, skip_ops_for_coreml_delegation: Optional[List[str]] = None
+    ) -> None:
+        if skip_ops_for_coreml_delegation is None:
+            skip_ops_for_coreml_delegation = []
         super().__init__()
         self.skip_ops_for_coreml_delegation = skip_ops_for_coreml_delegation
 
@@ -51,7 +54,11 @@ def is_node_supported(self, submodules, node: torch.fx.Node) -> bool:
 class CoreMLPartitioner(Partitioner):
     compile_spec = []
 
-    def __init__(self, skip_ops_for_coreml_delegation: List[str] = []) -> None:
+    def __init__(
+        self, skip_ops_for_coreml_delegation: Optional[List[str]] = None
+    ) -> None:
+        if skip_ops_for_coreml_delegation is None:
+            skip_ops_for_coreml_delegation = []
         self.skip_ops_for_coreml_delegation = skip_ops_for_coreml_delegation
         self.delegation_spec = DelegationSpec("CoreMLBackend", self.compile_spec)
 

backends/apple/coreml/test/test_coreml_partitioner.py

@@ -4,13 +4,15 @@
 
 import unittest
 
+import executorch.exir as exir
+
 import torch
 
-import executorch.exir as exir
+from executorch.backends.apple.coreml.partition.coreml_partitioner import (
+    CoreMLPartitioner,
+)
 from executorch.exir.backend.backend_api import to_backend
 
-from executorch.backends.apple.coreml.partition.coreml_partitioner import CoreMLPartitioner
-
 
 class TestCoreMLPartitioner(unittest.TestCase):
     def test_partition_add_mul(self):
@@ -28,12 +30,20 @@ def forward(self, a, x, b):
 
         model = Model()
         inputs = (torch.randn(2, 2), torch.randn(2, 2), torch.randn(2, 2))
-        exported_program = exir.capture(model, inputs, exir.CaptureConfig()).to_edge().exported_program
+        exported_program = (
+            exir.capture(model, inputs, exir.CaptureConfig()).to_edge().exported_program
+        )
 
         assert [
-            node.target.__name__ for node in exported_program.graph.nodes if node.op == "call_function"
+            node.target.__name__
+            for node in exported_program.graph.nodes
+            if node.op == "call_function"
         ] == [
-            "aten.mm.default", "aten.add.Tensor", "aten.sub.Tensor", "aten.mm.default", "aten.add.Tensor"
+            "aten.mm.default",
+            "aten.add.Tensor",
+            "aten.sub.Tensor",
+            "aten.mm.default",
+            "aten.add.Tensor",
         ]
 
         exported_to_coreml = to_backend(
@@ -42,9 +52,16 @@ def forward(self, a, x, b):
         )
 
         assert [
-            node.target.__name__ for node in exported_to_coreml.graph.nodes if node.op == "call_function"
+            node.target.__name__
+            for node in exported_to_coreml.graph.nodes
+            if node.op == "call_function"
         ] == [
-            "aten.mm.default", "executorch_call_delegate", "getitem", "aten.mm.default", "executorch_call_delegate", "getitem"
+            "aten.mm.default",
+            "executorch_call_delegate",
+            "getitem",
+            "aten.mm.default",
+            "executorch_call_delegate",
+            "getitem",
         ]