nit: copy_ops -> get_copy_ops

Signed-off-by: gcunhase <[email protected]>

Author: gcunhase

modelopt/onnx/op_types.py

@@ -96,7 +96,7 @@ def is_fusible_scaling_op(op_type: str):
     ]
 
 
-def copy_ops():
+def get_copy_ops():
     """Returns list of copy operators."""
     return [
         "Flatten",
@@ -120,7 +120,7 @@ def copy_ops():
 
 def is_copy_op(op_type: str):
     """Returns whether the given op is a copy operator or not."""
-    return op_type in copy_ops()
+    return op_type in get_copy_ops()
 
 
 def is_linear_op(op_type: str):

modelopt/onnx/quantization/graph_utils.py

@@ -29,7 +29,7 @@
 from onnxruntime.quantization.calibrate import CalibrationDataReader
 
 from modelopt.onnx.logging_config import logger
-from modelopt.onnx.op_types import copy_ops, is_copy_op, is_linear_op
+from modelopt.onnx.op_types import get_copy_ops, is_copy_op, is_linear_op
 from modelopt.onnx.quantization.ort_utils import create_inference_session
 from modelopt.onnx.utils import (
     find_lowest_common_ancestor,
@@ -203,7 +203,7 @@ def _get_backbone(root: Node):
             ["MaxPool", "Relu", "BatchNormalization", "BiasAdd", conv_type],
         ]
     for idx, path_type in enumerate(fusible_linear_path_types):
-        if has_path_type(node, graph, path_type, is_forward=False, wild_card_types=copy_ops()):
+        if has_path_type(node, graph, path_type, is_forward=False, wild_card_types=get_copy_ops()):
             return _get_backbone(node)
 
     return None