fix import bug

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

Author: yuwenzho

neural_compressor/adaptor/ox_utils/util.py

@@ -29,7 +29,6 @@
 numpy_helper = LazyImport("onnx.numpy_helper")
 onnx_proto = LazyImport("onnx.onnx_pb")
 torch = LazyImport("torch")
-onnxruntime = LazyImport("onnxruntime")
 symbolic_shape_infer = LazyImport("onnxruntime.tools.symbolic_shape_infer")
 onnx = LazyImport("onnx")
 
@@ -599,40 +598,36 @@ def to_numpy(data):
     else:
         return data
 
+def infer_shapes(in_mp, int_max=2**31 - 1, auto_merge=False, guess_output_rank=False, verbose=0, base_dir=""):
+    """Symbolic shape inference."""
+
+    class SymbolicShapeInference(symbolic_shape_infer.SymbolicShapeInference):
+        def __init__(self, int_max, auto_merge, guess_output_rank, verbose, prefix="", base_dir=""):
+            super().__init__(int_max, auto_merge, guess_output_rank, verbose, prefix)
+            self.base_dir = base_dir
+
+        def _get_value(self, node, idx):
+            name = node.input[idx]
+            assert name in self.sympy_data_ or name in self.initializers_
+            return (
+                self.sympy_data_[name]
+                if name in self.sympy_data_
+                else numpy_helper.to_array(self.initializers_[name], base_dir=self.base_dir)
+            )
 
-class SymbolicShapeInference(symbolic_shape_infer.SymbolicShapeInference):
-    """Shape inference for ONNX model."""
-
-    def __init__(self, int_max, auto_merge, guess_output_rank, verbose, prefix="", base_dir=""):
-        """Initialize Shape inference class."""
-        super().__init__(int_max, auto_merge, guess_output_rank, verbose, prefix)
-        self.base_dir = base_dir
-
-    def _get_value(self, node, idx):
-        name = node.input[idx]
-        assert name in self.sympy_data_ or name in self.initializers_
-        return (
-            self.sympy_data_[name]
-            if name in self.sympy_data_
-            else numpy_helper.to_array(self.initializers_[name], base_dir=self.base_dir)
-        )
-
-    @staticmethod
-    def infer_shapes(in_mp, int_max=2**31 - 1, auto_merge=False, guess_output_rank=False, verbose=0, base_dir=""):
-        """Symbolic shape inference."""
-        onnx_opset = symbolic_shape_infer.get_opset(in_mp)
-        if (not onnx_opset) or onnx_opset < 7:
-            logger.warning("Only support models of onnx opset 7 and above.")
-            return None
-        symbolic_shape_inference = SymbolicShapeInference(
-            int_max, auto_merge, guess_output_rank, verbose, base_dir=base_dir
-        )
-        all_shapes_inferred = False
-        symbolic_shape_inference._preprocess(in_mp)
-        while symbolic_shape_inference.run_:
-            all_shapes_inferred = symbolic_shape_inference._infer_impl()
-        symbolic_shape_inference._update_output_from_vi()
-        if not all_shapes_inferred:
-            onnx.save_model(symbolic_shape_inference.out_mp_, "sym_shape_infer_temp.onnx", save_as_external_data=True)
-            raise Exception("Incomplete symbolic shape inference")
-        return symbolic_shape_inference.out_mp_
+    onnx_opset = symbolic_shape_infer.get_opset(in_mp)
+    if (not onnx_opset) or onnx_opset < 7:
+        logger.warning("Only support models of onnx opset 7 and above.")
+        return None
+    symbolic_shape_inference = SymbolicShapeInference(
+        int_max, auto_merge, guess_output_rank, verbose, base_dir=base_dir
+    )
+    all_shapes_inferred = False
+    symbolic_shape_inference._preprocess(in_mp)
+    while symbolic_shape_inference.run_:
+        all_shapes_inferred = symbolic_shape_inference._infer_impl()
+    symbolic_shape_inference._update_output_from_vi()
+    if not all_shapes_inferred:
+        onnx.save_model(symbolic_shape_inference.out_mp_, "sym_shape_infer_temp.onnx", save_as_external_data=True)
+        raise Exception("Incomplete symbolic shape inference")
+    return symbolic_shape_inference.out_mp_

neural_compressor/model/onnx_model.py

@@ -1045,9 +1045,9 @@ def split_model_with_node(
         if shape_infer:
             try:
                 # need ort.GraphOptimizationLevel <= ORT_ENABLE_BASIC
-                from neural_compressor.adaptor.ox_utils.util import SymbolicShapeInference
+                from neural_compressor.adaptor.ox_utils.util import infer_shapes
 
-                self._model = SymbolicShapeInference.infer_shapes(
+                self._model = infer_shapes(
                     self._model, auto_merge=True, base_dir=os.path.dirname(self._model_path)
                 )
             except Exception as e:  # pragma: no cover