Fix tests

Author: andrey-churkin

nncf/onnx/graph/nncf_graph_builder.py

@@ -337,7 +337,7 @@ def convert_onnx_dtype_to_nncf_dtype(onnx_dtype: int) -> Dtype:
         return Dtype.FLOAT if onnx_dtype == int(onnx.TensorProto.FLOAT) else Dtype.INTEGER
 
     @staticmethod
-    def create_nncf_graph(onnx_model: onnx.ModelProto) -> NNCFGraph:
+    def create_nncf_graph(onnx_model: onnx.ModelProto, infer_shapes: bool = True) -> NNCFGraph:
         """
         Creates NNCFGraph from 'onnx_model'.
         Initially, ONNXGraph is built. All nodes from onnx_model which have valid metatype are added to NNCFGraph.
@@ -347,6 +347,8 @@ def create_nncf_graph(onnx_model: onnx.ModelProto) -> NNCFGraph:
         :return: NNCFGraph.
         """
         onnx_model = GraphConverter._replace_empty_node_name(onnx_model)
+        if infer_shapes:
+            onnx_model = onnx.shape_inference.infer_shapes(onnx_model)
         edge_info_mapping = get_edge_info_mapping(onnx_model)
         children_node_mapping = get_children_node_mapping(onnx_model)
         parents_node_mapping = get_parents_node_mapping(onnx_model)

nncf/onnx/quantization/quantize_model.py

@@ -126,7 +126,7 @@ def quantize_impl(
     )
 
     model = quantize_pre_process(model)
-    graph = GraphConverter.create_nncf_graph(model)
+    graph = GraphConverter.create_nncf_graph(model, infer_shapes=False)
     warning_model_no_batchwise_support(graph, advanced_parameters, model_type, OPERATIONS_OUTPUT_HAS_NO_BATCH_AXIS)
     quantized_model = quantization_algorithm.apply(model, graph, dataset=calibration_dataset)