Added some mo optimizations to improve performance (#1674)

Signed-off-by: suryasidd <surya.siddharth.pemmaraju@intel.com>

onnxruntime/core/providers/openvino/openvino_mo/openvino_mo.py

@@ -251,6 +251,21 @@ def driver_R5(onnx_modelproto_bytes, precision: str, output_model_name: str, out
  convert_batch_norm(graph)
  graph_clean_up(graph)
 
+ convert_scale_shift_to_mul_add(graph)
+ graph_clean_up(graph)
+
+ fuse_mul_add_sequence(graph)
+ graph_clean_up(graph)
+
+ fuse_linear_ops(graph)
+ graph_clean_up(graph)
+
+ grouped_convolutions_fusing(graph)
+ graph_clean_up(graph)
+
+ fuse_linear_ops(graph)
+ graph_clean_up(graph)
+
  convert_muladd_to_scaleshift_or_power(graph)
  graph_clean_up(graph)
 
@@ -308,9 +323,7 @@ def driver_R1(onnx_modelproto_bytes, precision: str, output_model_name: str, out
  input=None, input_model=None, input_shape=None, keep_shape_ops=False, log_level='ERROR', mean_scale_values={}, mean_values=(), model_name=None, move_to_preprocess=False, output=None, output_dir='.', placeholder_shapes=None, reverse_input_channels=False, scale=None, scale_values=(), silent=False, version=False)
  graph.graph['fw'] = 'onnx'
  graph.graph['feature_dim'] = 1 if graph.graph['layout'] == 'NCHW' else 3
- graph.graph['ir_version'] = 4
- extract_node_attrs(graph, lambda node: (
- True, common_onnx_fields(node)))
+ graph.graph['ir_version'] = 5
  except Exception as e:
  raise Error(
  'Cannot pre-process ONNX graph after reading from model file "{}". '
@@ -327,8 +340,6 @@ def driver_R1(onnx_modelproto_bytes, precision: str, output_model_name: str, out
  # --------------------------------- LOAD END ------------------------------------------------------
  class_registration.apply_replacements(
  graph, class_registration.ClassType.FRONT_REPLACER)
- partial_infer(graph)
- graph.check_empty_graph('partial_infer')
  class_registration.apply_replacements(
  graph, class_registration.ClassType.MIDDLE_REPLACER)
 
@@ -339,6 +350,21 @@ def driver_R1(onnx_modelproto_bytes, precision: str, output_model_name: str, out
  convert_batch_norm(graph)
  graph_clean_up_onnx(graph)
 
+ convert_scale_shift_to_mul_add(graph)
+ graph_clean_up_onnx(graph)
+
+ fuse_mul_add_sequence(graph)
+ graph_clean_up_onnx(graph)
+
+ fuse_linear_ops(graph)
+ graph_clean_up_onnx(graph)
+
+ grouped_convolutions_fusing(graph)
+ graph_clean_up_onnx(graph)
+
+ fuse_linear_ops(graph)
+ graph_clean_up_onnx(graph)
+
  convert_muladd_to_scaleshift_or_power(graph)
  graph_clean_up_onnx(graph)