openvinotoolkit · ilya-lavrenov · Jun 25, 2024 · Jun 25, 2024
@@ -820,6 +820,9 @@ def _convert(cli_parser: argparse.ArgumentParser, framework, args, python_api_us
     if 'help' in args and args['help']:
         show_mo_convert_help()
         return None, None
+    ovc_message = get_ovc_message()
+    if ovc_message is not None:
+        print(ovc_message)
     simplified_mo_version = VersionChecker().get_mo_simplified_version()
     telemetry = init_mo_telemetry()
     telemetry.start_session('mo')
@@ -908,14 +911,11 @@ def _convert(cli_parser: argparse.ArgumentParser, framework, args, python_api_us
 
             ov_update_message = get_ov_update_message()
             ov_api20_message = get_ov_api20_message()
-            ovc_message = get_ovc_message()
             _, is_caffe, is_mxnet, is_kaldi, _ = deduce_legacy_frontend_by_namespace(argv)
             if ov_update_message is not None:
                 print(ov_update_message)
             if ov_api20_message is not None and ov_model is not None:
                 print(ov_api20_message)
-            if ovc_message is not None and not is_caffe and not is_mxnet and not is_kaldi:
-                print(ovc_message)
             is_fallback = getattr(argv, 'is_fallback', False)
             if not argv.use_legacy_frontend and framework_is_tf(args, argv) and not is_fallback:
                 # now TF FE is default frontend for TensorFlow models conversion

@@ -94,9 +94,9 @@ def extract(cls, node):
             'visualize_threshold': visualize_threshold,
             'save_file': param.save_file,
             # nms_param
-            'nms_threshold': nms_threshold,
-            'top_k': top_k,
-            'eta': eta,
+            'nms_threshold': nms_threshold,  # pylint: disable=possibly-used-before-assignment
+            'top_k': top_k,  # pylint: disable=possibly-used-before-assignment
+            'eta': eta,  # pylint: disable=possibly-used-before-assignment
             # save_output_param
             'output_directory': param.save_output_param.output_directory,
             'output_name_prefix': param.save_output_param.output_name_prefix,
@@ -111,7 +111,7 @@ def extract(cls, node):
             'width': param.save_output_param.resize_param.width,
             'height_scale': param.save_output_param.resize_param.height_scale,
             'width_scale': param.save_output_param.resize_param.width_scale,
-            'pad_mode': pad_mode,
+            'pad_mode': pad_mode,  # pylint: disable=possibly-used-before-assignment
             'pad_value': ','.join(str(x) for x in param.save_output_param.resize_param.pad_value),
             'interp_mode': interp_mode,
         }

@@ -69,7 +69,7 @@ def extract(cls, node: Node) -> bool:
             'kernel_spatial_idx': [2, 3],
             'group': 1,
             'reshape_kernel': True,
-            'appended_conv': appended_conv
+            'appended_conv': appended_conv  # pylint: disable=possibly-used-before-assignment
         }
 
         mapping_rule.update(layout_attrs())

@@ -71,7 +71,7 @@ def replace_op(self, graph: Graph, node: Node):
         if node['use_dropout']:
             mul_dropout_i = Mul(graph, {'name': split_node.soft_get('name', split_node.id) + '/mul_i'}).create_node()
             mul_dropout_i.in_port(0).connect(i_sigmoid.out_port(0))
-            mul_dropout_i.in_port(1).connect(i_drop_scale)
+            mul_dropout_i.in_port(1).connect(i_drop_scale)  # pylint: disable=possibly-used-before-assignment
             i_sigmoid = mul_dropout_i
 
         # f_t = Sigmoid(f_part + w_fc*ct_1)
@@ -91,7 +91,7 @@ def replace_op(self, graph: Graph, node: Node):
         if node['use_dropout']:
             mul_dropout_f = Mul(graph, {'name': split_node.soft_get('name', split_node.id) + '/mul_f'}).create_node()
             mul_dropout_f.in_port(0).connect(f_sigmoid.out_port(0))
-            mul_dropout_f.in_port(1).connect(f_drop_scale)
+            mul_dropout_f.in_port(1).connect(f_drop_scale)  # pylint: disable=possibly-used-before-assignment
             f_sigmoid = mul_dropout_f
 
         # c_t = f_t*ct_1 + i_t * tanh(c_part)
@@ -127,7 +127,7 @@ def replace_op(self, graph: Graph, node: Node):
         if node['use_dropout']:
             mul_dropout_o = Mul(graph, {'name': split_node.soft_get('name', split_node.id) + '/mul_o'}).create_node()
             mul_dropout_o.in_port(0).connect(o_sigmoid.out_port(0))
-            mul_dropout_o.in_port(1).connect(o_drop_scale)
+            mul_dropout_o.in_port(1).connect(o_drop_scale)  # pylint: disable=possibly-used-before-assignment
             o_sigmoid = mul_dropout_o
 
         # m_t = o_t * Tanh(c_t)

@@ -106,7 +106,7 @@ def split_multilayer_cell(self, graph: Graph, match: dict):
             ).create_node_with_data()
 
             if have_hidden:
-                layer_hidden_state = hidden_state_value[l * direction: l * direction + direction]
+                layer_hidden_state = hidden_state_value[l * direction: l * direction + direction]  # pylint: disable=possibly-used-before-assignment
                 hidden_state_value_node = Const(
                     rnn_layer.graph,
                     dict(name=name + '/LayerSplittedHiddenState/{}/'.format(l), value=layer_hidden_state)
@@ -115,7 +115,7 @@ def split_multilayer_cell(self, graph: Graph, match: dict):
                 hidden_state_value_node = None
 
             if have_cell:
-                layer_cell_state = cell_state_value[l * direction: l * direction + direction]
+                layer_cell_state = cell_state_value[l * direction: l * direction + direction]  # pylint: disable=possibly-used-before-assignment
                 cell_state_value_node = Const(
                     rnn_layer.graph,
                     dict(name=name + '/LayerSplittedCellState/{}/'.format(l), value=layer_cell_state)

@@ -154,7 +154,7 @@ def normalize_strided_slice(graph: Graph, node: Node):
         if num_insertions > 0:
             # insert blank values for ellipsis unrolling and extending
             for mask_name in StridedSlice.get_mask_names():
-                node[mask_name] = np.insert(node[mask_name], insertion_start_idx, [0] * num_insertions).astype(int)
+                node[mask_name] = np.insert(node[mask_name], insertion_start_idx, [0] * num_insertions).astype(int)  # pylint: disable=possibly-used-before-assignment
 
     @staticmethod
     def unroll_ellipsis_for_inputs(graph: Graph, node: Node, ellipsis_start: int, num_insertions: int):

@@ -74,7 +74,7 @@ def infer(node: Node):
                     hot_idx = *idx, indices[idx]
 
                 if -depth <= indices[idx] < depth:
-                    onehot_value[hot_idx] = on_value
+                    onehot_value[hot_idx] = on_value  # pylint: disable=possibly-used-before-assignment
 
             node.out_port(0).data.set_value(onehot_value)
 

@@ -51,8 +51,9 @@ def get_try_legacy_fe_message():
 
 def get_ovc_message():
     link = "https://docs.openvino.ai/2023.2/openvino_docs_OV_Converter_UG_prepare_model_convert_model_MO_OVC_transition.html"
-    message = '[ INFO ] MO command line tool is considered as the legacy conversion API as of OpenVINO 2023.2 release. ' \
-              'Please use OpenVINO Model Converter (OVC). ' \
+    message = '[ INFO ] MO command line tool is considered as the legacy conversion API as of OpenVINO 2023.2 release.\n' \
+              'In 2025.0 MO command line tool and openvino.tools.mo.convert_model() will be removed. ' \
+              'Please use OpenVINO Model Converter (OVC) or openvino.convert_model(). ' \
               'OVC represents a lightweight alternative of MO and provides simplified model conversion API. \n' \
               'Find more information about transition from MO to OVC at {}'.format(link)
 

@@ -14,7 +14,7 @@
 if importlib.util.find_spec('absl') is not None:
     import absl.logging
 
-    log.root.removeHandler(absl.logging._absl_handler)
+    log.root.removeHandler(absl.logging._absl_handler) # pylint: disable=c-extension-no-member
 
 handler_num = 0