Removed InputCutInfo, disabled input cut in OVC. (openvinotoolkit#18927)

* Fixed output_model logic.

* Removed InputCutInfo, disabled input cut in ovc.

* Disabled output cut, added tests for setting shapes or types for not all inputs.

* Returned support of numpy type.

* Separated MO and OVC python API tests.

* Small corrections.

* Added output dir test, exceptions test.

* Tests fixed.

* Corrected extension param description.

* Corrected input description, minor code corrections.

.ci/azure/linux.yml

@@ -551,6 +551,15 @@ jobs:
       TEST_DEVICE: CPU
     displayName: 'TensorFlow Lite Layer Tests - TFL FE'
 
+  - script: |
+      set -e
+      python3 -m pip install -r $(LAYER_TESTS_DIR)/requirements.txt
+      $(RUN_PREFIX) python3 -m pytest $(LAYER_TESTS_DIR)/ovc_python_api_tests/  --junitxml=./TEST-test_ovc_convert.xmlTEST
+    env:
+      PYTHONPATH: $(LAYER_TESTS_DIR)
+      TEST_DEVICE: CPU
+    displayName: 'OVC Python API Tests'
+
   - script: |
       set -e
       python3 -m pip install -r $(LAYER_TESTS_DIR)/requirements.txt

src/bindings/python/src/openvino/__init__.py

@@ -57,6 +57,6 @@
 # Tools
 try:
     # Model Conversion API - ovc should reside in the main namespace
-    from openvino.tools.ovc import convert_model, InputCutInfo
+    from openvino.tools.ovc import convert_model
 except ImportError:
     pass

tests/layer_tests/common/mo_convert_test_class.py

@@ -53,7 +53,7 @@ def _test(self, temp_dir, test_params, ref_params):
         ir_ref = core.read_model(Path(temp_dir, 'model_ref.xml'))
 
         flag, msg = compare_functions(ir_test, ir_ref)
-        assert flag, '\n'.join(msg)
+        assert flag, msg
 
     def _test_by_ref_graph(self, temp_dir, test_params, ref_graph, compare_tensor_names=True, compare_layout=True):
         """

tests/layer_tests/mo_python_api_tests/test_mo_convert_complex_params.py

@@ -5,9 +5,8 @@
 import os
 import pytest
 from openvino.runtime import Model, Layout, PartialShape, Shape, layout_helpers, Type, Dimension
-from openvino.tools.ovc import InputCutInfo
-from openvino.tools.mo import LayoutMap
-
+from openvino.tools.mo import LayoutMap, InputCutInfo
+import openvino.runtime as ov
 from common.mo_convert_test_class import CommonMOConvertTest
 from common.tf_layer_test_class import save_to_pb
 
@@ -134,11 +133,11 @@ def create_tf_param_res_model(self, tmp_dir):
         {'params_test': {'input_shape': [PartialShape([2, 3, 4]),
                                          [2, 3, 4],
                                          [Dimension(2), Dimension(3), Dimension(4)]],
-                         'input':['Input1', 'Input2', 'Relu3'], 'use_convert_model_from_mo': True, 'compress_to_fp16': True},
+                         'input':['Input1', 'Input2', 'Relu3'], 'compress_to_fp16': True},
          'params_ref': {'input_shape': "[2,3,4],[2,3,4],[2,3,4]", 'input': 'Input1,Input2,Relu3'}},
         {'params_test': {'input_shape': [PartialShape([Dimension(), Dimension(1, 3), Dimension(4, -1), Dimension(-1, 5)]),
                                          [Dimension(), Dimension(1, 3), 4, Dimension(-1, 5)],
-                                         [Dimension(), 3, Dimension(4, -1), Dimension(-1, 5)]], 'use_convert_model_from_mo': True,
+                                         [Dimension(), 3, Dimension(4, -1), Dimension(-1, 5)]],
                          'compress_to_fp16': True,
                          'input':['Input1', 'Input2', 'Relu3']},
          'params_ref': {'input_shape': "[?,1..3,4..,..5],[?,1..3,4,..5],[?,3,4..,..5]", 'input': 'Input1,Input2,Relu3'}},
@@ -153,32 +152,27 @@ def create_tf_param_res_model(self, tmp_dir):
         {'params_test': {'output': ["Sigmoid_0", "Sigmoid_2"]},
          'params_ref': {'output': "Sigmoid_0,Sigmoid_2"}},
         {'params_test': {'mean_values': {'Input1': [0.5,1.3,0.67], 'Input2':[4.2, 6.7, 3.15], 'Input3':[0.757, 4.6, 7.3]},
-                         'use_convert_model_from_mo': True, 'compress_to_fp16': True},
+                         'compress_to_fp16': True},
          'params_ref': {'mean_values': "Input1[0.5,1.3,0.67],Input2[4.2,6.7,3.15],Input3[0.757,4.6,7.3]"}},
         {'params_test': {
-            'mean_values': [[0.5, 1.3, 0.67], [4.2, 6.7, 3.15], [0.757, 4.6, 7.3]], 'use_convert_model_from_mo': True,
-            'compress_to_fp16': True},
+            'mean_values': [[0.5, 1.3, 0.67], [4.2, 6.7, 3.15], [0.757, 4.6, 7.3]], 'compress_to_fp16': True},
          'params_ref': {'mean_values': "[0.5,1.3,0.67],[4.2,6.7,3.15],[0.757,4.6,7.3]"}},
         {'params_test': {'scale_values': {'Input1': [0.5,1.3,0.67], 'Input2':[4.2, 6.7, 3.15], 'Input3':[0.757, 4.6, 7.3]},
-                         'use_convert_model_from_mo': True, 'compress_to_fp16': True},
+                         'compress_to_fp16': True},
          'params_ref': {'scale_values': "Input1[0.5,1.3,0.67],Input2[4.2,6.7,3.15],Input3[0.757,4.6,7.3]"}},
         {'params_test': {
-            'scale_values': [[0.5, 1.3, 0.67], [4.2, 6.7, 3.15], [0.757, 4.6, 7.3]], 'use_convert_model_from_mo': True,
-            'compress_to_fp16': True},
+            'scale_values': [[0.5, 1.3, 0.67], [4.2, 6.7, 3.15], [0.757, 4.6, 7.3]], 'compress_to_fp16': True},
          'params_ref': {'scale_values': "[0.5,1.3,0.67],[4.2,6.7,3.15],[0.757,4.6,7.3]"}},
         {'params_test': {
-            'source_layout': {'Input1': Layout("nchw"), 'Input2': "nchw", 'Input3': "nc??"}, 'use_convert_model_from_mo': True,
-            'compress_to_fp16': True},
+            'source_layout': {'Input1': Layout("nchw"), 'Input2': "nchw", 'Input3': "nc??"}, 'compress_to_fp16': True},
          'params_ref': {'source_layout': "Input1(nchw),Input2(nchw),Input3(nc??)"}},
         {'params_test': {
-            'target_layout': {'Input1': Layout("nhwc"), 'Input2': "nhwc", 'Input3': "n??c"}, 'use_convert_model_from_mo': True,
-            'compress_to_fp16': True},
+            'target_layout': {'Input1': Layout("nhwc"), 'Input2': "nhwc", 'Input3': "n??c"}, 'compress_to_fp16': True},
             'params_ref': {'target_layout': "Input1(nhwc),Input2(nhwc),Input3(n??c)"}},
         {'params_test': {
             'layout': {'Input1': LayoutMap(source_layout=Layout("nchw"), target_layout="nhwc"),
                        'Input2': LayoutMap(source_layout="nc??", target_layout=Layout("n??c")),
-                       'Input3': LayoutMap(source_layout="abcd", target_layout="acdb")}, 'use_convert_model_from_mo': True,
-            'compress_to_fp16': True},
+                       'Input3': LayoutMap(source_layout="abcd", target_layout="acdb")}, 'compress_to_fp16': True},
             'params_ref': {'layout': "Input1(nchw->nhwc),Input2(nc??->n??c),Input3(abcd->acdb)"}},
         {'params_test': {'input': [PartialShape([2, 3, 4]), [2, 3, 4], [Dimension(2), Dimension(3), Dimension(4)]]},
          'params_ref': {'input_shape': "[2,3,4],[2,3,4],[2,3,4]", 'input': 'Input1,Input2,Input3'}},
@@ -198,6 +192,7 @@ def test_mo_convert_tf_model(self, params, ie_device, precision, ir_version,
 
         test_params = params['params_test']
         ref_params = params['params_ref']
+        test_params.update({'use_convert_model_from_mo': True})
         test_params.update({'input_model': tf_net_path})
         ref_params.update({'input_model': tf_net_path})
         self._test(temp_dir, test_params, ref_params)
@@ -241,16 +236,13 @@ def test_mo_convert_tf_model_no_concat(self, params, ie_device, precision, ir_ve
         # By default compress_to_fp16 in Python API is False but for mo cli tool (used for params_ref) it's True.
         # compress_to_fp16 should be specified explicitly either in 'param_test' or  'params_ref' (or in both)
         # Check all args combinations.
-        {'params_test': {'input_shape': PartialShape([2, 3, 4]), 'use_convert_model_from_mo': True,
-                         'compress_to_fp16': True},
+        {'params_test': {'input_shape': PartialShape([2, 3, 4]), 'compress_to_fp16': True},
          'params_ref': {'input_shape': "[2,3,4]"}},
-        {'params_test': {'input_shape': PartialShape([2, 3, 4]), 'use_convert_model_from_mo': True},
+        {'params_test': {'input_shape': PartialShape([2, 3, 4])},
          'params_ref': {'input_shape': "[2,3,4]", 'compress_to_fp16': False}},
-        {'params_test': {'input_shape': PartialShape([2, 3, 4]), 'use_convert_model_from_mo': True,
-                         'compress_to_fp16': True},
+        {'params_test': {'input_shape': PartialShape([2, 3, 4]), 'compress_to_fp16': True},
          'params_ref': {'input_shape': "[2,3,4]", 'compress_to_fp16': True}},
-        {'params_test': {'input_shape': PartialShape([2, 3, 4]), 'use_convert_model_from_mo': True,
-                         'compress_to_fp16': False},
+        {'params_test': {'input_shape': PartialShape([2, 3, 4]), 'compress_to_fp16': False},
          'params_ref': {'input_shape': "[2,3,4]", 'compress_to_fp16': False}},
 
         # ovc.convert_model with save_model are used, by default save_model compresses to fp16 same as cli tool.
@@ -266,8 +258,7 @@ def test_mo_convert_tf_model_no_concat(self, params, ie_device, precision, ir_ve
         {'params_test': {'input': InputCutInfo("Relu", [3, 2], Type(np.int32), [1, 2, 3, 4, 5, 6]), 'compress_to_fp16': False},
          'params_ref': {'input': "Relu[3 2]{i32}->[1 2 3 4 5 6]", 'compress_to_fp16': False}},
 
-        {'params_test': {'input_shape': [Dimension(), Dimension(1, 3), 4, Dimension(-1, 5)], 'use_convert_model_from_mo': True,
-                         'compress_to_fp16': True},
+        {'params_test': {'input_shape': [Dimension(), Dimension(1, 3), 4, Dimension(-1, 5)], 'compress_to_fp16': True},
          'params_ref': {'input_shape': "[?,1..3,4,..5]"}},
         {'params_test': {'input': InputCutInfo("Relu", [3, 2], Type(np.int32), [1, 2, 3, 4, 5, 6])},
          'params_ref': {'input': "Relu[3 2]{i32}->[1 2 3 4 5 6]"}},
@@ -279,18 +270,17 @@ def test_mo_convert_tf_model_no_concat(self, params, ie_device, precision, ir_ve
          'params_ref': {'input': "Relu[3 2]"}},
         {'params_test': {'input': ("Relu")},
          'params_ref': {'input': "Relu"}},
-        {'params_test': {'mean_values': [0.5, 1.3, 0.67], 'use_convert_model_from_mo': True, 'compress_to_fp16': True},
+        {'params_test': {'mean_values': [0.5, 1.3, 0.67], 'compress_to_fp16': True},
          'params_ref': {'mean_values': "[0.5,1.3,0.67]"}},
-        {'params_test': {'scale_values': [0.5, 1.3, 0.67], 'use_convert_model_from_mo': True, 'compress_to_fp16': True},
+        {'params_test': {'scale_values': [0.5, 1.3, 0.67], 'compress_to_fp16': True},
          'params_ref': {'scale_values': "[0.5,1.3,0.67]"}},
-        {'params_test': {'source_layout': Layout("nchw"), 'use_convert_model_from_mo': True, 'compress_to_fp16': True},
+        {'params_test': {'source_layout': Layout("nchw"), 'compress_to_fp16': True},
          'params_ref': {'source_layout': "nchw"}},
-        {'params_test': {'target_layout': Layout("nchw"), 'use_convert_model_from_mo': True, 'compress_to_fp16': True},
+        {'params_test': {'target_layout': Layout("nchw"), 'compress_to_fp16': True},
          'params_ref': {'target_layout': "nchw"}},
-        {'params_test': {'layout': LayoutMap(source_layout=Layout("nchw"), target_layout="nhwc"),
-                         'use_convert_model_from_mo': True, 'compress_to_fp16': True},
+        {'params_test': {'layout': LayoutMap(source_layout=Layout("nchw"), target_layout="nhwc"), 'compress_to_fp16': True},
          'params_ref': {'layout': "nchw->nhwc"}},
-        {'params_test': {'layout': Layout("nchw"), 'use_convert_model_from_mo': True, 'compress_to_fp16': True},
+        {'params_test': {'layout': Layout("nchw"), 'compress_to_fp16': True},
          'params_ref': {'layout': "nchw"}},
         {'params_test': {'input': [3, 2]},
          'params_ref': {'input': "Input[3 2]"}},
@@ -306,13 +296,13 @@ def test_mo_convert_tf_model_no_concat(self, params, ie_device, precision, ir_ve
          'params_ref': {'input': "Input[1]{i32}->[10]"}},
         {'params_test': {'input': (np.int32, [1, 2, 3])},
          'params_ref': {'input': "Input[1,2,3]{i32}"}},
-        {'params_test': {'input_shape': [Dimension(3, 10), 10, -1], 'use_convert_model_from_mo': True, 'compress_to_fp16': True},
+        {'params_test': {'input_shape': [Dimension(3, 10), 10, -1], 'compress_to_fp16': True},
          'params_ref': {'input_shape': '[3..10,10,?]'}},
         {'params_test': {'input': [Dimension(3, 10), 10, -1]},
          'params_ref': {'input': 'Input[3..10,10,?]'}},
-        {'params_test': {'input': PartialShape([1, 100, 100, 3]), 'mean_values': [0.5, 1.3, 0.67], 'use_convert_model_from_mo': True, 'compress_to_fp16': True},
+        {'params_test': {'input': PartialShape([1, 100, 100, 3]), 'mean_values': [0.5, 1.3, 0.67], 'compress_to_fp16': True},
          'params_ref': {'input': "Input[1,100,100,3]", 'mean_values': "[0.5,1.3,0.67]"}},
-        {'params_test': {'input': [1, 100, 100, 3], 'scale_values': [0.5, 1.3, 0.67], 'use_convert_model_from_mo': True, 'compress_to_fp16': True},
+        {'params_test': {'input': [1, 100, 100, 3], 'scale_values': [0.5, 1.3, 0.67], 'compress_to_fp16': True},
          'params_ref': {'input': "Input[1,100,100,3]", 'scale_values': "[0.5,1.3,0.67]"}},
     ]
 
@@ -325,6 +315,7 @@ def test_mo_convert_tf_model_single_input_output(self, params, ie_device, precis
 
         test_params = params['params_test']
         ref_params = params['params_ref']
+        test_params.update({'use_convert_model_from_mo': True})
         test_params.update({'input_model': tf_net_path})
         ref_params.update({'input_model': tf_net_path})
         self._test(temp_dir, test_params, ref_params)

tests/layer_tests/mo_python_api_tests/test_mo_convert_extensions.py

@@ -102,9 +102,9 @@ def create_ref_graph2():
         return Model([sigmoid], [param], "test")
 
     test_data = [
-        {'params_test': {'extension': create_custom_extension_leaky_relu_to_relu()},
+        {'params_test': {'extensions': create_custom_extension_leaky_relu_to_relu()},
          'ref_graph': create_ref_graph1()},
-        {'params_test': {'extension': [create_custom_extension_leaky_relu_to_relu(),
+        {'params_test': {'extensions': [create_custom_extension_leaky_relu_to_relu(),
                                         create_custom_extension_elu_to_sigmoid()]},
          'ref_graph': create_ref_graph2()}
     ]
@@ -118,4 +118,5 @@ def test_mo_convert_extensions(self, params, ie_device, precision, ir_version,
 
         test_params = params['params_test']
         test_params.update({'input_model': onnx_net_path})
+        test_params.update({'use_convert_model_from_mo': True})
         self._test_by_ref_graph(temp_dir, test_params, params['ref_graph'])

tests/layer_tests/mo_python_api_tests/test_mo_convert_onnx.py

@@ -49,9 +49,8 @@ def make_graph_proto_model():
 
 def create_ref_model(shape):
     param1 = ov.opset8.parameter(shape, dtype=np.float32)
-    slope_const = ov.opset8.constant([0.1], dtype=np.float16)
-    decompress_slope = ov.opset8.convert(slope_const, np.float32)
-    prelu = ov.opset8.prelu(param1, slope=decompress_slope)
+    slope_const = ov.opset8.constant([0.1], dtype=np.float32)
+    prelu = ov.opset8.prelu(param1, slope=slope_const)
     relu = ov.opset8.elu(prelu, alpha=np.float32(0.1))
     parameter_list = [param1]
     return Model([relu], parameter_list, "test")
@@ -79,5 +78,6 @@ def test_mo_convert_onnx(self, create_model, ie_device, precision, ir_version,
         test_params = {'input_model': fw_model}
         if mo_params is not None:
             test_params.update(mo_params)
+        test_params.update({'use_convert_model_from_mo': True})
         self._test_by_ref_graph(temp_dir, test_params, graph_ref, compare_tensor_names=False)
 

tests/layer_tests/mo_python_api_tests/test_mo_convert_paddle.py

@@ -100,4 +100,5 @@ def test_mo_import_from_memory_paddle_fe(self, create_model, ie_device, precisio
         test_params = {'input_model': fw_model, 'use_new_frontend': True}
         if mo_params is not None:
             test_params.update(mo_params)
+        test_params.update({'use_convert_model_from_mo': True})
         self._test_by_ref_graph(temp_dir, test_params, graph_ref, compare_tensor_names=False)