Fixed passing of bf16 and tf.string types to convert_model().

tests/layer_tests/ovc_python_api_tests/test_complex_params.py

@@ -277,6 +277,27 @@ def test_ovc_convert_model_with_several_output(self, ie_device, precision, ir_ve
         self._test(temp_dir, convert_model_params, cli_tool_params)
 
 
+    @pytest.mark.nightly
+    @pytest.mark.precommit
+    def test_non_numpy_types(self, ie_device, precision, ir_version, temp_dir, use_legacy_frontend):
+        import tensorflow as tf
+        def func(a, b):
+            return [a, b]
+        model = tf.function(func, input_signature=[tf.TensorSpec([2], tf.float32, "a"),
+                                                   tf.TensorSpec([2], tf.float32, "b")])
+        parameter1 = ov.opset8.parameter(ov.Shape([2]), ov.Type.bf16)
+        parameter2 = ov.opset8.parameter(ov.Shape([2]), ov.Type.bf16)
+        bf16_ref = ov.Model([parameter1, parameter2], [parameter1, parameter2])
+
+        parameter1 = ov.opset8.parameter(ov.Shape([2]), ov.Type.string)
+        parameter2 = ov.opset8.parameter(ov.Shape([2]), ov.Type.string)
+        string_ref = ov.Model([parameter1, parameter2], [parameter1, parameter2])
+
+        self._test_by_ref_graph(temp_dir, {'input_model': model, 'input': [ov.Type.bf16, tf.bfloat16]}, bf16_ref, compare_tensor_names=False)
+        self._test_by_ref_graph(temp_dir, {'input_model': model, 'input': {'a': ov.Type.bf16, 'b': tf.bfloat16}}, bf16_ref, compare_tensor_names=False)
+        self._test_by_ref_graph(temp_dir, {'input_model': model, 'input': [ov.Type.string, tf.string]}, string_ref, compare_tensor_names=False)
+        self._test_by_ref_graph(temp_dir, {'input_model': model, 'input': {'a': ov.Type.string, 'b': tf.string}}, string_ref, compare_tensor_names=False)
+
 class NegativeCases(unittest.TestCase):
     test_directory = os.path.dirname(os.path.realpath(__file__))
 

tools/ovc/openvino/tools/ovc/convert_impl.py

@@ -12,6 +12,8 @@
 from pathlib import Path
 from typing import Iterable, Callable
 
+import numpy as np
+
 try:
     import openvino_telemetry as tm
     from openvino_telemetry.backend import backend_ga4
@@ -343,10 +345,8 @@ def normalize_inputs(argv: argparse.Namespace):
                 shape_dict[inp.name] = None
             if inp.type is not None:
                 # Convert type to numpy type for uniformity of stored values
-                if isinstance(inp.type, str):
-                    data_type_dict[inp.name] = destination_type_to_np_data_type(inp.type)
-                elif isinstance(inp.type, Type):
-                    data_type_dict[inp.name] = inp.type.to_dtype().type
+                if isinstance(inp.type, (np.dtype, str)):
+                    data_type_dict[inp.name] = Type(inp.type)
                 else:
                     data_type_dict[inp.name] = inp.type
         argv.placeholder_shapes = shape_dict if shape_dict else None
@@ -361,10 +361,8 @@ def normalize_inputs(argv: argparse.Namespace):
                 shape_list.append(PartialShape(inp.shape))
             if inp.type is not None:
                 # Convert type to numpy type for uniformity of stored values
-                if isinstance(inp.type, str):
-                    data_type_list.append(destination_type_to_np_data_type(inp.type))
-                elif isinstance(inp.type, Type):
-                    data_type_list.append(inp.type.to_dtype().type)
+                if isinstance(inp.type, (np.dtype, str)):
+                    data_type_list.append(Type(inp.type))
                 else:
                     data_type_list.append(inp.type)
         argv.placeholder_shapes = shape_list if shape_list else None

tools/ovc/openvino/tools/ovc/moc_frontend/pipeline.py

@@ -181,7 +181,7 @@ def create_target_input_shapes(new_input_places):
                 input_model.set_partial_shape(
                     user_shape['node'], user_shape['shape'])
             if user_shape.get('data_type') is not None:
-                data_type = get_element_type(user_shape['data_type'])
+                data_type = user_shape['data_type']
                 log.debug('Set data type: {}'.format(data_type))
                 input_model.set_element_type(user_shape['node'], data_type)
 

tools/ovc/openvino/tools/ovc/moc_frontend/type_utils.py

@@ -33,7 +33,22 @@ def to_ov_type(val):
     if 'tensorflow' in sys.modules:
         import tensorflow as tf # pylint: disable=import-error
         if isinstance(val, tf.dtypes.DType):
-            return Type(val.as_numpy_dtype())
+            tf_to_ov_type = {
+                tf.float32: ov.Type.f32,
+                tf.float16: ov.Type.f16,
+                tf.float64: ov.Type.f64,
+                tf.bfloat16: ov.Type.bf16,
+                tf.uint8: ov.Type.u8,
+                tf.int8: ov.Type.i8,
+                tf.int16: ov.Type.i16,
+                tf.int32: ov.Type.i32,
+                tf.int64: ov.Type.i64,
+                tf.bool: ov.Type.boolean,
+                tf.string: ov.Type.string
+            }
+            if val not in tf_to_ov_type:
+                raise Exception("The provided data time is not supported {}.".format(val))
+            return tf_to_ov_type[val]
     if 'torch' in sys.modules:
         import torch
 
@@ -48,7 +63,7 @@ def to_ov_type(val):
                 torch.int16: ov.Type.i16,
                 torch.int32: ov.Type.i32,
                 torch.int64: ov.Type.i64,
-                torch.bool: ov.Type.boolean,
+                torch.bool: ov.Type.boolean
             }
             if val not in torch_to_ov_type:
                 raise Exception("The provided data time is not supported {}.".format(val))