diff --git a/model-optimizer/extensions/ops/select.py b/model-optimizer/extensions/ops/select.py
index cac32852b63..09d541a2b0a 100644
--- a/model-optimizer/extensions/ops/select.py
+++ b/model-optimizer/extensions/ops/select.py
@@ -49,14 +49,14 @@ class Select(Op):
         node.out_port(0).data.set_shape(broadcast_shape(a_shape, b_shape))
         # Case with unknown condition
         if condition_value is not None:
+            output_value = np.where(condition_value, resulting_tensors[0], resulting_tensors[1])
             if condition_value.size != 1:
-                output_value = np.where(condition_value, resulting_tensors[0], resulting_tensors[1])
                 if np.any(output_value == None):
                     # If any element of output value is None that means that we use the value from 'then' or 'else' tensor
                     # which is not defined, this means that we cannot perform value propagation.
                     output_value = None
             else:
-                output_value = resulting_tensors[not np.bool(condition_value.item(0))]
+                output_value = np.array(output_value, dtype=resulting_tensors[not np.bool(condition_value.item(0))].dtype)
 
             if output_value is not None:
                 node.out_port(0).data.set_value(np.array(output_value))
diff --git a/model-optimizer/extensions/ops/select_test.py b/model-optimizer/extensions/ops/select_test.py
index e0e1686a30b..2f504b79d4e 100644
--- a/model-optimizer/extensions/ops/select_test.py
+++ b/model-optimizer/extensions/ops/select_test.py
@@ -151,31 +151,52 @@ class TestSelect(unittest.TestCase):
         self.assertTrue(flag, resp)
 
     @generate(*[
-        ([5, 6], [5, 6], [5, 6], np.ones(np.array([5, 6]), dtype=np.float),
-         np.zeros([5, 6], dtype=np.float), np.ones([5, 6], dtype=np.float),
-         np.ones([5, 6], dtype=np.float)),
-        ([15, 3, 5], [15, 1, 5], [15, 3, 5], np.ones([15, 3, 5], dtype=np.float),
-         np.zeros([15, 3, 5], dtype=np.float), np.ones([15, 3, 5], dtype=np.float),
-         np.ones([15, 3, 5], dtype=np.float)),
-        ([15, 3, 5], [15, 1, 5], [15, 3, 5], np.ones([15, 3, 5], dtype=np.float),
-         None, np.ones([15, 3, 5], dtype=np.float), np.ones([15, 3, 5], dtype=np.float)),
-        ([15, 3, 5], [15, 1, 5], [15, 3, 5], np.ones([15, 3, 5], dtype=np.float),
-         np.ones([15, 3, 5], dtype=np.float), None, None),
-        ([15, 3, 5], [15, 1, 5], [15, 3, 5], np.zeros([15, 3, 5], dtype=np.float),
-         None, np.ones([15, 3, 5], dtype=np.float), None),
-        ([15, 3, 5], [15, 1, 5], [15, 3, 5], np.zeros([15, 3, 5], dtype=np.float),
-         np.ones([15, 3, 5], dtype=np.float), None, np.ones([15, 3, 5], dtype=np.float)),
-        ([15, 3, 5], [15, 1, 5], [15, 3, 5], np.array([True], np.bool),
-         np.zeros([15, 3, 5], dtype=np.float), np.ones([15, 3, 5], dtype=np.float),
-         np.ones([15, 3, 5], dtype=np.float)),
-        ([15, 3, 5], [15, 1, 5], [15, 3, 5], np.array([False], np.bool),
-         np.zeros([15, 3, 5], dtype=np.float), np.ones([15, 3, 5], dtype=np.float),
-         np.zeros([15, 3, 5], dtype=np.float)),
+        ([5, 6], [5, 6], [5, 6], [5, 6], lambda x: np.ones(x, dtype=np.float),
+         lambda x: np.zeros(x, dtype=np.float), lambda x: np.ones(x, dtype=np.float),
+         lambda x: np.ones(x, dtype=np.float)),
+        ([15, 3, 5], [15, 3, 5], [15, 1, 5], [15, 3, 5], lambda x: np.ones(x, dtype=np.float),
+         lambda x: np.zeros(x, dtype=np.float), lambda x: np.ones(x, dtype=np.float),
+         lambda x: np.ones(x, dtype=np.float)),
+        ([15, 3, 5], [15, 3, 5], [15, 1, 5], [15, 3, 5], lambda x: np.ones(x, dtype=np.float),
+         lambda x: None, lambda x: np.ones(x, dtype=np.float), lambda x: np.ones(x, dtype=np.float)),
+        ([15, 3, 5], [15, 3, 5], [15, 1, 5], [15, 3, 5], lambda x: np.ones(x, dtype=np.float),
+         lambda x: np.ones(x, dtype=np.float), lambda x: None, lambda x: None),
+        ([15, 3, 5], [15, 3, 5], [15, 1, 5], [15, 3, 5], lambda x: np.zeros(x, dtype=np.float),
+         lambda x: None, lambda x: np.ones(x, dtype=np.float), lambda x: None),
+        ([15, 3, 5], [15, 3, 5], [15, 1, 5], [15, 3, 5], lambda x: np.zeros(x, dtype=np.float),
+         lambda x: np.ones(x, dtype=np.float), lambda x: None, lambda x: np.ones(x, dtype=np.float)),
+        ([15, 3, 5], [15, 3, 5], [15, 1, 5], [15, 3, 5], lambda x: np.array([True], np.bool),
+         lambda x: np.zeros(x, dtype=np.float), lambda x: np.ones(x, dtype=np.float),
+         lambda x: np.ones(x, dtype=np.float)),
+        ([15, 3, 5], [15, 3, 5], [15, 1, 5], [15, 3, 5], lambda x: np.array([False], np.bool),
+         lambda x: np.zeros(x, dtype=np.float), lambda x: np.ones(x, dtype=np.float),
+         lambda x: np.zeros(x, dtype=np.float)),
+        ([2, 3, 4, 5], [2, 3, 4, 5], [], [2, 3, 4, 5], lambda x: np.ones(x, dtype=np.float),
+         lambda x: np.zeros(x, dtype=np.float), lambda x: np.ones(x, dtype=np.float),
+         lambda x: np.ones(x, dtype=np.float)),
+        ([2, 3, 4, 5], [2, 3, 4, 5], [5], [2, 3, 4, 5], lambda x: np.ones(x, dtype=np.float),
+         lambda x: np.zeros(x, dtype=np.float), lambda x: np.ones(x, dtype=np.float),
+         lambda x: np.ones(x, dtype=np.float)),
+        ([2, 3, 1, 1], [2, 1, 1, 5], [2, 3, 4, 5], [2, 3, 4, 5], lambda x: np.ones(x, dtype=np.float),
+         lambda x: np.zeros(x, dtype=np.float), lambda x: np.ones(x, dtype=np.float),
+         lambda x: np.ones(x, dtype=np.float)),
+        ([2, 3, 4, 1], [2, 1, 1, 5], [1, 3, 1, 5], [2, 3, 4, 5], lambda x: np.ones(x, dtype=np.float),
+         lambda x: np.zeros(x, dtype=np.float), lambda x: np.ones(x, dtype=np.float),
+         lambda x: np.ones(x, dtype=np.float)),
     ])
-    def test_select_infer_condition_with_value(self, else_data_shape, than_data_shape, select_output_shape,
+    def test_select_infer_condition_with_value(self, condition_shape, else_data_shape, than_data_shape, select_output_shape,
                                                condition_value, else_value, than_value, output_value):
+        """
+        Unit tests generator can sporadic throw exception if we try
+        to run generator with call numpy array generation functions.
+        So we need to use lambda function for escape the problem.
+        """
+        condition_value = condition_value(condition_shape)
+        else_value = else_value(else_data_shape)
+        than_value = than_value(than_data_shape)
+        output_value = output_value(select_output_shape)
         graph = build_graph_with_attrs(nodes_with_attrs=self.nodes, edges_with_attrs=self.edges,
-                                       update_nodes_attributes=[('condition_data', {'shape': np.array(select_output_shape),
+                                       update_nodes_attributes=[('condition_data', {'shape': np.array(condition_shape),
                                                                                     'value': condition_value}),
                                                                 ('else_data', {'shape': np.array(else_data_shape),
                                                                                'value': else_value}),
@@ -188,7 +209,7 @@ class TestSelect(unittest.TestCase):
 
         graph_ref = build_graph_with_attrs(nodes_with_attrs=self.nodes, edges_with_attrs=self.edges,
                                            update_nodes_attributes=[
-                                               ('condition_data', {'shape': np.array(else_data_shape),
+                                               ('condition_data', {'shape': np.array(condition_shape),
                                                                    'value': condition_value}),
                                                ('else_data', {'shape': np.array(else_data_shape),
                                                               'value': else_value}),