Update Paddle API for ovc tools

.github/workflows/job_python_unit_tests.yml

@@ -194,7 +194,8 @@ jobs:
           if [[ "${{ runner.os }}" == "Linux" ]] && [[ "${{ runner.arch }}" == "ARM64" ]]; then
             # Find gomp lib
             GOMP_LIB=$(find "${PIP_INSTALL_PATH}/torch/lib/../../torch.libs/" -name '*libgomp-*so*')
-            export LD_PRELOAD=${GOMP_LIB}
+            GOMP_LIB_GLOBAL=$(ldconfig -p | grep libgomp | grep AArch64 | awk '{print $4}')
+            export LD_PRELOAD=${GOMP_LIB}:${GOMP_LIB_GLOBAL}
           fi
 
           python3 -m pytest ${LAYER_TESTS_INSTALL_DIR}/ovc_python_api_tests --junitxml=${INSTALL_TEST_DIR}/TEST-test_ovc_convert.xml

tests/constraints.txt

@@ -16,7 +16,7 @@ tensorflow>=2.5,<2.17.0
 test-generator==0.1.2
 requests>=2.25.1
 opencv-python>=4.5
-paddlepaddle==2.5.0
+paddlepaddle==2.6.0
 protobuf>=3.18.1,<4.0.0
 py>=1.9.0
 pytest>=5.0,<7.5

tests/layer_tests/ovc_python_api_tests/test_paddle.py

@@ -92,7 +92,6 @@ class TestMoConvertPaddle(CommonMOConvertTest):
         create_paddle_static_module,
         create_paddle_hapi_module
     ]
-    @pytest.mark.skip(reason="Paddlepaddle has incompatible protobuf. Ticket: 95904")
     @pytest.mark.parametrize("create_model", test_data)
     def test_mo_import_from_memory_paddle_fe(self, create_model, ie_device, precision, ir_version,
                                              temp_dir):

tests/layer_tests/requirements.txt

@@ -1,5 +1,5 @@
 -c ../constraints.txt
-# paddlepaddle #  ticket 95904
+paddlepaddle
 numpy
 onnxruntime
 requests

tools/ovc/openvino/tools/ovc/convert.py

@@ -51,8 +51,10 @@ def convert_model(
 
             PaddlePaddle
             paddle.hapi.model.Model
-            paddle.fluid.dygraph.layers.Layer
-            paddle.fluid.executor.Executor
+            paddle.nn.layer.layers.Layer
+            paddle.fluid.dygraph.layers.Layer   # deprecated since paddle v2.5
+            paddle.base.Executor
+            paddle.fluid.executor.Executor      # deprecated since paddle v2.6
 
         :param input:
             Information of model input required for model conversion.

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

@@ -35,7 +35,7 @@
 from openvino.tools.ovc.telemetry_utils import send_params_info, send_conversion_result, \
     init_mo_telemetry
 from openvino.tools.ovc.moc_frontend.pytorch_frontend_utils import get_pytorch_decoder, extract_input_info_from_example
-from openvino.tools.ovc.moc_frontend.paddle_frontend_utils import paddle_frontend_converter
+from openvino.tools.ovc.moc_frontend.paddle_frontend_utils import paddle_frontend_converter, is_paddle_model
 
 # pylint: disable=no-name-in-module,import-error
 from openvino.frontend import FrontEndManager, OpConversionFailure, TelemetryExtension
@@ -222,12 +222,8 @@ def check_model_object(argv):
     if isinstance(model, io.BytesIO):
         return 'onnx'
 
-    if 'paddle' in sys.modules:
-        import paddle
-        if isinstance(model, paddle.hapi.model.Model) or isinstance(model,
-                                                                    paddle.fluid.dygraph.layers.Layer) or isinstance(
-            model, paddle.fluid.executor.Executor):
-            return "paddle"
+    if 'paddle' in sys.modules and is_paddle_model(model):
+        return "paddle"
 
     raise Error('Unknown model type: {}'.format(type(model)))
 

tools/ovc/openvino/tools/ovc/moc_frontend/paddle_frontend_utils.py

@@ -4,7 +4,26 @@
 import os
 import sys
 import tempfile
+# pylint: disable=no-name-in-module,import-error
 
+def paddle_class_check(class_str):
+    try:
+        import paddle
+        return eval(class_str)
+    except:
+        return None
+
+def paddle_model_check_instance(model, class_str):
+    cls = paddle_class_check(class_str)
+    if cls and isinstance(model, cls):
+        return True
+    else:
+        return False
+
+def is_paddle_model(model):
+    possible_instances = ["paddle.hapi.model.Model", "paddle.nn.layer.layers.Layer", "paddle.fluid.dygraph.layers.Layer", "paddle.base.Executor", "paddle.fluid.executor.Executor"]
+    is_instance = [paddle_model_check_instance(model, possible_instance) for possible_instance in possible_instances]
+    return any(is_instance)
 
 class paddle_frontend_converter:
     def __init__(self, model, inputs=None, outputs=None):
@@ -49,26 +68,30 @@ def convert_paddle_to_pdmodel(self):
             self.pdiparams = "{}.pdiparams".format(self.model_name)
             self.pdiparams_info = "{}.pdiparams.info".format(self.model_name)
 
-            import paddle  # pylint: disable=import-error
-            if isinstance(self.model, paddle.hapi.model.Model):
+            import paddle
+            if paddle_model_check_instance(self.model, "paddle.hapi.model.Model"):
                 self.model.save(self.model_name, False)
             else:
                 if self.inputs is None:
                     raise RuntimeError(
                         "Saving inference model needs 'inputs' before saving. Please specify 'example_input'"
                     )
-                if isinstance(self.model, paddle.fluid.dygraph.layers.Layer):
-                    with paddle.fluid.framework._dygraph_guard(None):
-                        paddle.jit.save(self.model, self.model_name, input_spec=self.inputs, output_spec=self.outputs)
-                elif isinstance(self.model, paddle.fluid.executor.Executor):
+                if paddle_model_check_instance(self.model, "paddle.nn.layer.layers.Layer") or paddle_model_check_instance(self.model, "paddle.fluid.dygraph.layers.Layer"):
+                    if paddle_class_check("paddle.base.framework._dygraph_guard"):
+                        with paddle.base.framework._dygraph_guard(None):
+                            paddle.jit.save(self.model, self.model_name, input_spec=self.inputs, output_spec=self.outputs)
+                    else:
+                        with paddle.fluid.framework._dygraph_guard(None):
+                            paddle.jit.save(self.model, self.model_name, input_spec=self.inputs, output_spec=self.outputs)
+                elif paddle_model_check_instance(self.model, "paddle.base.Executor") or paddle_model_check_instance(self.model, "paddle.fluid.executor.Executor"):
                     if self.outputs is None:
                         raise RuntimeError(
                             "Model is static. Saving inference model needs 'outputs' before saving. Please specify 'output' for this model"
                         )
                     paddle.static.save_inference_model(self.model_name, self.inputs, self.outputs, self.model)
                 else:
                     raise RuntimeError(
-                        "Conversion just support paddle.hapi.model.Model, paddle.fluid.dygraph.layers.Layer and paddle.fluid.executor.Executor"
+                        "Conversion just support paddle.hapi.model.Model, paddle.nn.layer.layers.Layer, paddle.fluid.dygraph.layers.Layer, paddle.base.Executor and paddle.fluid.executor.Executor"
                     )
 
             if not os.path.exists(self.pdmodel):