[jit] jit.save support property serialization (#44581)

* jit.save support peropty serilization

* extract set property function

* fix property test file name

* fix typing error

* fix typing error

* fix test coverage

paddle/fluid/pybind/protobuf.cc

@@ -433,15 +433,6 @@ void BindJitProperty(pybind11::module *m) {
            "set list of string",
            py::arg("name"),
            py::arg("val"))
-      .def("set_tensor",
-           [](const pd::VarDesc &tensor, const std::string name) {
-             throw platform::errors::Unimplemented("Not implement set_tensor.");
-           })
-      .def(
-          "set_tensors",
-          [](const pybind11::list &tensors, const std::string name) {
-            throw platform::errors::Unimplemented("Not implement set_tensors.");
-          })
       .def("serialize_to_string", SerializeMessage<jit::Property>)
       .def("parse_from_string", DeserializeMessage<jit::Property>);
 }

python/paddle/fluid/dygraph/io.py

@@ -37,6 +37,7 @@
 INFER_MODEL_SUFFIX = ".pdmodel"
 INFER_PARAMS_SUFFIX = ".pdiparams"
 INFER_PARAMS_INFO_SUFFIX = ".pdiparams.info"
+INFER_PROPERTY_SUFFIX = '.meta'
 
 LOADED_VAR_SUFFIX = "load"
 PARAMETER_NAME_PREFIX = "param"

python/paddle/fluid/dygraph/jit.py

@@ -22,6 +22,7 @@
 from collections import OrderedDict
 import inspect
 import threading
+from typing import Text, Tuple, Any, List
 
 import six
 import paddle
@@ -34,7 +35,7 @@
 from paddle.fluid.dygraph.dygraph_to_static.convert_call_func import ConversionOptions, CONVERSION_OPTIONS
 from paddle.fluid.dygraph.dygraph_to_static.logging_utils import set_code_level, set_verbosity
 from paddle.fluid.dygraph.dygraph_to_static.program_translator import ProgramTranslator, StaticFunction, unwrap_decorators
-from paddle.fluid.dygraph.io import TranslatedLayer, INFER_MODEL_SUFFIX, INFER_PARAMS_SUFFIX, INFER_PARAMS_INFO_SUFFIX
+from paddle.fluid.dygraph.io import TranslatedLayer, INFER_MODEL_SUFFIX, INFER_PARAMS_SUFFIX, INFER_PARAMS_INFO_SUFFIX, INFER_PROPERTY_SUFFIX
 from paddle.fluid.dygraph.layers import Layer
 from paddle.fluid.executor import Executor, scope_guard
 from paddle.fluid.framework import Block, ParamBase, Program, Variable, Parameter, EagerParamBase
@@ -644,6 +645,40 @@ def wrapper(layer, path, input_spec=None, **configs):
     return wrapper
 
 
+def _save_property(filename: Text, property_vals: List[Tuple[Any, Text]]):
+    """class property serialization.
+
+    Args:
+        filename (Text): *.meta
+        property_vals (List[Tuple): class property.
+    """
+
+    def set_property(meta, key, val):
+        if isinstance(val, float):
+            meta.set_float(key, val)
+        elif isinstance(val, int):
+            meta.set_int(key, val)
+        elif isinstance(val, str):
+            meta.set_string(key, val)
+        elif isinstance(val, (tuple, list)):
+            if isinstance(val[0], float):
+                meta.set_floats(key, val)
+            elif isinstance(val[0], int):
+                meta.set_ints(key, val)
+            elif isinstance(val[0], str):
+                meta.set_strings(key, val)
+        else:
+            raise ValueError(f"Note support val type: {type(val)}")
+        return
+
+    with open(filename, 'wb') as f:
+        meta = paddle.framework.core.Property()
+        for item in property_vals:
+            val, key = item[0], item[1]
+            set_property(meta, key, val)
+        f.write(meta.serialize_to_string())
+
+
 @_run_save_pre_hooks
 @switch_to_static_graph
 def save(layer, path, input_spec=None, **configs):
@@ -1043,7 +1078,9 @@ def fun(inputs):
                                         filter(paddle.fluid.io.is_persistable,
                                                ordered_vars)),
                                     filename=params_filename)
-        # TODO: save property
+        # save property
+        property_filename = file_prefix + INFER_PROPERTY_SUFFIX
+        _save_property(property_filename, property_vals)
 
     # NOTE(chenweihang): [ Save extra variable info ]
     # save_inference_model will lose some important variable information, including:

python/paddle/fluid/tests/unittests/test_jit_save_load.py

@@ -1,4 +1,5 @@
 # Copyright (c) 2020 PaddlePaddle Authors. All Rights Reserved.
+# Copyright (c) 2020 PaddlePaddle Authors. All Rights Reserved.
 #
 # Licensed under the Apache License, Version 2.0 (the "License");
 # you may not use this file except in compliance with the License.
@@ -1156,7 +1157,7 @@ def forward(self, x):
 class Net(paddle.nn.Layer):
 
     def __init__(self):
-        super(Net, self).__init__()
+        super().__init__()
         self.fc1 = paddle.nn.Linear(4, 4)
         self.fc2 = paddle.nn.Linear(4, 4)
         self.bias = 0.4
@@ -1185,13 +1186,49 @@ def infer(self, input):
     def fbias(self):
         return self.bias + 1
 
-    # For extra Tensor
+    @paddle.jit.to_static(property=True)
+    def down_sampling(self):
+        return 4
+
+    @paddle.jit.to_static(property=True)
+    def fstr(self):
+        return "save str property"
+
+    @paddle.jit.to_static(property=True)
+    def ints(self):
+        return [10, 20]
+
+    @paddle.jit.to_static(property=True)
+    def floats(self):
+        return [1.1, 2.2]
+
+    @paddle.jit.to_static(property=True)
+    def strs(self):
+        return ["hello", "world"]
+
+
+class NetTensor(paddle.nn.Layer):
+
+    def __init__(self):
+        super().__init__()
+        self.fc1 = paddle.nn.Linear(4, 4)
+        self.fc2 = paddle.nn.Linear(4, 4)
+        self.bias = 0.4
+        self.flag = paddle.ones([2], dtype="int32")
+
+    @paddle.jit.to_static(input_spec=[InputSpec([None, 4], dtype='float32')])
+    def forward(self, x):
+        out = self.fc1(x)
+        out = paddle.nn.functional.relu(out)
+        out = paddle.mean(out)
+        return out
+
     @paddle.jit.to_static(property=True)
     def fflag(self):
-        return self.flag
+        return True
 
 
-class TestJitSaveCombine(unittest.TestCase):
+class TestJitSaveCombineProperty(unittest.TestCase):
 
     def setUp(self):
         # enable dygraph mode
@@ -1201,16 +1238,24 @@ def setUp(self):
     def tearDown(self):
         self.temp_dir.cleanup()
 
-    def test_save_load_finetune_load(self):
+    def test_jit_save_combine_property(self):
         model_path = os.path.join(self.temp_dir.name,
                                   "test_jit_save_combine/model")
-
         # Use new namespace
         with unique_name.guard():
             net = Net()
         #save
         paddle.jit.save(net, model_path, combine_params=True)
 
+    def test_jit_save_tensor_property(self):
+        model_path = os.path.join(self.temp_dir.name,
+                                  "test_jit_save_combine/model")
+        # Use new namespace
+        with unique_name.guard():
+            net = NetTensor()
+
+        paddle.jit.save(net, model_path, combine_params=True)
+
 
 class LayerLoadFinetune(paddle.nn.Layer):