Dygraph Layer kwargs & param getter setter (#19901)

* opt FC

* opt rest of dygraph.nn

* new param shape check and unittest

* add kwargs for Layer

* add new set_value api

* use property decorator

* update API.spec, test=develop

* use UserList, separate gettersetters, test=develop

* update test_custom_layer_with_kwargs, test=develop

* fix UserList compatibility, test=develop

* fix UserList compatibility, test=develop

* keep FC._w, test=develop

* add unittests, Conv3D bug fix, test=develop

* clean code, test=develop

* fix dygraph guard in unittest, test=develop

* add property setters, remove unused param in tracer, test=develop

* tracer none check, test=develop

* merge, test=develop

* refine, test=develop

* bug fix in  prelu and conv3d_transpose, test=develop

* rm __set__, test=develop

* set tensor value instead of assign op

* fix property setter call, test=develop

* fix api.spec, test=develop

* fix doc sample, test=develop

python/paddle/fluid/dygraph/layers.py

@@ -150,20 +150,20 @@ class Layer(core.Layer):
             if p.trainable:
                 p.clear_gradient()
 
-    def _build_once(self, *args):
+    def _build_once(self, *args, **kwargs):
         pass
 
-    def __call__(self, *inputs):
+    def __call__(self, *inputs, **kwargs):
         if not self._built:
-            self._build_once(*inputs)
+            self._build_once(*inputs, **kwargs)
             if parallel_helper._is_data_parallel_mode():
                 parallel_helper._broadcast_parameters(self._parameters.values())
 
-        outputs = self.forward(*inputs)
+        outputs = self.forward(*inputs, **kwargs)
         self._built = True
         return outputs
 
-    def forward(self, *inputs):
+    def forward(self, *inputs, **kwargs):
         raise NotImplementedError
 
     def backward(self, *inputs):
@@ -216,6 +216,8 @@ class Layer(core.Layer):
             return object.__getattribute__(self, name)
 
     def __setattr__(self, name, value):
+        if isinstance(getattr(type(self), name, None), property):
+            object.__setattr__(self, name, value)
         if isinstance(value, framework.Parameter):
             params = self.__dict__.get('_parameters', None)
             if params is None:
@@ -226,6 +228,11 @@ class Layer(core.Layer):
                 tensor = var.get_tensor()
                 tensor.set(self._loaddict_holder[value.name].numpy(),
                            framework._current_expected_place())
+            if name in params:
+                # remove unused param in tracer
+                if framework._dygraph_tracer_ is not None:
+                    framework._dygraph_tracer_._vars.pop(params[name].name,
+                                                         None)
             params[name] = value
         elif isinstance(value, core.Layer):
             layers = self.__dict__.get('_sub_layers', None)

python/paddle/fluid/framework.py

@@ -638,6 +638,45 @@ class Variable(object):
         new_ivar = self._ivar._copy_to(core.CPUPlace(), True)
         return np.array(new_ivar.value().get_tensor())
 
+    @dygraph_only
+    def set_value(self, value):
+        """
+        Set a new value for this Variable.
+
+        Args:
+            value (Variable|np.ndarray): the new value.
+
+        Returns:
+            None.
+
+        Examples:
+            .. code-block:: python
+
+                import paddle.fluid as fluid
+                from paddle.fluid.dygraph.base import to_variable
+                from paddle.fluid.dygraph import FC
+                import numpy as np
+
+                data = np.ones([3, 32, 32], dtype='float32')
+                with fluid.dygraph.guard():
+                    fc = fluid.dygraph.FC("fc", 4)
+                    t = to_variable(data)
+                    fc(t)  # call with default weight
+                    custom_weight = np.random.randn(1024, 4).astype("float32")
+                    fc.weight.set_value(custom_weight)  # change existing weight
+                    out = fc(t)  # call with different weight
+
+        """
+        assert isinstance(value, (Variable, np.ndarray))
+        if list(value.shape) != list(self.shape):
+            raise ValueError(
+                "The shape of the new value must be the same as that of the original Variable."
+            )
+        self_tensor = self._ivar.value().get_tensor()
+        if isinstance(value, Variable):
+            value = value._ivar.value().get_tensor().__array__()
+        self_tensor.set(value, _current_expected_place())
+
     @dygraph_only
     def backward(self, backward_strategy=None):
         """
@@ -1042,7 +1081,7 @@ class Variable(object):
             if self.shape[axis] < 0:
                 return self._cloneVar(True)
             index = int(item)
-            if (index > 0 and index >= self.shape[axis])\
+            if (index > 0 and index >= self.shape[axis]) \
                     or (index < 0 and (index + self.shape[axis]) < 0):
                 raise IndexError("invalid index")
             return self._sliceVar([axis], [index], [index + 1])
@@ -2662,10 +2701,10 @@ class IrOpNode(IrNode):
         if isinstance(val, Block):
             desc.set_block_attr(name, val.desc)
         elif isinstance(val, list) and val and \
-            all(isinstance(v, Block) for v in val):
+                all(isinstance(v, Block) for v in val):
             desc.set_blocks_attr(name, [v.desc for v in val])
         elif isinstance(val, core.BlockDesc) or \
-            isinstance(val, core.ProgramDesc):
+                isinstance(val, core.ProgramDesc):
             desc.set_serialized_attr(name, val.serialize_to_string())
         else:
             desc._set_attr(name, val)
@@ -2888,8 +2927,8 @@ class IrGraph(object):
             op_node(IrOpNode): the operator node that is needed to update input's link.
         """
         assert old_input_node.node in self.graph.nodes() and new_input_node.node in \
-        self.graph.nodes() and op_node.node in self.graph.nodes(), \
-        'The three arguments(old_input_node&new_input_node&op_node) must be in the graph nodes.'
+               self.graph.nodes() and op_node.node in self.graph.nodes(), \
+            'The three arguments(old_input_node&new_input_node&op_node) must be in the graph nodes.'
         old_input_node.remove_output(op_node)
         op_node.remove_input(old_input_node)
         new_input_node.append_output(op_node)
@@ -3024,7 +3063,7 @@ class IrGraph(object):
         def _convert_to_pdf(dot_file_path):
             pdf_save_path = os.path.splitext(dot_file_path)[0] + '.pdf'
             exited_code = subprocess.call('dot -Tpdf ' + dot_file_path \
-                            + ' -o ' + pdf_save_path, shell=True)
+                                          + ' -o ' + pdf_save_path, shell=True)
             if exited_code != 0:
                 print('The dot command is needed for creating pdf files.')
                 print('The {} is saved as the dot filetype.'.format(