[ Dy2Static ] convert_call support staticmethod for class. (#44983)

* convert_call support staticmethod for class.

* while support for python container.
It is convenient to convert more dynamic graph codes into static graphs.

* cond support python container

* add unittest for staticmethod convert_call

* fix bugs

* add unittest for item interface

* fix bugs

* change to np.testing.assert_allclose

* code format

* fix comments.

* code format

python/paddle/fluid/dygraph/dygraph_to_static/ast_transformer.py

@@ -123,7 +123,10 @@ def visit_FunctionDef(self, node):
         # Remove the decorated name of dygraph_to_static
         if hasattr(node, 'decorator_list'):
             decorator_list = []
+            ignore_list = ["staticmethod"]
             for d in node.decorator_list:
+                if isinstance(d, gast.Name) and d.id in ignore_list:
+                    continue
                 if isinstance(d, gast.Name) and d.id not in DECORATOR_NAMES:
                     raise NotImplementedError(
                         "ProgramTranslator hasn't implemented multiple decorators. Please remove "

python/paddle/fluid/dygraph/dygraph_to_static/convert_call_func.py

@@ -213,6 +213,11 @@ def dyfunc(x):
                 elif isinstance(fn, StaticFunction):
                     _, fn = unwrap_decorators(fn)
                     global_functions.add(fn)
+                elif inspect.isclass(fn):
+                    if isinstance(fn.__dict__.get(func.__name__, None),
+                                  staticmethod):
+                        global_functions.add(
+                            func)  # Add func to ensure that we will convert
 
             if func in global_functions:
                 converted_call = convert_to_static(func)

python/paddle/fluid/dygraph/dygraph_to_static/convert_operators.py

@@ -87,7 +87,10 @@ def convert_while_loop(cond,
     Args:
         cond(Callable): A callable object that returns a boolean variable to control whether to execute the loop body. It takes ``loop_vars`` as arguments.
         body(Callable): A callable object that returns a tuple or list of variables with the same arguments ``loops_vars`` as ``cond`` .
-        loop_vars(list|tuple): A list or tuple of variables passed to ``cond`` and ``body`` .
+        get_args(callable): Get all arguments that needed in true_fn and false_fn.
+        set_args(callable): Update arguments that modified in trure_fn and false_fn.
+        return_name_ids(list[string], optional): the returned names.
+        push_pop_names(list[string], optional): the names on which called .append() or .pop().
 
     Returns:
         A list or tuple of variables which returned by ``body``.
@@ -306,7 +309,8 @@ def convert_ifelse(pred,
         false_fn(callable): A callable to be performed if ``pred`` is false.
         get_args(callable): Get all arguments that needed in true_fn and false_fn.
         set_args(callable): Update arguments that modified in trure_fn and false_fn.
-        return_name_ids(list[string]): the returned names.
+        return_name_ids(list[string], optional): the returned names.
+        push_pop_names(list[string], optional): the names on which called .append() or .pop().
 
     Returns:
         ``true_fn()`` if the predicate ``pred`` is true else ``false_fn()`` .

python/paddle/fluid/dygraph/dygraph_to_static/program_translator.py

@@ -380,7 +380,6 @@ def __call__(self, *args, **kwargs):
         try:
             concrete_program, partial_program_layer = self.get_concrete_program(
                 *args, **kwargs, is_train=self._is_train_mode())
-
             # 3. synchronize self.training attribute.
             if isinstance(self._class_instance, layers.Layer):
                 partial_program_layer.training = self._class_instance.training

python/paddle/fluid/layers/math_op_patch.py

@@ -227,12 +227,30 @@ def append(self, var):
                 .format(self.type))
         array_write(x=var, i=array_length(self), array=self)
 
+    @static_only
+    def _item(self):
+        """ 
+        In order to be compatible with the item interface introduced by the dynamic graph, it does nothing but returns self. 
+        It will check that the shape must be a 1-D tensor
+        """
+        if len(self.shape) > 1:
+            raise TypeError(
+                "Required input var should be 1-D Variable, but received {}".
+                format(self.shape))
+        return self
+
     @static_only
     def pop(self, *args):
         """
-         **Notes**:
-            **The type variable must be LoD Tensor Array.
-        
+        The type variable must be LoD Tensor Array.
+        When self is LoDTensorArray, calling pop is similar to Python's pop on list. 
+        This interface is used to simplify dygraph to static graph operations.
+
+        Args:
+            self(Variable): The source variable, which must be LOD_TENSOR_ARRAY
+            *args: optional, a int means index.
+        Returns:
+            Variable: self[index]
         """
         from paddle.fluid.dygraph.dygraph_to_static.convert_operators import _run_paddle_pop
         if self.type != core.VarDesc.VarType.LOD_TENSOR_ARRAY:
@@ -410,6 +428,7 @@ def __impl__(self, other_var):
         ('cpu', cpu),
         ('cuda', cuda),
         ('append', append),
+        ('item', _item),
         ('pop', pop),
         ('dim', lambda x: len(x.shape)),
         ('ndimension', lambda x: len(x.shape)),

python/paddle/fluid/tests/unittests/dygraph_to_static/test_convert_call.py

@@ -65,6 +65,23 @@ def dyfunc_with_third_library_logging(x_v):
     return x_v
 
 
+class A:
+
+    @staticmethod
+    def add(a, b):
+        """
+        dygraph mode, return a numpy object.
+        static mode, return a variable object.
+        """
+        return paddle.to_tensor(a.numpy() + b.numpy())
+
+
+@paddle.jit.to_static
+def dyfunc_with_staticmethod(x_v):
+    a = A()
+    return a.add(x_v, x_v)
+
+
 class TestRecursiveCall1(unittest.TestCase):
 
     def setUp(self):
@@ -188,6 +205,12 @@ def set_func(self):
         self.dygraph_func = dyfunc_with_third_library_logging
 
 
+class TestStaticMethod(TestRecursiveCall2):
+
+    def set_func(self):
+        self.dygraph_func = dyfunc_with_staticmethod
+
+
 # Situation 2 : test not_to_static
 
 

python/paddle/fluid/tests/unittests/dygraph_to_static/test_tensor_methods.py

@@ -62,6 +62,29 @@ def test_to_static_numpy_report_error(self):
             static_res = self._run(to_static=True)
 
 
+@paddle.jit.to_static
+def tensor_item(x):
+    x = paddle.to_tensor(x)
+    y = x.clone()
+    return y.item()
+
+
+class TestTensorItem(unittest.TestCase):
+
+    def _run(self, to_static):
+        prog_trans = paddle.jit.ProgramTranslator()
+        prog_trans.enable(to_static)
+        x = paddle.ones([1])
+        if to_static:
+            return tensor_item(x).numpy()
+        return tensor_item(x)
+
+    def test_tensor_clone(self):
+        dygraph_res = self._run(to_static=False)
+        static_res = self._run(to_static=True)
+        np.testing.assert_allclose(dygraph_res, static_res)
+
+
 @paddle.jit.to_static
 def tensor_size(x):
     x = paddle.to_tensor(x)