[Yaml] Modify api and add unittests for full api final state.

python/paddle/fluid/dygraph/layers.py

@@ -540,9 +540,8 @@ def parameters(self, include_sublayers=True):
 
         """
         ret = [
-            param
-            for _, param in self.named_parameters(
-                include_sublayers=include_sublayers)
+            param for _, param in
+            self.named_parameters(include_sublayers=include_sublayers)
         ]
         return ret
 
@@ -798,9 +797,8 @@ def buffers(self, include_sublayers=True):
 
         """
         ret = [
-            buffer
-            for _, buffer in self.named_buffers(
-                include_sublayers=include_sublayers)
+            buffer for _, buffer in
+            self.named_buffers(include_sublayers=include_sublayers)
         ]
         return ret
 
@@ -1170,6 +1168,9 @@ def _remove_if_exist(*dicts):
                     if name not in self._buffers:
                         self._non_persistable_buffer_names_set.add(name)
                     _buffers[name] = value
+                    if not _buffers[name].name:
+                        _buffers[name].name = unique_name.generate(
+                            '_generated_var')
                 elif _buffers is not None and name in _buffers:
                     # Note(Aurelius84): In Dy2stat, the value of the Buffer may be modified in
                     # decorated function, such as `self.buffer = new_tensor`. So we update its

python/paddle/fluid/layers/tensor.py

@@ -21,7 +21,7 @@
 from ..layer_helper import LayerHelper
 from ..param_attr import ParamAttr
 from ..initializer import Initializer
-from ..framework import _current_expected_place, convert_np_dtype_to_dtype_, _non_static_mode, _varbase_creator, device_guard, _in_legacy_dygraph, in_dygraph_mode
+from ..framework import _current_expected_place, convert_np_dtype_to_dtype_, _non_static_mode, _varbase_creator, device_guard, _in_legacy_dygraph, in_dygraph_mode, _get_paddle_place
 from ..framework import Variable
 from ..initializer import Constant
 from ..core import VarDesc
@@ -751,22 +751,36 @@ def fill_constant(shape, dtype, value, force_cpu=False, out=None, name=None):
             attrs['value'] = float(value)
 
     if _non_static_mode():
-        shape = utils.convert_shape_to_list(shape)
-        if out is None:
-            out = _varbase_creator(dtype=dtype)
-
-        if isinstance(value, Variable):
-            if dtype in ['uint8', 'int16', 'int32', 'int64']:
-                attrs['str_value'] = str(int(value.numpy().item(0)))
-            else:
-                attrs['str_value'] = str(float(value.numpy().item(0)))
-
-        _C_ops.fill_constant(out, 'value',
-                             float(value), 'force_cpu', force_cpu, 'dtype',
-                             out.dtype, 'str_value', attrs['str_value'],
-                             'shape', shape)
-        out.stop_gradient = True
-        return out
+        if out is None and in_dygraph_mode():
+            #Currently, final state mode don't support out is None.
+            place = _current_expected_place()
+            if force_cpu:
+                place = core.CPUPlace()
+
+            shape = utils.convert_shape_to_list(shape)
+            if not isinstance(dtype, core.VarDesc.VarType):
+                dtype = convert_np_dtype_to_dtype_(dtype)
+            out = _C_ops.final_state_full(shape, float(value), dtype, place)
+            out.stop_gradient = True
+            return out
+
+        else:
+            shape = utils.convert_shape_to_list(shape)
+            if out is None:
+                out = _varbase_creator(dtype=dtype)
+
+            if isinstance(value, Variable):
+                if dtype in ['uint8', 'int16', 'int32', 'int64']:
+                    attrs['str_value'] = str(int(value.numpy().item(0)))
+                else:
+                    attrs['str_value'] = str(float(value.numpy().item(0)))
+
+            _C_ops.fill_constant(out, 'value',
+                                 float(value), 'force_cpu', force_cpu, 'dtype',
+                                 out.dtype, 'str_value', attrs['str_value'],
+                                 'shape', shape)
+            out.stop_gradient = True
+            return out
 
     helper = LayerHelper("fill_constant", **locals())
     inputs = {}

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

@@ -23,6 +23,7 @@
 import paddle.fluid as fluid
 import paddle
 from paddle.fluid import compiler, Program, program_guard
+from paddle.fluid.framework import _test_eager_guard
 
 
 # Test python API
@@ -75,6 +76,61 @@ def test_api(self):
         assert np.array_equal(res_6, np.full([1, 2], 1.1, dtype="float32"))
         assert np.array_equal(res_7, np.full([1, 2], 1.1, dtype="float32"))
 
+    def test_api_eager(self):
+        with fluid.dygraph.base.guard():
+            with _test_eager_guard():
+                positive_2_int32 = fluid.layers.fill_constant([1], "int32", 2)
+
+                positive_2_int64 = fluid.layers.fill_constant([1], "int64", 2)
+                out_1 = paddle.full(
+                    shape=[1, 2], dtype="float32", fill_value=1.1)
+
+                out_2 = paddle.full(
+                    shape=[1, positive_2_int32.item()],
+                    dtype="float32",
+                    fill_value=1.1)
+
+                out_3 = paddle.full(
+                    shape=[1, positive_2_int64.item()],
+                    dtype="float32",
+                    fill_value=1.1)
+
+                out_4 = paddle.full(
+                    shape=[1, 2], dtype="float32", fill_value=1.2)
+
+                out_5 = paddle.full(
+                    shape=[1, 2], dtype="float32", fill_value=1.1)
+
+                out_6 = paddle.full(
+                    shape=[1, 2], dtype=np.float32, fill_value=1.1)
+
+                val = fluid.layers.fill_constant(
+                    shape=[1], dtype=np.float32, value=1.1)
+                out_7 = paddle.full(
+                    shape=[1, 2], dtype=np.float32, fill_value=val)
+
+                assert np.array_equal(
+                    out_1, np.full(
+                        [1, 2], 1.1, dtype="float32"))
+                assert np.array_equal(
+                    out_2, np.full(
+                        [1, 2], 1.1, dtype="float32"))
+                assert np.array_equal(
+                    out_3, np.full(
+                        [1, 2], 1.1, dtype="float32"))
+                assert np.array_equal(
+                    out_4, np.full(
+                        [1, 2], 1.2, dtype="float32"))
+                assert np.array_equal(
+                    out_5, np.full(
+                        [1, 2], 1.1, dtype="float32"))
+                assert np.array_equal(
+                    out_6, np.full(
+                        [1, 2], 1.1, dtype="float32"))
+                assert np.array_equal(
+                    out_7, np.full(
+                        [1, 2], 1.1, dtype="float32"))
+
 
 class TestFullOpError(unittest.TestCase):
     def test_errors(self):