remove useless and fluid import.

paddlespeech/s2t/training/optimizer/adadelta.py

@@ -11,18 +11,7 @@
 # WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
 # See the License for the specific language governing permissions and
 # limitations under the License.
-from collections import defaultdict
-
 import paddle
-from paddle import _C_ops
-from paddle import _legacy_C_ops
-from paddle.fluid import core
-from paddle.fluid import framework
-from paddle.fluid.dygraph import base as imperative_base
-from paddle.fluid.dygraph import no_grad
-from paddle.fluid.framework import name_scope
-from paddle.fluid.framework import Variable
-from paddle.framework import in_dygraph_mode
 from paddle.optimizer import Optimizer
 
 __all__ = []
@@ -120,8 +109,7 @@ class SimpleAdadelta(Optimizer):
         self.square_avgs = []
         self.acc_deltas = []
 
-    @imperative_base.no_grad
+    @paddle.no_grad()
-    @framework.dygraph_only
     def step(self):
         """Performs a single optimization step.
 
@@ -173,19 +161,16 @@ class SimpleAdadelta(Optimizer):
             maximize=self._maximize)
 
 
-def adadelta(
+def adadelta(params_grads,
-        params_grads,
+             square_avgs,
-        square_avgs,
+             acc_deltas,
-        acc_deltas,
+             foreach=None,
-        # kwonly args with defaults are not supported by functions compiled with torchscript issue #70627
+             *,
-        # setting this as kwarg for now as functional API is compiled by torch/distributed/optim
+             learning_rate: float,
-        foreach=None,
+             rho: float,
-        *,
+             epsilon: float,
-        learning_rate: float,
+             weight_decay: float,
-        rho: float,
+             maximize: bool):
-        epsilon: float,
-        weight_decay: float,
-        maximize: bool):
 
     if foreach is None:
         # if foreach is None, set False