From 59d4eef6dadf47b7405765200c44aaa9f2b3aa5a Mon Sep 17 00:00:00 2001
From: Guanghua Yu <742925032@qq.com>
Date: Wed, 13 Jan 2021 21:45:33 +0800
Subject: [PATCH] fix framework warning (#2059)

---
 ppdet/modeling/backbones/fpn.py          | 3 +--
 ppdet/modeling/backbones/mobilenet_v3.py | 2 +-
 ppdet/modeling/ops.py                    | 3 ++-
 3 files changed, 4 insertions(+), 4 deletions(-)

diff --git a/ppdet/modeling/backbones/fpn.py b/ppdet/modeling/backbones/fpn.py
index f09e8f8f8..baefd4019 100644
--- a/ppdet/modeling/backbones/fpn.py
+++ b/ppdet/modeling/backbones/fpn.py
@@ -18,7 +18,6 @@ from __future__ import print_function
 
 from collections import OrderedDict
 import copy
-import paddle
 from paddle import fluid
 from paddle.fluid.param_attr import ParamAttr
 from paddle.fluid.initializer import Xavier
@@ -106,7 +105,7 @@ class FPN(object):
                 out_shape=[body_input.shape[2], body_input.shape[3]],
                 name=topdown_name)
 
-        return paddle.add(lateral, topdown)
+        return fluid.layers.elementwise_add(lateral, topdown)
 
     def get_output(self, body_dict):
         """
diff --git a/ppdet/modeling/backbones/mobilenet_v3.py b/ppdet/modeling/backbones/mobilenet_v3.py
index d4727449a..96c425fd6 100644
--- a/ppdet/modeling/backbones/mobilenet_v3.py
+++ b/ppdet/modeling/backbones/mobilenet_v3.py
@@ -225,7 +225,7 @@ class MobileNetV3(object):
         return out
 
     def _hard_swish(self, x):
-        return x * fluid.layers.relu6(x + 3) / 6.
+        return fluid.layers.elementwise_mul(x, fluid.layers.relu6(x + 3) / 6.)
 
     def _se_block(self, input, num_out_filter, ratio=4, name=None):
         lr_idx = self.curr_stage // 3
diff --git a/ppdet/modeling/ops.py b/ppdet/modeling/ops.py
index 00a611348..86cd9d5cc 100644
--- a/ppdet/modeling/ops.py
+++ b/ppdet/modeling/ops.py
@@ -325,7 +325,8 @@ def DropBlock(input, block_size, keep_prob, is_test):
     elem_sum_m = fluid.layers.cast(elem_sum, dtype="float32")
     elem_sum_m.stop_gradient = True
 
-    output = input * mask * elem_numel_m / elem_sum_m
+    output = fluid.layers.elementwise_mul(input,
+                                          mask) * elem_numel_m / elem_sum_m
     return output
 
 
-- 
GitLab