diff --git a/python/paddle/fluid/dygraph/layer_object_helper.py b/python/paddle/fluid/dygraph/layer_object_helper.py
index 9fd1e392791f2bf7a19942749eae87001ec3ede8..f2e914a2137d0be0606556471696fd3d255b3c12 100644
--- a/python/paddle/fluid/dygraph/layer_object_helper.py
+++ b/python/paddle/fluid/dygraph/layer_object_helper.py
@@ -135,38 +135,6 @@ class LayerObjectHelper(LayerHelperBase):
                              (name, self.name))
         return param
 
-    def append_bias_op(self,
-                       input_var,
-                       dim_start=1,
-                       dim_end=None,
-                       bias_attr=None):
-        """Append bias operator and return its output. If the user does not set bias_attr, append_bias_op will return input_var
-
-            Args:
-                input_var: the input variable. The len(input_var.shape) is
-                larger or equal than 2.
-                dim_start:
-                dim_end: the shape of the bias will be
-                bias_attr: the bias_attr of it
-
-        Return the Variable of after append bias op
-        """
-        size = list(input_var.shape[dim_start:dim_end])
-        bias_attr = bias_attr
-        if not bias_attr:
-            return input_var
-
-        b = self.create_parameter(
-            attr=bias_attr, shape=size, dtype=input_var.dtype, is_bias=True)
-        tmp = self.create_variable_for_type_inference(dtype=input_var.dtype)
-        self.append_op(
-            type='elementwise_add',
-            inputs={'X': [input_var],
-                    'Y': [b]},
-            outputs={'Out': [tmp]},
-            attrs={'axis': dim_start})
-        return tmp
-
     # TODO: this should not be called anymore after all activation func move to Layers
     def append_activation(self,
                           input_var,
diff --git a/python/paddle/fluid/dygraph_utils.py b/python/paddle/fluid/dygraph_utils.py
index 544cadcf70f19b1e98fab14cf065f5f06bbf4f53..7b559494e6c3b779983e54f5f9675170ef985f63 100644
--- a/python/paddle/fluid/dygraph_utils.py
+++ b/python/paddle/fluid/dygraph_utils.py
@@ -31,7 +31,7 @@ def _append_activation_in_dygraph(input,
 
     Return the Variable after append activation
     """
-    if not act:
+    if act is None:
         return input
 
     attrs = ()
diff --git a/python/paddle/fluid/layers/detection.py b/python/paddle/fluid/layers/detection.py
index e0725242b7b28f92a9d788a17ec2fe84fcdacc83..e1034cc4c27451d4138e96b08005fe8e3e949169 100644
--- a/python/paddle/fluid/layers/detection.py
+++ b/python/paddle/fluid/layers/detection.py
@@ -993,7 +993,7 @@ def yolov3_loss(x,
         "GTBox": gt_box,
         "GTLabel": gt_label,
     }
-    if gt_score:
+    if gt_score is not None:
         inputs["GTScore"] = gt_score
 
     attrs = {
@@ -1159,15 +1159,16 @@ def detection_map(detect_res,
         return helper.create_variable_for_type_inference(dtype=type)
 
     map_out = __create_var('float32')
-    accum_pos_count_out = out_states[0] if out_states else __create_var('int32')
-    accum_true_pos_out = out_states[1] if out_states else __create_var(
-        'float32')
-    accum_false_pos_out = out_states[2] if out_states else __create_var(
-        'float32')
+    accum_pos_count_out = out_states[
+        0] if out_states is not None else __create_var('int32')
+    accum_true_pos_out = out_states[
+        1] if out_states is not None else __create_var('float32')
+    accum_false_pos_out = out_states[
+        2] if out_states is not None else __create_var('float32')
 
-    pos_count = input_states[0] if input_states else None
-    true_pos = input_states[1] if input_states else None
-    false_pos = input_states[2] if input_states else None
+    pos_count = input_states[0] if input_states is not None else None
+    true_pos = input_states[1] if input_states is not None else None
+    false_pos = input_states[2] if input_states is not None else None
 
     helper.append_op(
         type="detection_map",
@@ -2159,17 +2160,17 @@ def multi_box_head(inputs,
             aspect_ratios, num_layer,
             'aspect_ratios should be list or tuple, and the length of inputs '
             'and aspect_ratios should be the same.')
-    if step_h:
+    if step_h is not None:
         _is_list_or_tuple_and_equal(
             step_h, num_layer,
             'step_h should be list or tuple, and the length of inputs and '
             'step_h should be the same.')
-    if step_w:
+    if step_w is not None:
         _is_list_or_tuple_and_equal(
             step_w, num_layer,
             'step_w should be list or tuple, and the length of inputs and '
             'step_w should be the same.')
-    if steps:
+    if steps is not None:
         _is_list_or_tuple_and_equal(
             steps, num_layer,
             'steps should be list or tuple, and the length of inputs and '
@@ -2195,7 +2196,10 @@ def multi_box_head(inputs,
             aspect_ratio = aspect_ratios[i]
             if not _is_list_or_tuple_(aspect_ratio):
                 aspect_ratio = [aspect_ratio]
-        step = [step_w[i] if step_w else 0.0, step_h[i] if step_w else 0.0]
+        step = [
+            step_w[i] if step_w is not None else 0.0, step_h[i]
+            if step_w is not None else 0.0
+        ]
 
         box, var = prior_box(input, image, min_size, max_size, aspect_ratio,
                              variance, flip, clip, step, offset, None,