delete fluid

ppocr/modeling/heads/rec_ctc_head.py

@@ -24,7 +24,7 @@ from paddle.nn import functional as F
 
 
 def get_para_bias_attr(l2_decay, k, name):
-    regularizer = paddle.fluid.regularizer.L2Decay(l2_decay)
+    regularizer = paddle.regularizer.L2Decay(l2_decay)
     stdv = 1.0 / math.sqrt(k * 1.0)
     initializer = nn.initializer.Uniform(-stdv, stdv)
     weight_attr = ParamAttr(
@@ -33,6 +33,7 @@ def get_para_bias_attr(l2_decay, k, name):
         regularizer=regularizer, initializer=initializer, name=name + "_b_attr")
     return [weight_attr, bias_attr]
 
+
 class CTCHead(nn.Layer):
     def __init__(self, in_channels, out_channels, fc_decay=0.0004, **kwargs):
         super(CTCHead, self).__init__()

ppocr/optimizer/regularizer.py

@@ -17,7 +17,7 @@ from __future__ import division
 from __future__ import print_function
 from __future__ import unicode_literals
 
-from paddle import fluid
+import paddle
 
 
 class L1Decay(object):
@@ -32,8 +32,7 @@ class L1Decay(object):
         self.regularization_coeff = factor
 
     def __call__(self):
-        reg = fluid.regularizer.L1Decay(
-            regularization_coeff=self.regularization_coeff)
+        reg = paddle.regularizer.L1Decay(self.regularization_coeff)
         return reg
 
 
@@ -49,6 +48,5 @@ class L2Decay(object):
         self.regularization_coeff = factor
 
     def __call__(self):
-        reg = fluid.regularizer.L2Decay(
-            regularization_coeff=self.regularization_coeff)
+        reg = paddle.regularizer.L2Decay(self.regularization_coeff)
         return reg