From 6181003b0c6163b6817728eeeac4426866e19680 Mon Sep 17 00:00:00 2001
From: Bai Yifan <me@ethanbai.com>
Date: Fri, 22 Jan 2021 22:18:18 +0800
Subject: [PATCH] [Cherry-pick]fix hardsigmoid/hardswish (#608)
---
demo/dygraph/quant/mobilenet_v3.py | 6 +++---
1 file changed, 3 insertions(+), 3 deletions(-)
diff --git a/demo/dygraph/quant/mobilenet_v3.py b/demo/dygraph/quant/mobilenet_v3.py
index e56c8990..f9e69962 100644
--- a/demo/dygraph/quant/mobilenet_v3.py
+++ b/demo/dygraph/quant/mobilenet_v3.py
@@ -21,7 +21,6 @@ import paddle
from paddle import ParamAttr
import paddle.nn as nn
import paddle.nn.functional as F
-from paddle.nn.functional.activation import hard_sigmoid, hard_swish
from paddle.nn import Conv2D, BatchNorm, Linear, Dropout
from paddle.nn import AdaptiveAvgPool2D, MaxPool2D, AvgPool2D
from paddle.regularizer import L2Decay
@@ -165,7 +164,7 @@ class MobileNetV3(nn.Layer):
x = self.pool(x)
x = self.last_conv(x)
- x = hard_swish(x)
+ x = paddle.nn.functional.activation.hardswish(x)
x = paddle.reshape(x, shape=[x.shape[0], x.shape[1]])
x = self.out(x)
@@ -303,7 +302,8 @@ class SEModule(nn.Layer):
outputs = self.conv1(outputs)
outputs = F.relu(outputs)
outputs = self.conv2(outputs)
- outputs = hard_sigmoid(outputs)
+ outputs = paddle.nn.functional.activation.hardsigmoid(
+ outputs, slope=0.2)
return paddle.multiply(x=inputs, y=outputs)
--
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