Revert "fix mv3 to adapt to paddle2.0"

493027d3 · zhoujun · GitHub · 95ad4d10 · 493027d3 · 493027d3
Showing with 42 addition and 43 deletion

ppocr/modeling/backbones/det_mobilenet_v3.py ppocr/modeling/backbones/det_mobilenet_v3.py +23 -24

ppocr/modeling/backbones/rec_mobilenet_v3.py ppocr/modeling/backbones/rec_mobilenet_v3.py +19 -19

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--- a/ppocr/modeling/backbones/det_mobilenet_v3.py
+++ b/ppocr/modeling/backbones/det_mobilenet_v3.py
@@ -58,15 +58,15 @@ class MobileNetV3(nn.Layer):
                [5, 72, 40, True, 'relu', 2],
                [5, 120, 40, True, 'relu', 1],
                [5, 120, 40, True, 'relu', 1],
-                [3, 240, 80, False, 'hardswish', 2],
+                [3, 240, 80, False, 'hard_swish', 2],
-                [3, 200, 80, False, 'hardswish', 1],
+                [3, 200, 80, False, 'hard_swish', 1],
-                [3, 184, 80, False, 'hardswish', 1],
+                [3, 184, 80, False, 'hard_swish', 1],
-                [3, 184, 80, False, 'hardswish', 1],
+                [3, 184, 80, False, 'hard_swish', 1],
-                [3, 480, 112, True, 'hardswish', 1],
+                [3, 480, 112, True, 'hard_swish', 1],
-                [3, 672, 112, True, 'hardswish', 1],
+                [3, 672, 112, True, 'hard_swish', 1],
-                [5, 672, 160, True, 'hardswish', 2],
+                [5, 672, 160, True, 'hard_swish', 2],
-                [5, 960, 160, True, 'hardswish', 1],
+                [5, 960, 160, True, 'hard_swish', 1],
-                [5, 960, 160, True, 'hardswish', 1],
+                [5, 960, 160, True, 'hard_swish', 1],
            ]
            cls_ch_squeeze = 960
        elif model_name == "small":
@@ -75,14 +75,14 @@ class MobileNetV3(nn.Layer):
                [3, 16, 16, True, 'relu', 2],
                [3, 72, 24, False, 'relu', 2],
                [3, 88, 24, False, 'relu', 1],
-                [5, 96, 40, True, 'hardswish', 2],
+                [5, 96, 40, True, 'hard_swish', 2],
-                [5, 240, 40, True, 'hardswish', 1],
+                [5, 240, 40, True, 'hard_swish', 1],
-                [5, 240, 40, True, 'hardswish', 1],
+                [5, 240, 40, True, 'hard_swish', 1],
-                [5, 120, 48, True, 'hardswish', 1],
+                [5, 120, 48, True, 'hard_swish', 1],
-                [5, 144, 48, True, 'hardswish', 1],
+                [5, 144, 48, True, 'hard_swish', 1],
-                [5, 288, 96, True, 'hardswish', 2],
+                [5, 288, 96, True, 'hard_swish', 2],
-                [5, 576, 96, True, 'hardswish', 1],
+                [5, 576, 96, True, 'hard_swish', 1],
-                [5, 576, 96, True, 'hardswish', 1],
+                [5, 576, 96, True, 'hard_swish', 1],
            ]
            cls_ch_squeeze = 576
        else:
@@ -102,7 +102,7 @@ class MobileNetV3(nn.Layer):
            padding=1,
            groups=1,
            if_act=True,
-            act='hardswish',
+            act='hard_swish',
            name='conv1')
        self.stages = []
@@ -137,7 +137,7 @@ class MobileNetV3(nn.Layer):
                padding=0,
                groups=1,
                if_act=True,
-                act='hardswish',
+                act='hard_swish',
                name='conv_last'))
        self.stages.append(nn.Sequential(*block_list))
        self.out_channels.append(make_divisible(scale * cls_ch_squeeze))
@@ -191,11 +191,10 @@ class ConvBNLayer(nn.Layer):
        if self.if_act:
            if self.act == "relu":
                x = F.relu(x)
-            elif self.act == "hardswish":
+            elif self.act == "hard_swish":
-                x = F.hardswish(x)
+                x = F.activation.hard_swish(x)
            else:
-                print("The activation function({}) is selected incorrectly.".
+                print("The activation function is selected incorrectly.")
-                      format(self.act))
                exit()
        return x
@@ -282,5 +281,5 @@ class SEModule(nn.Layer):
        outputs = self.conv1(outputs)
        outputs = F.relu(outputs)
        outputs = self.conv2(outputs)
-        outputs = F.hardsigmoid(outputs, slope=0.2, offset=0.5)
+        outputs = F.activation.hard_sigmoid(outputs)
        return inputs * outputs
--- a/ppocr/modeling/backbones/rec_mobilenet_v3.py
+++ b/ppocr/modeling/backbones/rec_mobilenet_v3.py
@@ -51,15 +51,15 @@ class MobileNetV3(nn.Layer):
                [5, 72, 40, True, 'relu', (large_stride[2], 1)],
                [5, 120, 40, True, 'relu', 1],
                [5, 120, 40, True, 'relu', 1],
-                [3, 240, 80, False, 'hardswish', 1],
+                [3, 240, 80, False, 'hard_swish', 1],
-                [3, 200, 80, False, 'hardswish', 1],
+                [3, 200, 80, False, 'hard_swish', 1],
-                [3, 184, 80, False, 'hardswish', 1],
+                [3, 184, 80, False, 'hard_swish', 1],
-                [3, 184, 80, False, 'hardswish', 1],
+                [3, 184, 80, False, 'hard_swish', 1],
-                [3, 480, 112, True, 'hardswish', 1],
+                [3, 480, 112, True, 'hard_swish', 1],
-                [3, 672, 112, True, 'hardswish', 1],
+                [3, 672, 112, True, 'hard_swish', 1],
-                [5, 672, 160, True, 'hardswish', (large_stride[3], 1)],
+                [5, 672, 160, True, 'hard_swish', (large_stride[3], 1)],
-                [5, 960, 160, True, 'hardswish', 1],
+                [5, 960, 160, True, 'hard_swish', 1],
-                [5, 960, 160, True, 'hardswish', 1],
+                [5, 960, 160, True, 'hard_swish', 1],
            ]
            cls_ch_squeeze = 960
        elif model_name == "small":
@@ -68,14 +68,14 @@ class MobileNetV3(nn.Layer):
                [3, 16, 16, True, 'relu', (small_stride[0], 1)],
                [3, 72, 24, False, 'relu', (small_stride[1], 1)],
                [3, 88, 24, False, 'relu', 1],
-                [5, 96, 40, True, 'hardswish', (small_stride[2], 1)],
+                [5, 96, 40, True, 'hard_swish', (small_stride[2], 1)],
-                [5, 240, 40, True, 'hardswish', 1],
+                [5, 240, 40, True, 'hard_swish', 1],
-                [5, 240, 40, True, 'hardswish', 1],
+                [5, 240, 40, True, 'hard_swish', 1],
-                [5, 120, 48, True, 'hardswish', 1],
+                [5, 120, 48, True, 'hard_swish', 1],
-                [5, 144, 48, True, 'hardswish', 1],
+                [5, 144, 48, True, 'hard_swish', 1],
-                [5, 288, 96, True, 'hardswish', (small_stride[3], 1)],
+                [5, 288, 96, True, 'hard_swish', (small_stride[3], 1)],
-                [5, 576, 96, True, 'hardswish', 1],
+                [5, 576, 96, True, 'hard_swish', 1],
-                [5, 576, 96, True, 'hardswish', 1],
+                [5, 576, 96, True, 'hard_swish', 1],
            ]
            cls_ch_squeeze = 576
        else:
@@ -96,7 +96,7 @@ class MobileNetV3(nn.Layer):
            padding=1,
            groups=1,
            if_act=True,
-            act='hardswish',
+            act='hard_swish',
            name='conv1')
        i = 0
        block_list = []
@@ -124,7 +124,7 @@ class MobileNetV3(nn.Layer):
            padding=0,
            groups=1,
            if_act=True,
-            act='hardswish',
+            act='hard_swish',
            name='conv_last')
        self.pool = nn.MaxPool2D(kernel_size=2, stride=2, padding=0)