diff --git a/model/attention/SEAttention.py b/model/attention/SEAttention.py
deleted file mode 100644
index 4aa8b7b..0000000
--- a/model/attention/SEAttention.py
+++ /dev/null
@@ -1,32 +0,0 @@
-"""
-MindSpore implementation of 'SEAttention'
-Refer to "Squeeze-and-Excitation Networks"
-"""
-import mindspore as ms
-from mindspore import nn
-
-
-class SEAttention(nn.Cell):
-    """ SEAttention """
-    def __init__(self, channels=512, reduction=16):
-        super().__init__()
-        self.avg_pool = nn.AdaptiveAvgPool2d(1)
-        self.fc = nn.SequentialCell(
-            nn.Dense(channels, channels // reduction, has_bias=False),
-            nn.ReLU(),
-            nn.Dense(channels // reduction, channels, has_bias=False),
-            nn.Sigmoid()
-        )
-
-    def construct(self, x):
-        B, C, _, _ = x.shape
-        y = self.avg_pool(x).view(B, C)
-        y = self.fc(y).view(B, C, 1, 1)
-        return x * y.expand_as(x)
-
-
-if __name__ == '__main__':
-    dummy_input = ms.ops.randn(50, 512, 7, 7)
-    se = SEAttention(channels=512, reduction=8)
-    output = se(dummy_input)
-    print(output.shape)