limingjuan
2 years ago
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model/attention/ECAAttention.py
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| """ | |||||
| MindSpore implementation of 'ECAAttention' | |||||
| Refer to "ECA-Net: Efficient Channel Attention for Deep Convolutional Neural Networks" | |||||
| """ | |||||
| import mindspore as ms | |||||
| from mindspore import nn | |||||
| class ECAAttention(nn.Cell): | |||||
| """ ECA Attention """ | |||||
| def __init__(self, kernel_size=3): | |||||
| super().__init__() | |||||
| self.gap = nn.AdaptiveAvgPool2d(1) | |||||
| self.conv = nn.Conv1d(1, 1, kernel_size=kernel_size, pad_mode='pad', padding=(kernel_size - 1) // 2) | |||||
| self.sigmoid = nn.Sigmoid() | |||||
| def construct(self, x): | |||||
| y = self.gap(x) | |||||
| y = y.squeeze(-1).permute(0, 2, 1) | |||||
| y = self.conv(y) | |||||
| y = self.sigmoid(y) | |||||
| y = y.permute(0, 2, 1).unsqueeze(-1) | |||||
| return x * y.expand_as(x) | |||||
| if __name__ == "__main__": | |||||
| dummy_input = ms.ops.randn(50, 512, 7, 7) | |||||
| eca = ECAAttention() | |||||
| output = eca(dummy_input) | |||||
| print(output.shape) | |||||