32 lines
1.3 KiB
Python
32 lines
1.3 KiB
Python
#--------------------------------------------#
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# 该部分代码用于看网络结构
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#--------------------------------------------#
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import torch
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from thop import clever_format, profile
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from torchsummary import summary
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from nets.yolo import YoloBody
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if __name__ == "__main__":
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input_shape = [640, 640]
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num_classes = 80
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phi = 'l'
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# 需要使用device来指定网络在GPU还是CPU运行
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device = torch.device('cuda' if torch.cuda.is_available() else 'cpu')
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m = YoloBody(num_classes, phi).to(device)
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summary(m, (3, input_shape[0], input_shape[1]))
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dummy_input = torch.randn(1, 3, input_shape[0], input_shape[1]).to(device)
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flops, params = profile(m.to(device), (dummy_input, ), verbose=False)
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#--------------------------------------------------------#
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# flops * 2是因为profile没有将卷积作为两个operations
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# 有些论文将卷积算乘法、加法两个operations。此时乘2
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# 有些论文只考虑乘法的运算次数，忽略加法。此时不乘2
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# 本代码选择乘2，参考YOLOX。
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#--------------------------------------------------------#
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flops = flops * 2
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flops, params = clever_format([flops, params], "%.3f")
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print('Total GFLOPS: %s' % (flops))
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print('Total params: %s' % (params))
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