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from model.conv.MBConv import MBConvBlock
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import torch
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from torch import nn
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from torch.nn import functional as F
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input=torch.randn(1,3,224,224)
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mbconv=MBConvBlock(ksize=3,input_filters=3,output_filters=512,image_size=224)
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out=mbconv(input)
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print(out.shape)
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