output = model( data )[ 0 ] # shape: (100, 321, 481)
output = output.permute(1, 2, 0) # 维度置换 shape: (321, 481, 100)
output = output.contiguous().view(-1, args.nChannel) # (321x481, 100)
view原矩阵变换到其他大小,需要原矩阵tensor的内存是整块的
view之前为何先用函数contiguous()
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转载自blog.csdn.net/jizhidexiaoming/article/details/82454432
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