1 |
Conv2DLayer(l_in, num_filters = 64, filter_size = (9, 9),stride = 1, pad = 'same',nonlinearity = lasagne.nonlinearities.rectify,W = lasagne.init.GlorotNormal('relu')) |
pad为填充方式，共3种，
- same：卷积后的输出大小与输入相同
- full：卷积后的输出大小略大于输入
- valid：卷积后的输出大小略小与输入
1 |
Conv2DLayer(l_in, num_filters = 64, filter_size = (9, 9),stride = 1, pad = 'same',nonlinearity = lasagne.nonlinearities.rectify,W = lasagne.init.GlorotNormal('relu')) |
pad为填充方式，共3种，
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