如何使用pycaffe編寫帶有內存數據層的網絡？

Question

是可能的寫在pycaffe一個CAFFE prototxt與來自如下的HDF5數據層：

import caffe 
from caffe import layers as L 

def logreg(hdf5, batch_size): 
    n = caffe.NetSpec() 
    n.data, n.label = L.HDF5Data(batch_size = batch_size, source = hdf5, ntop = 2) 
    n.ip1 = L.InnerProduct(n.data, num_output = 2, weight_filler = dict(type='xavier')) 
    n.accuracy = L.Accuracy(n.ip1, n.label) 
    n.loss = L.SoftmaxWithLoss(n.ip1, n.label) 
    return n.to_proto() 

with open('models/logreg_auto_train.prototxt', 'w') as f: 
    f.write(str(logreg('data/train.txt', chunck_size))) 

是否有可能使用類似的方法來編寫具有存儲器數據層a prototxt？

Answer 1

嘗試是這樣的：

import caffe 
from caffe import layers as L 

def logreg(height, width, channels, batch_size): 
    n = caffe.NetSpec() 
    n.data = L.MemoryData(batch_size = batch_size, height = height, width = width, channels = channels) 
    n.ip1 = L.InnerProduct(n.data, num_output = 2, weight_filler = dict(type='xavier')) 
    return n.to_proto() 

with open('models/logreg_memdata.prototxt', 'w') as f: 
    f.write(str(logreg(128,128,3, chunck_size)))