如何打印来自model.fit MXNet的处理步骤/报告Python

我想使用MXNet深度学习库来训练我的20x20图像数据集，您可以看到下面的代码：问题是当我运行它时，虽然它未显示任何错误，它返回什么，我的意思是它不显示像任何处理：如何打印来自model.fit MXNet的处理步骤/报告Python

划时代0：........精度：.....

划时代1：.... ....精度：.....

那么，我该如何让它打印这样的处理格式，或者哪里可能会出现问题呢？注：我试过各种回调API：http://mxnet.io/api/python/callback.html?fref=gc，他们都没有给出任何回应;代码工作没有错误，但没有显示处理步骤！

在此先感谢

X_train = [] 
training_flatten_rows_mxnet_csv=np.loadtxt("training_set_flatten_rows_mxnet.csv", delimiter=",") 
train_data = training_flatten_rows_mxnet_csv 
X_train = train_data.reshape((training_counter,1,20,20)) 
Y_train = np.loadtxt("training_labels.csv", delimiter=",") 

X_validate = [] 
validate_flatten_rows_mxnet_csv=np.loadtxt("validation_set_flatten_rows_mxnet.csv", delimiter=",") 
validate_data = validate_flatten_rows_mxnet_csv 
X_validate = validate_data.reshape((validate_counter,1,20,20)) 
Y_validate = np.loadtxt("validate_labels.csv", delimiter=",") 

train_iterator = mx.io.NDArrayIter(X_train, Y_train, batch_size=batch_size,shuffle=True)#,last_batch_handle='discard') 
validate_iterator = mx.io.NDArrayIter(X_validate, Y_validate, batch_size=batch_size,shuffle=True) 

data = mx.sym.var('data') 

conv1 = mx.sym.Convolution(data=data, kernel=(3,3), num_filter=6) 
relu1 = mx.sym.Activation(data=conv1, act_type="relu") 
pool1 = mx.sym.Pooling(data=relu1, pool_type="max", kernel=(2,2), stride=(2,2)) 

conv2 = mx.sym.Convolution(data=pool1, kernel=(6,6), num_filter=12) 
relu2 = mx.sym.Activation(data=conv2, act_type="relu") 
pool2 = mx.sym.Pooling(data=relu2, pool_type="max", kernel=(2,2), stride=(2,2)) 

flatten = mx.sym.flatten(data=pool2) 
fc1 = mx.symbol.FullyConnected(data=flatten, num_hidden=12) 

lenet = mx.sym.SoftmaxOutput(data=fc1, name='softmax') 

lenet_model = mx.mod.Module(symbol=lenet, context=mx.cpu()) 

lenet_model.fit(train_iterator, 
       eval_data=validate_iterator, 
       optimizer='sgd', 
       optimizer_params={'learning_rate':0.1}, 
       eval_metric='acc', 
       batch_end_callback =mx.callback.Speedometer(batch_size, 100), 
       num_epoch=5)

来源

2017-08-13 esraa

解决添加到您的这些代码：

import logging 
logging.getLogger().setLevel(logging.INFO)

针对不同类型的处理报告，请参阅 “回调API中MXNet”

来源

2017-08-19 02:05:20 esraa

如何打印来自model.fit MXNet的处理步骤/报告Python

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