python保存log日志,实现用log日志画图

python保存保存log日志日志,实现用实现用log日志画图日志画图

今天小编就为大家分享一篇python保存log日志,实现用log日志来画图，具有很好的参考价值，希望对大家有所

帮助。一起跟随小编过来看看吧

在神经网络训练中，我们常常需要画出loss function的变化图，log日志里会显示每一次迭代的loss function的值，于是我们先

把log日志保存为log.txt文档，再利用这个文档来画图。 　　

1，先来产生一个，先来产生一个log日志。日志。

import mxnet as mx

import numpy as np

train_label = np.array([train_data[i][0] + 2 * train_data[i][1] for i in range(100)])

batch_size = 1

num_epoch=5

# Evaluation Data

eval_data = np.array([[7,2],[6,10],[12,2]])

eval_label = np.array([11,26,16])

train_iter = mx.io.NDArrayIter(train_data,train_label, batch_size, shuffle=True,label_name='lin_reg_label')

eval_iter = mx.io.NDArrayIter(eval_data, eval_label, batch_size, shuffle=False)

X = mx.sym.Variable('data')

Y = mx.sym.Variable('lin_reg_label')

)

model.fit(train_iter, eval_iter,

optimizer_params={'learning_rate':0.005, 'momentum': 0.9},

num_epoch=20,

eval_metric='mse',)

model.predict(eval_iter).asnumpy()

metric = mx.metric.MSE()

model.score(eval_iter, metric)

上面的代码中logging.basicConfig(filename = os.path.join(os.getcwd(), 'log.txt'), level = logging.DEBUG) # 把log日志保存为

log.txt 就是把log日志保存为log.txt文件。 　　

INFO:root:Epoch[1] Validation-mse=41.625072

INFO:root:Epoch[2] Train-mse=0.044817

INFO:root:Epoch[2] Time cost=0.063

INFO:root:Epoch[2] Validation-mse=23.743375

INFO:root:Epoch[3] Train-mse=0.024459

INFO:root:Epoch[3] Time cost=0.063

INFO:root:Epoch[3] Validation-mse=13.511120

INFO:root:Epoch[4] Train-mse=0.013431

INFO:root:Epoch[4] Time cost=0.063

INFO:root:Epoch[4] Validation-mse=7.670062

INFO:root:Epoch[7] Train-mse=0.002274

INFO:root:Epoch[7] Time cost=0.062

INFO:root:Epoch[7] Validation-mse=1.385449

INFO:root:Epoch[8] Train-mse=0.001263

INFO:root:Epoch[8] Time cost=0.063

INFO:root:Epoch[8] Validation-mse=0.780387

INFO:root:Epoch[9] Train-mse=0.000703

INFO:root:Epoch[9] Time cost=0.063