我试图用torch (torch.utils.tensorboard)将我的培训和验证损失写到张力板上,看起来它只写了1000个数据点,不管实际的迭代次数是多少。例如,运行以下代码,
writer1 = SummaryWriter('runs/1')
writer2 = SummaryWriter('runs/2')
for i in range(2000):
writer1.add_scalar('tag', 1, i)
for i in range(20000):
writer2.add_scalar('tag
我想使用tensorflow 2在张拉板上显示我的网络图。我遵循了教程,并编写了如下代码:
for epoch in range(epochs):
# Bracket the function call with
# tf.summary.trace_on() and tf.summary.trace_export().
tf.summary.trace_on(graph=True, profiler=True)
# Call only one tf.function when tracing.
z = train_step(x, y)
with
我正在尝试生产克拉斯的张力板。但是即使在给出正确的路径之后,也会得到'name not found error‘ 注意:有权限在该文件夹中写入,并且尝试时也没有时间格式 代码: from tensorflow.keras.callbacks import TensorBoard
from time import time
tensorboard = TensorBoard(log_dir="logs/{}".format(time()))
history= model_inc.fit(trainX,trainY,epochs=9,batch_size=16,val