Yuk*_*uka 4 tensorflow tensorboard
我正在尝试使用张量板仪表板来检查模型性能。下面是我使用的代码:
from keras.callbacks import TensorBoard
%load_ext tensorboard
log_dir = "logs/fit/" + datetime.now().strftime("%Y%m%d-%H%M%S")
tensorboard_callback = TensorBoard(log_dir=log_dir, histogram_freq=1)
checkpoint_name = 'Weights-{epoch:03d}--{val_loss:.5f}.hdf5'
checkpoint = ModelCheckpoint(checkpoint_name, monitor='val_loss', verbose = 1, save_best_only = True, mode ='auto')
es = EarlyStopping(monitor='val_loss', verbose=1, patience=10)
callbacks_list = [checkpoint ,es,tensorboard_callback]
NN_model.fit(train, target, epochs=100, batch_size=32, validation_split = 0.2, callbacks=callbacks_list)
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但模型训练后,我无法显示仪表板:
%tensorboard --logdir logs
这是我得到的错误:
ERROR: Could not find `tensorboard`. Please ensure that your PATH
contains an executable `tensorboard` program, or explicitly specify
the path to a TensorBoard binary by setting the `TENSORBOARD_BINARY`
environment variable.
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小智 6
这可能是由于笔记本和虚拟环境之间的某些冲突而发生的。
这里一个简单的解决方案就是TENSORBOARD_BINARY在笔记本中指定变量,这样它就不会干扰全局变量,然后再像这样调用张量板:
os.environ['TENSORBOARD_BINARY'] = '/path/to/envs/my_env/bin/tensorboard'
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一个长期的解决方案是为虚拟环境设置一个变量,就像这里提出的那样。
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