Tensorflow 找不到张力板

我正在尝试使用tensorboard仪表板检查模型性能。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)

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.

但是在模型培训之后，我无法显示仪表板：

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)

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.

%tensorboard--logdir日志

这是我得到的错误：

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)

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.

---

您需要在终端上执行tensorboard命令以打开tensorboard服务器

命令应该是

tensorboard --logdir="<path to your logdir>"

tensorboard--logdir=“”

这可能是因为笔记本电脑和虚拟环境之间存在冲突

这里一个简单的解决方案就是在笔记本中指定

TENSORBOARD\u BINARY

变量，这样它就不会干扰全局变量，然后再像这样调用TENSORBOARD：

os.environ['TENSORBOARD_BINARY'] = '/path/to/envs/my_env/bin/tensorboard'

一个长期的解决方案是为虚拟环境设置一个变量，就像它被提议的那样