Python Tensorboard以Chrome显示空白页面

我不熟悉TensorFlow和Tensorboard，当我运行下面的代码时，模型训练并返回其输出，但是Tensorboard在浏览器中显示空白页

import pandas as pd
import os
import tensorflow as tf
from time import time
from tensorflow.python.keras.layers.core import Dense
from tensorflow.python.keras.models import Sequential
from tensorflow.python.keras.layers import LSTM
from tensorflow.python.keras.callbacks import TensorBoard
import matplotlib.pyplot as plt
from sklearn.preprocessing import MinMaxScaler
import numpy as np

model = Sequential()
model.add(LSTM(units=20, return_sequences=True, input_shape=(1, 7), activation='softsign'))
model.add(LSTM(units=50, return_sequences=True, activation='softsign'))
model.add(LSTM(units=50, return_sequences=True, activation='softsign'))
model.add(LSTM(units=50, return_sequences=True, activation='softsign'))
model.add(LSTM(units=20, activation='softsign'))
model.add(Dense(units=1, activation='sigmoid'))

model.compile(loss='mse', optimizer='Nadam',metrics=['mse'])

tensorboard = TensorBoard(log_dir="logs/fit")

result = model.fit(X_train, Y_train, batch_size=200, epochs=5, validation_split=0.1, verbose=1, callbacks=[tensorboard])

我在PyCharm终端中使用

TensorBoard--logdir=logs/

实例化TensorBoard，并在Chrome（）中打开TensorBoard。但是，该页面是空白的，没有显示任何输出（甚至连Tensorboard的橙色标题都没有）

任何帮助都将不胜感激

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谢谢。

为了社区的利益，我在这里发布了答案

import pandas as pd
import os
import tensorflow as tf
from time import time
from tensorflow.python.keras.layers.core import Dense
from tensorflow.python.keras.models import Sequential
from tensorflow.python.keras.layers import LSTM
from tensorflow.python.keras.callbacks import TensorBoard
import matplotlib.pyplot as plt
from sklearn.preprocessing import MinMaxScaler
import numpy as np

model = Sequential()
model.add(LSTM(units=20, return_sequences=True, input_shape=(1, 7), activation='softsign'))
model.add(LSTM(units=50, return_sequences=True, activation='softsign'))
model.add(LSTM(units=50, return_sequences=True, activation='softsign'))
model.add(LSTM(units=50, return_sequences=True, activation='softsign'))
model.add(LSTM(units=20, activation='softsign'))
model.add(Dense(units=1, activation='sigmoid'))

model.compile(loss='mse', optimizer='Nadam',metrics=['mse'])

tensorboard = TensorBoard(log_dir="logs/fit")

result = model.fit(X_train, Y_train, batch_size=200, epochs=5, validation_split=0.1, verbose=1, callbacks=[tensorboard])

%load_ext tensorboard
%tensorboard --logdir logs

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您使用的是哪个版本？我发现2.1.0是空白的，但2.0.0是有效的。我试过两种方法，但都没有成功。你可以试试

tensorboard--logdir='logs/'--port=6006

请你试试

tensorboard--logdir=logs/fit

。如果这不是解决问题的方法。共享整个代码怎么样？使用

tensorboard--logdir-logs

最终在tensorboard 2.0.0中起作用！谢谢你们的帮助！