首先创建log的目录my_dir，在cmd下执行 tensorboard --logdir=my_dir,对模型进行训练，同时打开浏览器，输入 localhost:6006 ,就可以看到模型训练过程的一些实时信息。
代码如下：
import keras from keras import layers from keras.datasets import imdb from keras.preprocessing import sequence max_features = 2000 max_len = 500 (x_train, y_train), (x_test, y_test) = imdb.load_data(num_words=max_features) x_train = sequence.pad_sequences(x_train, maxlen=max_len) x_test = sequence.pad_sequences(x_test, maxlen=max_len) model = keras.models.Sequential() model.add(layers.Embedding(max_features, 128, input_length=max_len, name=‘embed‘)) model.add(layers.Conv1D(32, 7, activation=‘relu‘)) model.add(layers.MaxPooling1D(5)) model.add(layers.Conv1D(32, 7, activation=‘relu‘)) model.add(layers.GlobalMaxPool1D()) model.add(layers.Dense(1)) print(model.summary()) model.compile(optimizer=‘rmsprop‘, loss=‘binary_crossentropy‘, metrics=[‘acc‘]) tcallbacks = [ keras.callbacks.TensorBoard( log_dir=‘./logs_dir‘, histogram_freq=1, embeddings_freq=1, embeddings_data=x_train[:1000].astype("float32") ) ] history = model.fit( x_train, y_train, epochs=20, batch_size=128, validation_split=0.2, callbacks=tcallbacks )
tensorboard界面展示如下：
原文：https://www.cnblogs.com/andy2020/p/13161185.html