contrib.keras.callbacks.TensorBoard
tf.contrib.keras.callbacks.TensorBoard
class tf.contrib.keras.callbacks.TensorBoard
Defined in tensorflow/contrib/keras/python/keras/callbacks.py
.
Tensorboard basic visualizations.
This callback writes a log for TensorBoard, which allows you to visualize dynamic graphs of your training and test metrics, as well as activation histograms for the different layers in your model.
Arguments:
log_dir: the path of the directory where to save the log files to be parsed by Tensorboard. histogram_freq: frequency (in epochs) at which to compute activation histograms for the layers of the model. If set to 0, histograms won't be computed. write_graph: whether to visualize the graph in Tensorboard. The log file can become quite large when write_graph is set to True. write_images: whether to write model weights to visualize as image in Tensorboard. embeddings_freq: frequency (in epochs) at which selected embedding layers will be saved. embeddings_layer_names: a list of names of layers to keep eye on. If None or empty list all the embedding layer will be watched. embeddings_metadata: a dictionary which maps layer name to a file name in which metadata for this embedding layer is saved. See the [details](https://www.tensorflow.org/how_tos/embedding_viz/#metadata_optional) about metadata files format. In case if the same metadata file is used for all embedding layers, string can be passed.
Methods
__init__
__init__( log_dir='./logs', histogram_freq=0, write_graph=True, write_images=False, embeddings_freq=0, embeddings_layer_names=None, embeddings_metadata=None )
on_batch_begin
on_batch_begin( batch, logs=None )
on_batch_end
on_batch_end( batch, logs=None )
on_epoch_begin
on_epoch_begin( epoch, logs=None )
on_epoch_end
on_epoch_end( epoch, logs=None )
on_train_begin
on_train_begin(logs=None)
on_train_end
on_train_end(_)
set_model
set_model(model)
set_params
set_params(params)
© 2017 The TensorFlow Authors. All rights reserved.
Licensed under the Creative Commons Attribution License 3.0.
Code samples licensed under the Apache 2.0 License.
https://www.tensorflow.org/api_docs/python/tf/contrib/keras/callbacks/TensorBoard