update doc links for tensorboard/embeddings
@@ -669,7 +669,7 @@ class LearningRateScheduler(Callback):
class TensorBoard(Callback):
"""TensorBoard basic visualizations.
- [TensorBoard](https://www.tensorflow.org/get_started/summaries_and_tensorboard)
+ [TensorBoard](https://www.tensorflow.org/guide/summaries_and_tensorboard)
is a visualization tool provided with TensorFlow.
This callback writes a log for TensorBoard, which allows
@@ -711,14 +711,14 @@ class TensorBoard(Callback):
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)
+ [details](https://www.tensorflow.org/guide/embedding#metadata)
about metadata files format. In case if the same metadata file is
used for all embedding layers, string can be passed.
embeddings_data: data to be embedded at layers specified in
`embeddings_layer_names`. Numpy array (if the model has a single
input) or list of Numpy arrays (if the model has multiple inputs).
Learn [more about embeddings](
- https://www.tensorflow.org/programmers_guide/embedding).
+ https://www.tensorflow.org/guide/embedding).
update_freq: `'batch'` or `'epoch'` or integer. When using `'batch'`, writes
the losses and metrics to TensorBoard after each batch. The same
applies for `'epoch'`. If using an integer, let's say `10000`,
