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Diffstat (limited to 'tensorflow/docs_src/programmers_guide/embedding.md')
| -rw-r--r-- | tensorflow/docs_src/programmers_guide/embedding.md | 4 |
1 files changed, 2 insertions, 2 deletions
diff --git a/tensorflow/docs_src/programmers_guide/embedding.md b/tensorflow/docs_src/programmers_guide/embedding.md index 975850349f..91beb36f96 100644 --- a/tensorflow/docs_src/programmers_guide/embedding.md +++ b/tensorflow/docs_src/programmers_guide/embedding.md @@ -84,7 +84,7 @@ labels/images to the data points. You can do this by generating a [metadata file](#metadata) containing the labels for each point and configuring the projector either by using our Python API, or manually constructing and saving a -<code>[projector_config.pbtxt](https://github.com/tensorflow/tensorflow/blob/master/tensorflow/tensorboard/plugins/projector/projector_config.proto)</code> +<code>[projector_config.pbtxt](https://github.com/tensorflow/tensorflow/blob/master/tensorflow/contrib/tensorboard/plugins/projector/projector_config.proto)</code> in the same directory as your checkpoint file. ### Setup @@ -113,7 +113,7 @@ saver.save(session, os.path.join(LOG_DIR, "model.ckpt"), step) If you have any metadata (labels, images) associated with your embedding, you can tell TensorBoard about it either by directly storing a -<code>[projector_config.pbtxt](https://github.com/tensorflow/tensorflow/blob/master/tensorflow/tensorboard/plugins/projector/projector_config.proto)</code> +<code>[projector_config.pbtxt](https://github.com/tensorflow/tensorflow/blob/master/tensorflow/contrib/tensorboard/plugins/projector/projector_config.proto)</code> in the <code>LOG_DIR</code>, or use our python API. For instance, the following <code>projector_config.ptxt</code> associates the |