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Diffstat (limited to 'tensorflow/docs_src/extend/architecture.md')
| -rw-r--r-- | tensorflow/docs_src/extend/architecture.md | 4 |
1 files changed, 2 insertions, 2 deletions
diff --git a/tensorflow/docs_src/extend/architecture.md b/tensorflow/docs_src/extend/architecture.md index 84435a57f2..83d70c9468 100644 --- a/tensorflow/docs_src/extend/architecture.md +++ b/tensorflow/docs_src/extend/architecture.md @@ -81,7 +81,7 @@ implementation from all client languages. Most of the training libraries are still Python-only, but C++ does have support for efficient inference. The client creates a session, which sends the graph definition to the -distributed master as a @{tf.GraphDef} +distributed master as a `tf.GraphDef` protocol buffer. When the client evaluates a node or nodes in the graph, the evaluation triggers a call to the distributed master to initiate computation. @@ -96,7 +96,7 @@ feature vector (x), adds a bias term (b) and saves the result in a variable ### Code -* @{tf.Session} +* `tf.Session` ## Distributed master |