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Diffstat (limited to 'tensorflow/docs_src/guide/graphs.md')
| -rw-r--r-- | tensorflow/docs_src/guide/graphs.md | 8 |
1 files changed, 4 insertions, 4 deletions
diff --git a/tensorflow/docs_src/guide/graphs.md b/tensorflow/docs_src/guide/graphs.md index 2bb44fbb32..c70479dba2 100644 --- a/tensorflow/docs_src/guide/graphs.md +++ b/tensorflow/docs_src/guide/graphs.md @@ -38,13 +38,13 @@ programs: machines. TensorFlow inserts the necessary communication and coordination between devices. -* **Compilation.** TensorFlow's @{$performance/xla$XLA compiler} can +* **Compilation.** TensorFlow's [XLA compiler](../performance/xla/index.md) can use the information in your dataflow graph to generate faster code, for example, by fusing together adjacent operations. * **Portability.** The dataflow graph is a language-independent representation of the code in your model. You can build a dataflow graph in Python, store it - in a @{$saved_model$SavedModel}, and restore it in a C++ program for + in a [SavedModel](../guide/saved_model.md), and restore it in a C++ program for low-latency inference. @@ -93,7 +93,7 @@ to all API functions in the same context. For example: stored value. The `tf.Variable` object also has methods such as `tf.Variable.assign` and `tf.Variable.assign_add` that create `tf.Operation` objects that, when executed, update the stored value. - (See @{$guide/variables} for more information about variables.) + (See [Variables](../guide/variables.md) for more information about variables.) * Calling `tf.train.Optimizer.minimize` will add operations and tensors to the default graph that calculates gradients, and return a `tf.Operation` that, @@ -210,7 +210,7 @@ with tf.device("/device:GPU:0"): # Operations created in this context will be pinned to the GPU. result = tf.matmul(weights, img) ``` -If you are deploying TensorFlow in a @{$distributed$typical distributed configuration}, +If you are deploying TensorFlow in a [typical distributed configuration](../deploy/distributed.md), you might specify the job name and task ID to place variables on a task in the parameter server job (`"/job:ps"`), and the other operations on task in the worker job (`"/job:worker"`): |