December 2017
Intermediate to advanced
536 pages
14h 23m
English
Content preview from TensorFlow 1.x Deep Learning Cookbook
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How to do it...
TensorFlow generates TensorFlow graphs. With the help of XLA, it is possible to run the TensorFlow graphs on any new kind of device.
- JIT Compilation: This is to turn on JIT compilation at session level:
# Config to turn on JIT compilation config = tf.ConfigProto() config.graph_options.optimizer_options.global_jit_level = tf.OptimizerOptions.ON_1 sess = tf.Session(config=config)
- This is to turn on JIT compilation manually:
jit_scope = tf.contrib.compiler.jit.experimental_jit_scopex = tf.placeholder(np.float32)with jit_scope(): y = tf.add(x, x) # The "add" will be compiled with XLA.
- We can also run computations via XLA by placing the operator on a specific XLA device XLA_CPU or XLA_GPU:
with tf.device \ ("/job:localhost/replica:0/task:0/device:XLA_GPU:0"): ...Become an O’Reilly member and get unlimited access to this title plus top books and audiobooks from O’Reilly and nearly 200 top publishers, thousands of courses curated by job role, 150+ live events each month,
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