|TensorFlow 2 version||View source on GitHub|
Mapping from logical cores in a computation to the physical TPU topology.
`tf.contrib.tpu.DeviceAssignment`Compat aliases for migration
See Migration guide for more details.
tf.tpu.experimental.DeviceAssignment( topology, core_assignment )
Prefer to use the
DeviceAssignment.build() helper to construct a
DeviceAssignment; it is easier if less flexible than constructing a
A logical to physical core mapping, represented as a
rank 3 numpy array. See the description of the
||The logical to physical core mapping.|
||The number of cores per replica.|
||The number of replicas of the computation.|
build( topology, computation_shape=None, computation_stride=None, num_replicas=1 )
coordinates( replica, logical_core )
Returns the physical topology coordinates of a logical core.
host_device( replica=0, logical_core=0, job=None )
Returns the CPU device attached to a logical core.
lookup_replicas( task_id, logical_core )
Lookup replica ids by task number and logical core.
||TensorFlow task number.|
||An integer, identifying a logical core.|
|A sorted list of the replicas that are attached to that task and logical_core.|
||If no replica exists in the task which contains the logical core.|
tpu_device( replica=0, logical_core=0, job=None )
Returns the name of the TPU device assigned to a logical core.
tpu_ordinal( replica=0, logical_core=0 )
Returns the ordinal of the TPU device assigned to a logical core.