tf.contrib.tpu.Topology

Class Topology

Defined in tensorflow/contrib/tpu/python/tpu/topology.py.

Describes a set of TPU devices.

Represents both the shape of the physical mesh, and the mapping between TensorFlow TPU devices to physical mesh coordinates.

Properties

device_coordinates

Describes the mapping from TPU devices to topology coordinates.

Returns:

A rank 3 int32 array with shape [tasks, devices, axis]. tasks is the number of tasks in the TPU cluster, devices is the number of TPU devices per task, and axis is the number of axes in the TPU cluster topology. Each entry gives the axis-th coordinate in the topology of a task/device pair. TPU topologies are 3-dimensional, with dimensions (x, y, core number).

mesh_shape

A rank 1 int32 array describing the shape of the TPU topology.

Methods

__init__

__init__(
    serialized=None,
    mesh_shape=None,
    device_coordinates=None
)

Builds a Topology object.

If serialized is not None, the topology is parsed from serialized and the other arguments are ignored. Otherwise, the topology is computed from mesh_shape and device_coordinates.

Args:

• serialized: A serialized TopologyProto, or None. If not None, the serialized proto is parsed to discover the topology.
• mesh_shape: A sequence of 3 positive integers, or None. If not None, the shape of the TPU topology, in number of cores. Ignored if serialized is not None.
• device_coordinates: A rank 3 numpy array that describes the mapping from TensorFlow TPU devices to TPU fabric coordinates, or None. Ignored if serialized is notNone`.

Raises:

• ValueError: If serialized does not describe a well-formed topology.
• ValueError: If serialized is None and mesh_shape is not a sequence of 3 positive integers.
• ValueError: If serialized is None and device_coordinates is not a rank 3 numpy int32 array that describes a valid coordinate mapping.

serialized

serialized()

Returns the serialized form of the topology.