class_docstr: 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.
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docstr: 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 4-dimensional, with
    dimensions `(x, y, z, core number)`.
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code: def device_coordinates(self):
      """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 4-dimensional, with
        dimensions `(x, y, z, core number)`.
      """
      return self._device_coordinates
  
imports: import numpy
  from tensorflow.core.protobuf.tpu import topology_pb2
  from tensorflow.python.util.tf_export import tf_export
label_desc: Use image node_id 6 for calling the Topology obj's underlying member method code with example usage: obj.device_coordinates() and returns: self