TensorFlow 1 version View source on GitHub

Simple implementation of ClusterResolver that accepts a ClusterSpec.

Inherits From: ClusterResolver

    cluster_spec, master='', task_type=None, task_id=None, environment='',
    num_accelerators=None, rpc_layer=None


  • environment: Returns the current environment which TensorFlow is running in.

    There are two possible return values, "google" (when TensorFlow is running in a Google-internal environment) or an empty string (when TensorFlow is running elsewhere).

    If you are implementing a ClusterResolver that works in both the Google environment and the open-source world (for instance, a TPU ClusterResolver or similar), you will have to return the appropriate string depending on the environment, which you will have to detect.

    Otherwise, if you are implementing a ClusterResolver that will only work in open-source TensorFlow, you do not need to implement this property.

  • rpc_layer

  • task_id

  • task_type



View source


Returns the ClusterSpec passed into the constructor.


View source

    task_type=None, task_id=None, rpc_layer=None

Returns the master address to use when creating a session.


  • task_type: (Optional) The type of the TensorFlow task of the master.
  • task_id: (Optional) The index of the TensorFlow task of the master.
  • rpc_layer: (Optional) The RPC used by distributed TensorFlow.


The name or URL of the session master.

If a task_type and task_id is given, this will override the master string passed into the initialization function.


View source

    task_type=None, task_id=None, config_proto=None

Returns the number of accelerator cores per worker.

The SimpleClusterResolver does not do automatic detection of accelerators, so a TensorFlow session will never be created, and thus all arguments are unused and we simply assume that the type of accelerator is a GPU and return the value in provided to us in the constructor.


  • task_type: Unused.
  • task_id: Unused.
  • config_proto: Unused.