View source on GitHub
Represents a cluster as a set of "tasks", organized into "jobs".
View aliases
Compat aliases for migration
See Migration guide for more details.
tf.train.ClusterSpec(
cluster
)
A tf.train.ClusterSpec represents the set of processes that
participate in a distributed TensorFlow computation. Every
tf.distribute.Server is constructed in a particular cluster.
To create a cluster with two jobs and five tasks, you specify the mapping from job names to lists of network addresses (typically hostname-port pairs).
cluster = tf.train.ClusterSpec({"worker": ["worker0.example.com:2222",
"worker1.example.com:2222",
"worker2.example.com:2222"],
"ps": ["ps0.example.com:2222",
"ps1.example.com:2222"]})
Each job may also be specified as a sparse mapping from task indices to network addresses. This enables a server to be configured without needing to know the identity of (for example) all other worker tasks:
cluster = tf.train.ClusterSpec({"worker": {1: "worker1.example.com:2222"},
"ps": ["ps0.example.com:2222",
"ps1.example.com:2222"]})
Args | |
|---|---|
cluster
|
A dictionary mapping one or more job names to (i) a list of
network addresses, or (ii) a dictionary mapping integer task indices to
network addresses; or a tf.train.ClusterDef protocol buffer.
|
Raises | |
|---|---|
TypeError
|
If cluster is not a dictionary mapping strings to lists
of strings, and not a tf.train.ClusterDef protobuf.
|
Methods
as_cluster_def
as_cluster_def()
Returns a tf.train.ClusterDef protocol buffer based on this cluster.
as_dict
as_dict()
Returns a dictionary from job names to their tasks.
For each job, if the task index space is dense, the corresponding value will be a list of network addresses; otherwise it will be a dictionary mapping (sparse) task indices to the corresponding addresses.
| Returns | |
|---|---|
| A dictionary mapping job names to lists or dictionaries describing the tasks in those jobs. |
job_tasks
job_tasks(
job_name
)
Returns a mapping from task ID to address in the given job.
| Args | |
|---|---|
job_name
|
The string name of a job in this cluster. |
| Returns | |
|---|---|
A list of task addresses, where the index in the list
corresponds to the task index of each task. The list may contain
None if the job was defined with a sparse set of task indices.
|
| Raises | |
|---|---|
ValueError
|
If job_name does not name a job in this cluster.
|
num_tasks
num_tasks(
job_name
)
Returns the number of tasks defined in the given job.
| Args | |
|---|---|
job_name
|
The string name of a job in this cluster. |
| Returns | |
|---|---|
| The number of tasks defined in the given job. |
| Raises | |
|---|---|
ValueError
|
If job_name does not name a job in this cluster.
|
task_address
task_address(
job_name, task_index
)
Returns the address of the given task in the given job.
| Args | |
|---|---|
job_name
|
The string name of a job in this cluster. |
task_index
|
A non-negative integer. |
| Returns | |
|---|---|
| The address of the given task in the given job. |
| Raises | |
|---|---|
ValueError
|
If job_name does not name a job in this cluster,
or no task with index task_index is defined in that job.
|
task_indices
task_indices(
job_name
)
Returns a list of valid task indices in the given job.
| Args | |
|---|---|
job_name
|
The string name of a job in this cluster. |
| Returns | |
|---|---|
| A list of valid task indices in the given job. |
| Raises | |
|---|---|
ValueError
|
If job_name does not name a job in this cluster,
or no task with index task_index is defined in that job.
|
__bool__
__bool__()
__eq__
__eq__(
other
)
Return self==value.
__ne__
__ne__(
other
)
Return self!=value.
__nonzero__
__nonzero__()