# Class DeviceSpec

Represents a (possibly partial) specification for a TensorFlow device.

# Aliases:

• Class tf.compat.v2.DeviceSpec DeviceSpecs are used throughout TensorFlow to describe where state is stored and computations occur. Using DeviceSpec allows you to parse device spec strings to verify their validity, merge them or compose them programmatically.

# Example:

 # Place the operations on device "GPU:0" in the "ps" job.
device_spec = DeviceSpec(job="ps", device_type="GPU", device_index=0)
with tf.device(device_spec):
  # Both my_var and squared_var will be placed on /job:ps/device:GPU:0.
  my_var = tf.Variable(..., name="my_variable")
  squared_var = tf.square(my_var)

If a DeviceSpec is partially specified, it will be merged with other DeviceSpecs according to the scope in which it is defined. DeviceSpec components defined in inner scopes take precedence over those defined in outer scopes.

 with tf.device(DeviceSpec(job="train", )):
  with tf.device(DeviceSpec(job="ps", device_type="GPU", device_index=0):
    # Nodes created here will be assigned to /job:ps/device:GPU:0.
  with tf.device(DeviceSpec(device_type="GPU", device_index=1):
    # Nodes created here will be assigned to /job:train/device:GPU:1.

A DeviceSpec consists of 5 components -- each of which is optionally specified:

• Job:Thejobname.``
• Replica:Thereplicaindex.
• Task: The taskindex.
• Devicetype:Thedevice typestring (e.g. "CPU" or"GPU").``
• Deviceindex: The deviceindex.

# init

View source

 __init__(
    job=None,
    replica=None,
    task=None,
    device_type=None,
    device_index=None
)

Create a new DeviceSpec object.

# Args:

• job: string. Optional job name.
• replica: int. Optional replica index.
• task: int. Optional task index.
• device_type: Optional device type string (e.g. "CPU" or "GPU")
• device_index: int. Optional device index. If left unspecified, device represents 'any' device_index.

# Properties

# device_index

# device_type

# job

# replica

# task

# Methods

# eq

View source

 __eq__(other)

Checks if the other DeviceSpec is same as the current instance, eg have same value for all the internal fields.

# Args:

• other: Another DeviceSpec

# Returns:

Return True if other is also a DeviceSpec instance and has same value as the current instance. Return False otherwise.

# from_string

View source

 @classmethod
from_string(
    cls,
    spec
)

Construct a DeviceSpec from a string.

# Args:

• spec: a string of the form /job:/replica:/task:/device:CPU: or /job:/replica:/task:/device:GPU: as cpu and gpu are mutually exclusive. All entries are optional.

# Returns:

A DeviceSpec.

# make_merged_spec

View source

 make_merged_spec(dev)

Returns a new DeviceSpec which incorporates dev. When combining specs, dev will take precidence over the current spec. So for instance:

 first_spec = tf.DeviceSpec(job=0, device_type="CPU")
second_spec = tf.DeviceSpec(device_type="GPU")
combined_spec = first_spec.make_merged_spec(second_spec)

is equivalent to:

 combined_spec = tf.DeviceSpec(job=0, device_type="GPU")

# Args:

• dev: a DeviceSpec

# Returns:

A new DeviceSpec which combines self and dev

# parse_from_string

View source

 parse_from_string(spec)

Parse a DeviceSpec name into its components. 2.x behavior change: In TensorFlow 1.x, this function mutates its own state and returns itself. In 2.x, DeviceSpecs are immutable, and this function will return a DeviceSpec which contains the spec. Recommended: Will work in 1.x and 2.x (though deprecated in 2.x): Will NOT work in 2.x: DeviceSpec.from_stringIn general, should completely replace DeviceSpec.parse_from_string, and DeviceSpec.replace should completely replace setting attributes directly.

# Args:

• spec: an optional string of the form /job:/replica:/task:/device:CPU: or /job:/replica:/task:/device:GPU: as cpu and gpu are mutually exclusive. All entries are optional.

# Returns:

The DeviceSpec.

# Raises:

• ValueError: if the spec was not valid.

# replace

View source

 replace(**kwargs)

Convenience method for making a new DeviceSpec by overriding fields.

# For instance:

 my_spec = DeviceSpec=(job="my_job", device="CPU")
my_updated_spec = my_spec.replace(device="GPU")
my_other_spec = my_spec.replace(device=None)

# Args:

# Returns:

A DeviceSpec with the fields specified in kwargs overridden.

# to_string

View source

 to_string()

Return a string representation of this DeviceSpec.

# Returns:

a string of the form /job:/replica:/task:/device::.