tf.config.list_logical_devices

Return a list of logical devices created by runtime.

View aliases

Main aliases

tf.config.experimental.list_logical_devices

Compat aliases for migration

See Migration guide for more details.

tf.compat.v1.config.experimental.list_logical_devices, tf.compat.v1.config.list_logical_devices

tf.config.list_logical_devices(
    device_type=None
)

Used in the notebooks

Used in the guide	Used in the tutorials
Use a GPU NumPy API on TensorFlow Migrate from TPU embedding_columns to TPUEmbedding layer Migrate from TPUEstimator to TPUStrategy Distributed training with Core APIs and DTensor	Using DTensors with Keras Distributed training with DTensors Distributed Input Image classification with Model Garden TFF simulations with accelerators

Logical devices may correspond to physical devices or remote devices in the cluster. Operations and tensors may be placed on these devices by using the name of the tf.config.LogicalDevice.

Calling tf.config.list_logical_devices triggers the runtime to configure any tf.config.PhysicalDevice visible to the runtime, thereby preventing further configuration. To avoid runtime initialization, call tf.config.list_physical_devices instead.

For example:

logical_devices = tf.config.list_logical_devices('GPU')
if len(logical_devices) > 0:
  # Allocate on GPU:0
  with tf.device(logical_devices[0].name):
    one = tf.constant(1)
  # Allocate on GPU:1
  with tf.device(logical_devices[1].name):
    two = tf.constant(2)

Args
device_type	(optional string) Only include devices matching this device type. For example "CPU" or "GPU".
Notes	If provided with any numerical values or any string other than supported device type such as 'CPU' it returns an empty list instead of raising error. 2. For default value it returns all logical devices

Returns
List of initialized LogicalDevices