tf.config.experimental.get_device_details

Returns details about a physical devices.

This API takes in a tf.config.PhysicalDevice returned by tf.config.list_physical_devices. It returns a dict with string keys containing various details about the device. Each key is only supported by a subset of devices, so you should not assume the returned dict will have any particular key.

gpu_devices = tf.config.list_physical_devices('GPU')
if gpu_devices:
  details = tf.config.experimental.get_device_details(gpu_devices[0])
  details.get('device_name', 'Unknown GPU')

Currently, details are only returned for GPUs. This function returns an empty dict if passed a non-GPU device.

The returned dict may have the following keys:

  • 'device_name': A human-readable name of the device as a string, e.g. "Titan V". Unlike tf.config.PhysicalDevice.name, this will be the same for multiple devices if each device is the same model. Currently only available for GPUs.
  • 'compute_capability': The compute capability of the device as a tuple of two ints, in the form (major_version, minor_version). Only available for NVIDIA GPUs
Note: This is similar to tf.sysconfig.get_build_info in that both functions can return information relating to GPUs. However, this function returns run-time information about a specific device (such as a GPU's compute capability), while tf.sysconfig.get_build_info returns compile-time information about how TensorFlow was built (such as what version of CUDA TensorFlow was built for).
Args
device A tf.config.PhysicalDevice returned by tf.config.list_physical_devices or tf.config.get_visible_devices.
Returns
A dict with string keys.

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Licensed under the Creative Commons Attribution License 3.0.
Code samples licensed under the Apache 2.0 License.
https://www.tensorflow.org/versions/r2.4/api_docs/python/tf/config/experimental/get_device_details