Returns details about a physical devices.
Compat aliases for migration
See Migration guide for more details.
tf.config.experimental.get_device_details( device )
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) 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_infoin 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_inforeturns compile-time information about how TensorFlow was built (such as what version of CUDA TensorFlow was built for).
| || A |
|A dict with string keys.|
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Code samples licensed under the Apache 2.0 License.