code: def get_device_details(device):
      """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](https://developer.nvidia.com/cuda-gpus) 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.
      """
      return context.context().get_device_details(device)
  
imports: from typing import Union
  from tensorflow.python.eager import context
  from tensorflow.python.framework import errors
  from tensorflow.python.util import _pywrap_determinism
  from tensorflow.python.util import _pywrap_tensor_float_32_execution
  from tensorflow.python.util import deprecation
  from tensorflow.python.util.tf_export import tf_export
label_desc: Use image node_id 26 for calling a global function with example usage: get_device_details(device) and returns: context