class_docstr: A distribution strategy for running on a single device.
  
  Using this strategy will place any variables created in its scope on the
  specified device. Input distributed through this strategy will be
  prefetched to the specified device. Moreover, any functions called via
  `strategy.run` will also be placed on the specified device
  as well.
  
  Typical usage of this strategy could be testing your code with the
  tf.distribute.Strategy API before switching to other strategies which
  actually distribute to multiple devices/machines.
  
  For example:
  ```
  strategy = tf.distribute.OneDeviceStrategy(device="/gpu:0")
  
  with strategy.scope():
    v = tf.Variable(1.0)
    print(v.device)  # /job:localhost/replica:0/task:0/device:GPU:0
  
  def step_fn(x):
    return x * 2
  
  result = 0
  for i in range(10):
    result += strategy.run(step_fn, args=(i,))
  print(result)  # 90
  ```
class_docstr_tok: ["A","distribution","strategy","for","running","on","a","single","device",".","Using","this","strategy","will","place","any","variables","created","in","its","scope","on","the","specified","device",".","Input","distributed","through","this","strategy","will","be","prefetched","to","the","specified","device",".","Moreover",",","any","functions","called","via","`","strategy.run","`","will","also","be","placed","on","the","specified","device","as","well",".","Typical","usage","of","this","strategy","could","be","testing","your","code","with","the","tf.distribute.Strategy","API","before","switching","to","other","strategies","which","actually","distribute","to","multiple","devices\/machines",".","For","example",":","``","`","strategy","=","tf.distribute.OneDeviceStrategy","(","device=","''","\/gpu:0","''",")","with","strategy.scope","(",")",":","v","=","tf.Variable","(","1.0",")","print","(","v.device",")","#","\/job",":","localhost\/replica:0\/task:0\/device",":","GPU:0","def","step_fn","(","x",")",":","return","x","*","2","result","=","0","for","i","in","range","(","10",")",":","result","+=","strategy.run","(","step_fn",",","args=","(","i",",",")",")","print","(","result",")","#","90","``","`"]
docstr: Creates a `OneDeviceStrategy`.
  
  Args:
    device: Device string identifier for the device on which the variables
      should be placed. See class docs for more details on how the device is
      used. Examples: "/cpu:0", "/gpu:0", "/device:CPU:0", "/device:GPU:0"
docstr_tok: ["Creates","a","`","OneDeviceStrategy","`",".","Args",":","device",":","Device","string","identifier","for","the","device","on","which","the","variables","should","be","placed",".","See","class","docs","for","more","details","on","how","the","device","is","used",".","Examples",":","``","\/cpu:0","''",",","``","\/gpu:0","''",",","``","\/device",":","CPU:0","''",",","``","\/device",":","GPU:0","''"]
code: def __init__(self, device):
      """Creates a `OneDeviceStrategy`.
  
      Args:
        device: Device string identifier for the device on which the variables
          should be placed. See class docs for more details on how the device is
          used. Examples: "/cpu:0", "/gpu:0", "/device:CPU:0", "/device:GPU:0"
      """
      super(OneDeviceStrategy, self).__init__(
          OneDeviceExtended(self, device)
      )
      distribute_lib.distribution_strategy_gauge.get_cell("V2").set(
          "OneDeviceStrategy"
      )
  
imports: from tensorflow.python.distribute import device_util
  from tensorflow.python.distribute import distribute_lib
  from tensorflow.python.distribute import distribute_utils
  from tensorflow.python.distribute import input_lib
  from tensorflow.python.distribute import input_util
  from tensorflow.python.distribute import numpy_dataset
  from tensorflow.python.distribute.v1 import input_lib
  from tensorflow.python.framework import constant_op
  from tensorflow.python.framework import ops
  from tensorflow.python.ops import array_ops
  from tensorflow.python.ops import control_flow_ops
  from tensorflow.python.ops import while_loop
  from tensorflow.python.util import nest
  from tensorflow.python.util.tf_export import tf_export
label_desc: Use image node_id 1 to create a new OneDeviceStrategy object from inherited base classes: distribute_lib with example: obj = OneDeviceStrategy(device)