parameters: (device)
docstring: Resets the tracked memory stats for the chosen device.
  
    This function sets the tracked peak memory for a device to the device's
    current memory usage. This allows you to measure the peak memory usage for a
    specific part of your program. For example:
  
    >>> if tf.config.list_physical_devices('GPU'):
    ...   # Sets the peak memory to the current memory.
    ...   tf.config.experimental.reset_memory_stats('GPU:0')
    ...   # Creates the first peak memory usage.
    ...   x1 = tf.ones(1000 * 1000, dtype=tf.float64)
    ...   del x1 # Frees the memory referenced by `x1`.
    ...   peak1 = tf.config.experimental.get_memory_info('GPU:0')['peak']
    ...   # Sets the peak memory to the current memory again.
    ...   tf.config.experimental.reset_memory_stats('GPU:0')
    ...   # Creates the second peak memory usage.
    ...   x2 = tf.ones(1000 * 1000, dtype=tf.float32)
    ...   del x2
    ...   peak2 = tf.config.experimental.get_memory_info('GPU:0')['peak']
    ...   assert peak2 < peak1  # tf.float32 consumes less memory than tf.float64.
  
    Currently only supports GPU and TPU. If called on a CPU device, an exception
    will be raised.
  
    Args:
      device: Device string to reset the memory stats, e.g. `"GPU:0"`, `"TPU:0"`.
        See https://www.tensorflow.org/api_docs/python/tf/device for specifying
        device strings.
  
    Raises:
      ValueError: No device found with the device name, like '"nonexistent"'.
      ValueError: Invalid device name, like '"GPU"', '"CPU:GPU"', '"CPU:"'.
      ValueError: Multiple devices matched with the device name.
      ValueError: Memory statistics not tracked or clearing memory statistics not
        supported, like '"CPU:0"'.
docstring_summary: Resets the tracked memory stats for the chosen device.
docstring_tokens: Resets the tracked memory stats for the chosen device .
function: def reset_memory_stats(device):
    """Resets the tracked memory stats for the chosen device.
  
    This function sets the tracked peak memory for a device to the device's
    current memory usage. This allows you to measure the peak memory usage for a
    specific part of your program. For example:
  
    >>> if tf.config.list_physical_devices('GPU'):
    ...   # Sets the peak memory to the current memory.
    ...   tf.config.experimental.reset_memory_stats('GPU:0')
    ...   # Creates the first peak memory usage.
    ...   x1 = tf.ones(1000 * 1000, dtype=tf.float64)
    ...   del x1 # Frees the memory referenced by `x1`.
    ...   peak1 = tf.config.experimental.get_memory_info('GPU:0')['peak']
    ...   # Sets the peak memory to the current memory again.
    ...   tf.config.experimental.reset_memory_stats('GPU:0')
    ...   # Creates the second peak memory usage.
    ...   x2 = tf.ones(1000 * 1000, dtype=tf.float32)
    ...   del x2
    ...   peak2 = tf.config.experimental.get_memory_info('GPU:0')['peak']
    ...   assert peak2 < peak1  # tf.float32 consumes less memory than tf.float64.
  
    Currently only supports GPU and TPU. If called on a CPU device, an exception
    will be raised.
  
    Args:
      device: Device string to reset the memory stats, e.g. `"GPU:0"`, `"TPU:0"`.
        See https://www.tensorflow.org/api_docs/python/tf/device for specifying
        device strings.
  
    Raises:
      ValueError: No device found with the device name, like '"nonexistent"'.
      ValueError: Invalid device name, like '"GPU"', '"CPU:GPU"', '"CPU:"'.
      ValueError: Multiple devices matched with the device name.
      ValueError: Memory statistics not tracked or clearing memory statistics not
        supported, like '"CPU:0"'.
    """
    context.context().reset_memory_stats(device)
function_tokens: def reset_memory_stats ( device ) : context . context ( ) . reset_memory_stats ( device )