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tf.config.experimental.reset_memory_stats

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.

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.

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"'.