tf.contrib.learn.monitors.ExportMonitor.signature_fn

tf.contrib.learn.monitors.ExportMonitor.step_end(step, output) Overrides BaseMonitor.step_end. When overriding this method, you must call the super implementation. Args: step: int, the current value of the global step. output: dict mapping string values representing tensor names to the value resulted from running these tensors. Values may be either scalars, for scalar tensors, or Numpy array, for non-scalar tensors. Returns: bool, the result of every_n_step_end, if that was called this ste

tf.contrib.learn.monitors.ExportMonitor.set_estimator(estimator) A setter called automatically by the target estimator. If the estimator is locked, this method does nothing. Args: estimator: the estimator that this monitor monitors. Raises: ValueError: if the estimator is None.

tf.contrib.learn.monitors.ExportMonitor.run_on_all_workers

tf.contrib.learn.monitors.ExportMonitor.post_step(step, session)

tf.contrib.learn.monitors.ExportMonitor.every_n_step_end(step, outputs)

tf.contrib.learn.monitors.ExportMonitor.every_n_step_begin(step) Callback before every n'th step begins. Args: step: int, the current value of the global step. Returns: A list of tensors that will be evaluated at this step.

tf.contrib.learn.monitors.ExportMonitor.last_export_dir Returns the directory containing the last completed export. Returns: The string path to the exported directory. NB: this functionality was added on 2016/09/25; clients that depend on the return value may need to handle the case where this function returns None because the estimator being fitted does not yet return a value during export.

tf.contrib.learn.monitors.ExportMonitor.export_dir

tf.contrib.learn.monitors.ExportMonitor.exports_to_keep