tf.contrib.learn.monitors.StepCounter.post_step()
  • References/Big Data/TensorFlow/TensorFlow Python/Monitors

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

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tf.contrib.learn.monitors.GraphDump.run_on_all_workers
  • References/Big Data/TensorFlow/TensorFlow Python/Monitors

tf.contrib.learn.monitors.GraphDump.run_on_all_workers

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tf.contrib.learn.monitors.BaseMonitor.set_estimator()
  • References/Big Data/TensorFlow/TensorFlow Python/Monitors

tf.contrib.learn.monitors.BaseMonitor.set_estimator(estimator) A setter called automatically by the target estimator.

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tf.contrib.learn.monitors.LoggingTrainable.post_step()
  • References/Big Data/TensorFlow/TensorFlow Python/Monitors

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

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tf.contrib.learn.monitors.NanLoss.end()
  • References/Big Data/TensorFlow/TensorFlow Python/Monitors

tf.contrib.learn.monitors.NanLoss.end(session=None)

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tf.contrib.learn.monitors.BaseMonitor.epoch_end()
  • References/Big Data/TensorFlow/TensorFlow Python/Monitors

tf.contrib.learn.monitors.BaseMonitor.epoch_end(epoch) End epoch. Args:

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tf.contrib.learn.monitors.CheckpointSaver.epoch_begin()
  • References/Big Data/TensorFlow/TensorFlow Python/Monitors

tf.contrib.learn.monitors.CheckpointSaver.epoch_begin(epoch) Begin epoch. Args:

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tf.contrib.learn.monitors.StopAtStep.end()
  • References/Big Data/TensorFlow/TensorFlow Python/Monitors

tf.contrib.learn.monitors.StopAtStep.end(session=None) Callback at the end of training/evaluation. Args:

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tf.contrib.learn.monitors.StopAtStep.
  • References/Big Data/TensorFlow/TensorFlow Python/Monitors

tf.contrib.learn.monitors.StopAtStep.__init__(num_steps=None, last_step=None) Create a StopAtStep monitor. This

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tf.contrib.learn.monitors.BaseMonitor.step_begin()
  • References/Big Data/TensorFlow/TensorFlow Python/Monitors

tf.contrib.learn.monitors.BaseMonitor.step_begin(step) Callback before training step begins. You

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