tf.contrib.learn.monitors.EveryN.every_n_step_end()
  • References/Big Data/TensorFlow/TensorFlow Python/Monitors

tf.contrib.learn.monitors.EveryN.every_n_step_end(step, outputs) Callback after every n'th step finished. This

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

tf.contrib.learn.monitors.NanLoss.every_n_post_step(step, session) Callback after a step is finished or end() is

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

tf.contrib.learn.monitors.ValidationMonitor.early_stopped Returns True if this monitor caused an early stop.

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

tf.contrib.learn.monitors.StepCounter.step_end(step, output) Overrides BaseMonitor.step_end. When

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

class tf.contrib.learn.monitors.PrintTensor Prints given tensors every N steps. This is an EveryN

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tf.contrib.learn.monitors.RunHookAdapterForMonitors.before_run()
  • References/Big Data/TensorFlow/TensorFlow Python/Monitors

tf.contrib.learn.monitors.RunHookAdapterForMonitors.before_run(run_context)

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

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

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

tf.contrib.learn.monitors.NanLoss.step_end(step, output) Overrides BaseMonitor.step_end. When

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

tf.contrib.learn.monitors.GraphDump.data

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tf.contrib.learn.monitors.ExportMonitor.every_n_step_end()
  • References/Big Data/TensorFlow/TensorFlow Python/Monitors

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

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