How to print progress when training a DNNClassifier in tensorflow r0.9 (skflow)?
<p>I couldn't get that a DNNClassifier prints the progress while training, ie, loss and validation score. As I understood the loss can be printed using the config parameter that inherits from BaseEstimator, but when I passed a RunConfig object, the classifier didn't printed anything.</p>

<pre><code>from tensorflow.contrib.learn.python.learn.estimators import run_config

config = run_config.RunConfig(verbose=1)
classifier = learn.DNNClassifier(hidden_units=[10, 20, 10],
                             n_classes=3,
                             config=config)
classifier.fit(X_train, y_train, steps=1000)
</code></pre>

<p>Am I missing something? I checked how RunConfig handles the verbose parameter and it seems <a href="https://github.com/tensorflow/tensorflow/blob/r0.9/tensorflow/contrib/learn/python/learn/estimators/run_config.py#L96" rel="noreferrer">that it only cares if its greater than 1</a>, which doesn't match with the documentation:</p>

<blockquote>
  <p>verbose: Controls the verbosity, possible values:
        0: the algorithm and debug information is muted.
        1: trainer prints the progress.
        2: log device placement is printed.</p>
</blockquote>

<p>As for the validation score I thought that using <a href="https://github.com/tensorflow/tensorflow/blob/r0.9/tensorflow/contrib/learn/python/learn/monitors.py#L181" rel="noreferrer">monitors.ValidationMonitor</a> would be just fine, but when tried it, the classifier doesn't print anything, also nothing happens when tried to use early_stopping_rounds. I search for documentation or some comments in the source code but I couldn't find any for monitors.</p>