skflow

I have a basic input_fn that can be used with Tensorflow Estimators below. It works flawlessly without setting the num_epochs parameter; the obtained tensor has a discrete shape. Pass in num_epochs as anything other than None results in an unknown shape. My issue lies with constructing sparse tensors whilst using num_epochs ; I cannot figure out how to generically create said tensors without knowing the shape of the input tensor. Can anyone think of a solution to this problem? I'd like to be able to pass num_epochs=1 to be able to evaluate only 1 time over the data set, as well as to pass to

Using the following with TF .9.0rc0 on 60,000 (train) and 26,000 (test) on or so records with 145 coded columns (1,0) trying to predict 1 or 0 for class identification.. classifier_TensorFlow = learn.TensorFlowDNNClassifier(hidden_units=[10, 20, 10],n_classes=2, steps=100) classifier_TensorFlow.fit(X_train, y_train.ravel()) I get: WARNING:tensorflow:TensorFlowDNNClassifier class is deprecated. Please consider using DNNClassifier as an alternative. Out[34]:TensorFlowDNNClassifier(steps=100, batch_size=32) And then good results quite fast: score = metrics.accuracy_score(y_test, classifier

Summary : Using the new tf.contrib.data.Dataset doubles the size of my graph protobuff file and I'm unable to visualize the graph in Tensorboard. The details: I'm trying out the new TensorFlow tf.contrib.data.Dataset functionality together with the tf.contrib.learn.Experiment framework. My input data is defined as input functions which return tensors of features and labels. If I create my input function with the tf.train.slice_input_producer function like in the following codeblock (full code here ), then my resulting graph.pbtxt file is 620M and the .meta files are around 165M in size. def

I am creating neural nets with Tensorflow and skflow ; for some reason I want to get the values of some inner tensors for a given input, so I am using myClassifier.get_layer_value(input, "tensorName") , myClassifier being a skflow.estimators.TensorFlowEstimator . However, I find it difficult to find the correct syntax of the tensor name, even knowing its name (and I'm getting confused between operation and tensors), so I'm using tensorboard to plot the graph and look for the name. Is there a way to enumerate all the tensors in a graph without using tensorboard? You can do [n.name for n in tf