Training with mixed-precision using the tensorflow estimator api
I found the issue: I used tf.get_variable to store the learning rate. This variable has no gradient. Normal optimizers do not care, but tf.contrib.mixed_precision.LossScaleOptimizer crashes. Therefore, make sure these variables are not added to tf.GraphKeys.TRAINABLE_VARIABLES.
Does anyone has experience with mixed-precision training using the tensorflow estimator api? 
I tried casting my inputs to tf.float16 and the results of the network back to tf.float32. For scaling the loss I used tf.contrib.mixed_precision.LossScaleOptimizer.
The error messages I get are relatively uninformative: "Tried to convert 'x' to a tensor and failed. Error: None values not supported",