Modification of code to account for different features

[Vincent9797]

Hi,

I am trying to put a tensorflow Estimator class into production. My features are in the form of this: { "input_ids": tf.constant( features[0].input_ids, shape=[1, 128], dtype=tf.int32), "input_mask": tf.constant( features[0].input_mask, shape=[1, 128], dtype=tf.int32), "segment_ids": tf.constant( features[0].segment_ids, shape=[1, 128], dtype=tf.int32), "label_ids": tf.constant(features[0].label_id, shape=[1], dtype=tf.int32), }

When I tried to edit the code for queued_predict_input_fn for the threaded classifier, I am unsure of what to assign output_types to.

When I tried to assign it as tensors, it gave me this error:

TypeError: Cannot convert value <tf.Tensor 'Const:0' shape=(1, 128) dtype=int32> to a TensorFlow DType.