I have read all the guides, videos, and everything, but I have no idea how to convert my feature set to an ELWC datasheet format for TF-Rank ListWise problem. There is no description of this structure.
For example, a students profile is:
Student ID age grade math% physics% english% art% math_competit language_competit Rank 14588 16 k12 98 67 88 100 first_place very_good 5 If I have 20 students in the same class, how can I transform this data to be able to make a listwise prediction for every grade ( theoretically in every grade has 3 class with 20 students)
1 Answer
ELWC format requires 'context' and 'example features'. Example features are features that are different for every item in a query list. Context features are ones which are dependent only on the query. Therefore, every query will have a list of features for every item in the list (the Example features), and a single list of features for Context features.
To convert to ELWC format, start by gathering all the items for a given query. The code below shows a query with two items along with some context information. Use input_pb2.ExampleListWithContext() to create an instance of a ELWC formatter. Then all you have to do is feed in the context and examples.
Save using TFRecordWriter.
from tensorflow_serving.apis import input_pb2 import tensorflow as tf def _float_feature(value): return tf.train.Feature(float_list=tf.train.FloatList(value=[value])) def _int64_feature(value): return tf.train.Feature(int64_list=tf.train.Int64List(value=[value])) def _bytes_feature(value): return tf.train.Feature(bytes_list=tf.train.BytesList(value=[value])) context = { 'custom_features_1': _float_feature(1.0), 'utility': _int64_feature(1), } examples = [ { 'custom_features_1': _float_feature(1.0), 'custom_features_2': _float_feature(1.5), 'utility': _int64_feature(1), }, { 'custom_features_1': _float_feature(1.0), 'custom_features_2': _float_feature(2.1), 'utility': _int64_feature(0), } ] def to_example(dictionary): return tf.train.Example(features=tf.train.Features(feature=dictionary)) ELWC = input_pb2.ExampleListWithContext() ELWC.context.CopyFrom(to_example(context)) for expl in examples: example_features = ELWC.examples.add() example_features.CopyFrom(to_example(expl)) print(ELWC) 
