Tensorflow Prediction in Bigquery Softmax


I have a multiclass classification TensorFlow model imported into GCP BigQuery. When you make predictions, the output is the probabilities which is a type FLOAT (the probabilities) and a mode REPEATED. What is the best way to get the index of the max value using SQL in BigQuery?


If you want to find an index of max value from an array, using an UDF would be handy, I think.

CREATE TEMP FUNCTION index_of_max(probabilites ARRAY<FLOAT64>) AS ((
  SELECT i FROM UNNEST(probabilites) p WITH OFFSET i 
   WHERE p = (SELECT MAX(p) FROM UNNEST(probabilites) p)

SELECT index_of_max(dense_1) index_of_max FROM UNNEST([
  STRUCT([0.8611106872558594, 0.06648489832878113, 0.07240447402000427] AS dense_1),
  STRUCT([0.6251607537269592, 0.2989124655723572, 0.07592668384313583]),
  STRUCT([0.01427623350173235, 0.972910463809967, 0.01281337533146143])


enter image description here

[note] zero-based index

If applied to below example,

 SELECT dense_1, index_of_max(dense_1) AS index_of_max
          MODEL `testset_us.imported_tf_model`,
          (SELECT title AS input FROM `bigquery-public-data.hacker_news.stories`)

enter image description here

Answered By – Jaytiger

This Answer collected from stackoverflow, is licensed under cc by-sa 2.5 , cc by-sa 3.0 and cc by-sa 4.0

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