PREDICT_TENSORFLOW

Applies a TensorFlow model on an input relation, and returns with the result expected for the encoded model type.

Syntax

PREDICT_TENSORFLOW ( input‑columns
        USING PARAMETERS model_name = 'model‑name' [, num_passthru_cols = 'n-first-columns-to-ignore'] )
OVER( [window-partition-clause] )

Arguments

input‑columns Comma-separated list of columns to use from the input relation, or asterisk (*) to select all columns.

Parameters

model_name Name of the model (case-insensitive).
num_passthru_cols Integer that specifies the number of input columns to skip.

Examples

Use PREDICT_TENSORFLOW with the num_passthru_cols parameter to skip the first two input columns:

SELECT PREDICT_TENSORFLOW ( pid,label,x1,x2
        USING PARAMETERS model_name='spiral_demo', num_passthru_cols=2 )
OVER(PARTITION BEST) as predicted_class FROM points;
 
--example output, the skipped columns are displayed as the first columns of the output
  pid  | label |         col0         |         col1
-------+-------+----------------------+----------------------
     0 |     0 |    0.990638732910156 |  0.00936129689216614
     1 |     0 |    0.999036073684692 | 0.000963933940511197
     2 |     1 |   0.0103802494704723 | 0.989619791507721

See Also