[jira] [Commented] (MADLIB-1290) Minibatch pre-processor for deep learning

[Frank McQuillan (JIRA)]

    [ 
https://issues.apache.org/jira/browse/MADLIB-1290?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=16767640#comment-16767640
 ] 

Frank McQuillan commented on MADLIB-1290:
-----------------------------------------

In my testing this seems mostly OK, the only issue I found is that NULL is not 
being handled properly for the input parameter "normalizing_const"

{code}
DROP TABLE IF EXISTS image_data;

CREATE TABLE image_data AS (
SELECT ARRAY[
        (random() * 256)::integer, -- R values
        (random() * 256)::integer,
        (random() * 256)::integer,
        (random() * 256)::integer,
        (random() * 256)::integer, -- G values
        (random() * 256)::integer,
        (random() * 256)::integer,
        (random() * 256)::integer,
        (random() * 256)::integer, -- B values
        (random() * 256)::integer,
        (random() * 256)::integer,
        (random() * 256)::integer
    ] as rgb, ('{cat,dog,bird}'::text[])[ceil(random()*3)] as species
FROM generate_series(1, 52)
);
{code}

{code}
DROP TABLE IF EXISTS image_data_packed, image_data_packed_summary;
SELECT madlib.minibatch_preprocessor_dl('image_data',       -- Source table
                                        'image_data_packed', -- Output table
                                        'species',            -- Dependent 
variable
                                        'rgb',                -- Independent 
variable
                                        NULL,                 -- Buffer size
                                        NULL,                  -- Normalizing 
constant
                                        -1                   -- Dependent 
variable offset
                                        );
SELECT * FROM image_data_packed ORDER BY buffer_id;
{code}

produces error

{code}
ERROR:  plpy.SPIError: column "none" does not exist
LINE 4:                 rgb::REAL[], (1/None)::REAL) AS x_norm,
                                        ^
QUERY:  
            CREATE TEMP TABLE 
__madlib_temp_normalized79323135_1550096173_57808848__ AS
            SELECT madlib.array_scalar_mult(
                rgb::REAL[], (1/None)::REAL) AS x_norm,
                species + -1 AS y,
                row_number() over() AS row_id
            FROM image_data
        
CONTEXT:  Traceback (most recent call last):
  PL/Python function "minibatch_preprocessor_dl", line 24, in <module>
    minibatch_preprocessor_obj.minibatch_preprocessor_dl()
  PL/Python function "minibatch_preprocessor_dl", line 93, in 
minibatch_preprocessor_dl
PL/Python function "minibatch_preprocessor_dl"
{code}






> Minibatch pre-processor for deep learning
> -----------------------------------------
>
>                 Key: MADLIB-1290
>                 URL: https://issues.apache.org/jira/browse/MADLIB-1290
>             Project: Apache MADlib
>          Issue Type: New Feature
>          Components: Deep Learning
>            Reporter: Frank McQuillan
>            Assignee: Nandish Jayaram
>            Priority: Major
>             Fix For: v1.16
>
>
> The minibatch preprocessor we currently have in MADlib is bloated for DL
> tasks. This feature adds a simplified version of creating buffers, and
> divides each element of the independent array by a normalizing constant
> for standardization (which is 255.0 by default). This is standard practice
> with image data.



--
This message was sent by Atlassian JIRA
(v7.6.3#76005)