[MADLIB-1322] MLP with minibatch fails for integer dependent variable on PostgreSQL - ASF JIRA

Details

Type: Bug
Status: Closed
Priority: Minor
Resolution: Won't Fix
Affects Version/s: None
Fix Version/s: v1.16
Component/s: Module: Neural Networks
Labels:
None

Description

Fails on postgres 9.6. On Greenplum it does not fail as far as I know.

DROP TABLE IF EXISTS iris_data;
CREATE TABLE iris_data(
    id serial,
    attributes numeric[],
    class_text varchar,
    class integer,
    state varchar
);
INSERT INTO iris_data(id, attributes, class_text, class, state) VALUES
(1,ARRAY[5.0,3.2,1.2,0.2],'Iris_setosa',1,'Alaska'),
(2,ARRAY[5.5,3.5,1.3,0.2],'Iris_setosa',1,'Alaska'),
(3,ARRAY[4.9,3.1,1.5,0.1],'Iris_setosa',1,'Alaska'),
(4,ARRAY[4.4,3.0,1.3,0.2],'Iris_setosa',1,'Alaska'),
(5,ARRAY[5.1,3.4,1.5,0.2],'Iris_setosa',1,'Alaska'),
(6,ARRAY[5.0,3.5,1.3,0.3],'Iris_setosa',1,'Alaska'),
(7,ARRAY[4.5,2.3,1.3,0.3],'Iris_setosa',1,'Alaska'),
(8,ARRAY[4.4,3.2,1.3,0.2],'Iris_setosa',1,'Alaska'),
(9,ARRAY[5.0,3.5,1.6,0.6],'Iris_setosa',1,'Alaska'),
(10,ARRAY[5.1,3.8,1.9,0.4],'Iris_setosa',1,'Alaska'),
(11,ARRAY[4.8,3.0,1.4,0.3],'Iris_setosa',1,'Alaska'),
(12,ARRAY[5.1,3.8,1.6,0.2],'Iris_setosa',1,'Alaska'),
(13,ARRAY[5.7,2.8,4.5,1.3],'Iris_versicolor',2,'Alaska'),
(14,ARRAY[6.3,3.3,4.7,1.6],'Iris_versicolor',2,'Alaska'),
(15,ARRAY[4.9,2.4,3.3,1.0],'Iris_versicolor',2,'Alaska'),
(16,ARRAY[6.6,2.9,4.6,1.3],'Iris_versicolor',2,'Alaska'),
(17,ARRAY[5.2,2.7,3.9,1.4],'Iris_versicolor',2,'Alaska'),
(18,ARRAY[5.0,2.0,3.5,1.0],'Iris_versicolor',2,'Alaska'),
(19,ARRAY[5.9,3.0,4.2,1.5],'Iris_versicolor',2,'Alaska'),
(20,ARRAY[6.0,2.2,4.0,1.0],'Iris_versicolor',2,'Alaska'),
(21,ARRAY[6.1,2.9,4.7,1.4],'Iris_versicolor',2,'Alaska'),
(22,ARRAY[5.6,2.9,3.6,1.3],'Iris_versicolor',2,'Alaska'),
(23,ARRAY[6.7,3.1,4.4,1.4],'Iris_versicolor',2,'Alaska'),
(24,ARRAY[5.6,3.0,4.5,1.5],'Iris_versicolor',2,'Alaska'),
(25,ARRAY[5.8,2.7,4.1,1.0],'Iris_versicolor',2,'Alaska'),
(26,ARRAY[6.2,2.2,4.5,1.5],'Iris_versicolor',2,'Alaska'),
(27,ARRAY[5.6,2.5,3.9,1.1],'Iris_versicolor',2,'Alaska'),
(28,ARRAY[5.0,3.4,1.5,0.2],'Iris_setosa',1,'Tennessee'),
(29,ARRAY[4.4,2.9,1.4,0.2],'Iris_setosa',1,'Tennessee'),
(30,ARRAY[4.9,3.1,1.5,0.1],'Iris_setosa',1,'Tennessee'),
(31,ARRAY[5.4,3.7,1.5,0.2],'Iris_setosa',1,'Tennessee'),
(32,ARRAY[4.8,3.4,1.6,0.2],'Iris_setosa',1,'Tennessee'),
(33,ARRAY[4.8,3.0,1.4,0.1],'Iris_setosa',1,'Tennessee'),
(34,ARRAY[4.3,3.0,1.1,0.1],'Iris_setosa',1,'Tennessee'),
(35,ARRAY[5.8,4.0,1.2,0.2],'Iris_setosa',1,'Tennessee'),
(36,ARRAY[5.7,4.4,1.5,0.4],'Iris_setosa',1,'Tennessee'),
(37,ARRAY[5.4,3.9,1.3,0.4],'Iris_setosa',1,'Tennessee'),
(38,ARRAY[6.0,2.9,4.5,1.5],'Iris_versicolor',2,'Tennessee'),
(39,ARRAY[5.7,2.6,3.5,1.0],'Iris_versicolor',2,'Tennessee'),
(40,ARRAY[5.5,2.4,3.8,1.1],'Iris_versicolor',2,'Tennessee'),
(41,ARRAY[5.5,2.4,3.7,1.0],'Iris_versicolor',2,'Tennessee'),
(42,ARRAY[5.8,2.7,3.9,1.2],'Iris_versicolor',2,'Tennessee'),
(43,ARRAY[6.0,2.7,5.1,1.6],'Iris_versicolor',2,'Tennessee'),
(44,ARRAY[5.4,3.0,4.5,1.5],'Iris_versicolor',2,'Tennessee'),
(45,ARRAY[6.0,3.4,4.5,1.6],'Iris_versicolor',2,'Tennessee'),
(46,ARRAY[6.7,3.1,4.7,1.5],'Iris_versicolor',2,'Tennessee'),
(47,ARRAY[6.3,2.3,4.4,1.3],'Iris_versicolor',2,'Tennessee'),
(48,ARRAY[5.6,3.0,4.1,1.3],'Iris_versicolor',2,'Tennessee'),
(49,ARRAY[5.5,2.5,4.0,1.3],'Iris_versicolor',2,'Tennessee'),
(50,ARRAY[5.5,2.6,4.4,1.2],'Iris_versicolor',2,'Tennessee'),
(51,ARRAY[6.1,3.0,4.6,1.4],'Iris_versicolor',2,'Tennessee'),
(52,ARRAY[5.8,2.6,4.0,1.2],'Iris_versicolor',2,'Tennessee');

Works OK if dependent variable is TEXT:

DROP TABLE IF EXISTS iris_data_packed, iris_data_packed_summary, iris_data_packed_standardization;
SELECT madlib.minibatch_preprocessor('iris_data',         -- Source table
                                     'iris_data_packed',  -- Output table
                                     'class_text',        -- Dependent variable TEXT
                                     'attributes'        -- Independent variables
                                    );

\d+ iris_data_packed
                               Table "public.iris_data_packed"
       Column        |        Type        | Modifiers | Storage  | Stats target | Description 
---------------------+--------------------+-----------+----------+--------------+-------------
 __id__              | bigint             |           | plain    |              | 
 dependent_varname   | double precision[] |           | extended |              | 
 independent_varname | double precision[] |           | extended |              | 


DROP TABLE IF EXISTS mlp_model, mlp_model_summary, mlp_model_standardization;
-- Set seed so results are reproducible
SELECT setseed(0);
SELECT madlib.mlp_classification(
    'iris_data_packed',      -- Output table from mini-batch preprocessor
    'mlp_model',             -- Destination table
    'independent_varname',   -- Hardcode to this, from table iris_data_packed
    'dependent_varname',     -- Hardcode to this, from table iris_data_packed
    ARRAY[5],                -- Number of units per layer
    'learning_rate_init=0.1,
    n_iterations=5,
    tolerance=0',            -- Optimizer params
    'tanh',                  -- Activation function
    NULL,                    -- Default weight (1)
    FALSE,                   -- No warm start
    TRUE                    -- Not verbose
);

INFO:  Iteration: 1, Loss: <0.990848103579>
INFO:  Iteration: 2, Loss: <0.852423978558>
INFO:  Iteration: 3, Loss: <0.689764103374>
INFO:  Iteration: 4, Loss: <0.530458765792>
 mlp_classification 
--------------------
 
(1 row)

Does not work if dependent variable is INTEGER:

DROP TABLE IF EXISTS iris_data_packed, iris_data_packed_summary, iris_data_packed_standardization;
SELECT madlib.minibatch_preprocessor('iris_data',         -- Source table
                                     'iris_data_packed',  -- Output table
                                     'class',        -- Dependent variable INTEGER
                                     'attributes',        -- Independent variables
                                     NULL, -- grouping
                                     NULL, -- buffer size (or size of the mini-batch)
                                     TRUE -- Encode scalar int dependent variable
                                     );

\d+ iris_data_packed
                               Table "public.iris_data_packed"
       Column        |        Type        | Modifiers | Storage  | Stats target | Description 
---------------------+--------------------+-----------+----------+--------------+-------------
 __id__              | bigint             |           | plain    |              | 
 dependent_varname   | double precision[] |           | extended |              | 
 independent_varname | double precision[] |           | extended |              | 


DROP TABLE IF EXISTS mlp_model, mlp_model_summary, mlp_model_standardization;
-- Set seed so results are reproducible
SELECT setseed(0);
SELECT madlib.mlp_classification(
    'iris_data_packed',      -- Output table from mini-batch preprocessor
    'mlp_model',             -- Destination table
    'independent_varname',   -- Hardcode to this, from table iris_data_packed
    'dependent_varname',     -- Hardcode to this, from table iris_data_packed
    ARRAY[5],                -- Number of units per layer
    'learning_rate_init=0.1,
    n_iterations=10,
    tolerance=0',            -- Optimizer params
    'tanh',                  -- Activation function
    NULL,                    -- Default weight (1)
    FALSE,                   -- No warm start
    TRUE                    -- Not verbose
);

ERROR:  TypeError: must be string, not int
CONTEXT:  Traceback (most recent call last):
  PL/Python function "mlp_classification", line 33, in <module>
    grouping_col)
  PL/Python function "mlp_classification", line 42, in wrapper
  PL/Python function "mlp_classification", line 147, in mlp
  PL/Python function "mlp_classification", line 74, in quote_literal
PL/Python function "mlp_classification"

MLP with minibatch fails for integer dependent variable on PostgreSQL

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