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Posted to commits@madlib.apache.org by ok...@apache.org on 2020/03/10 23:33:38 UTC
[madlib] branch master updated: DL: Use pg_temp instead of public
schema for dev-check
This is an automated email from the ASF dual-hosted git repository.
okislal pushed a commit to branch master
in repository https://gitbox.apache.org/repos/asf/madlib.git
The following commit(s) were added to refs/heads/master by this push:
new 404e623 DL: Use pg_temp instead of public schema for dev-check
404e623 is described below
commit 404e62381248f81f84ec6032a86e67c9b215d620
Author: Orhan Kislal <ok...@apache.org>
AuthorDate: Fri Mar 6 13:22:28 2020 -0500
DL: Use pg_temp instead of public schema for dev-check
JIRA: MADLIB-1417
This commit alters the schema names from public to pg_temp for the
tests changed by the following commit:
c69ac53848a8f4c3e927bd048be0d35cf0dfb253
Closes #487
---
.../test/madlib_keras_model_averaging_e2e.sql_in | 22 +++++------
.../test/madlib_keras_model_selection_e2e.sql_in | 34 ++++++++--------
.../test/madlib_keras_transfer_learning.sql_in | 46 +++++++++++-----------
3 files changed, 52 insertions(+), 50 deletions(-)
diff --git a/src/ports/postgres/modules/deep_learning/test/madlib_keras_model_averaging_e2e.sql_in b/src/ports/postgres/modules/deep_learning/test/madlib_keras_model_averaging_e2e.sql_in
index 658edd2..bbb757b 100644
--- a/src/ports/postgres/modules/deep_learning/test/madlib_keras_model_averaging_e2e.sql_in
+++ b/src/ports/postgres/modules/deep_learning/test/madlib_keras_model_averaging_e2e.sql_in
@@ -29,10 +29,10 @@ m4_include(`SQLCommon.m4')
m4_changequote(`<!', `!>')
m4_ifdef(<!__POSTGRESQL__!>, <!!>, <!
-- Multiple models End-to-End test
-DROP TABLE if exists iris_model, iris_model_summary;
+DROP TABLE if exists pg_temp.iris_model, pg_temp.iris_model_summary;
SELECT madlib_keras_fit(
'iris_data_packed',
- 'public.iris_model',
+ 'pg_temp.iris_model',
'iris_model_arch',
1,
$$loss='categorical_crossentropy', optimizer='Adam(lr=0.01)', metrics=['accuracy']$$,
@@ -45,7 +45,7 @@ SELECT assert(
model_arch_table = 'iris_model_arch' AND
validation_table is NULL AND
source_table = 'iris_data_packed' AND
- model = 'public.iris_model' AND
+ model = 'pg_temp.iris_model' AND
dependent_varname = 'class_text' AND
independent_varname = 'attributes' AND
madlib_version is NOT NULL AND
@@ -57,31 +57,31 @@ SELECT assert(
dependent_vartype LIKE '%char%' AND
normalizing_const = 1,
'Keras Fit Multiple Output Summary Validation failed. Actual:' || __to_char(summary))
-FROM (SELECT * FROM public.iris_model_summary) summary;
+FROM (SELECT * FROM pg_temp.iris_model_summary) summary;
-- Run Predict
-DROP TABLE IF EXISTS public.iris_predict;
+DROP TABLE IF EXISTS pg_temp.iris_predict;
SELECT madlib_keras_predict(
- 'public.iris_model',
+ 'pg_temp.iris_model',
'iris_data',
'id',
'attributes',
- 'public.iris_predict',
+ 'pg_temp.iris_predict',
'prob',
FALSE);
-- Run Evaluate
-DROP TABLE IF EXISTS public.evaluate_out;
+DROP TABLE IF EXISTS pg_temp.evaluate_out;
SELECT madlib_keras_evaluate(
- 'public.iris_model',
+ 'pg_temp.iris_model',
'iris_data_val',
- 'public.evaluate_out',
+ 'pg_temp.evaluate_out',
FALSE);
SELECT assert(loss >= 0 AND
metric >= 0 AND
metrics_type = '{accuracy}', 'Evaluate output validation failed. Actual:' || __to_char(evaluate_out))
-FROM public.evaluate_out;
+FROM pg_temp.evaluate_out;
-- Test for one-hot encoded user input data
DROP TABLE if exists iris_model, iris_model_summary, iris_model_info;
diff --git a/src/ports/postgres/modules/deep_learning/test/madlib_keras_model_selection_e2e.sql_in b/src/ports/postgres/modules/deep_learning/test/madlib_keras_model_selection_e2e.sql_in
index 4995aed..43f08d0 100644
--- a/src/ports/postgres/modules/deep_learning/test/madlib_keras_model_selection_e2e.sql_in
+++ b/src/ports/postgres/modules/deep_learning/test/madlib_keras_model_selection_e2e.sql_in
@@ -30,10 +30,10 @@ m4_changequote(`<!', `!>')
m4_ifdef(<!__POSTGRESQL__!>, <!!>, <!
-- Multiple models End-to-End test
-- Prepare model selection table with four rows
-DROP TABLE IF EXISTS mst_table, mst_table_summary;
+DROP TABLE IF EXISTS pg_temp.mst_table, pg_temp.mst_table_summary;
SELECT load_model_selection_table(
'iris_model_arch',
- 'public.mst_table',
+ 'pg_temp.mst_table',
ARRAY[1],
ARRAY[
$$loss='categorical_crossentropy', optimizer='Adam(lr=0.01)', metrics=['accuracy']$$,
@@ -45,11 +45,13 @@ SELECT load_model_selection_table(
]
);
-DROP TABLE if exists iris_multiple_model, iris_multiple_model_summary, iris_multiple_model_info;
+DROP TABLE if exists pg_temp.iris_multiple_model,
+ pg_temp.iris_multiple_model_summary,
+ pg_temp.iris_multiple_model_info;
SELECT madlib_keras_fit_multiple_model(
'iris_data_packed',
- 'public.iris_multiple_model',
- 'public.mst_table',
+ 'pg_temp.iris_multiple_model',
+ 'pg_temp.mst_table',
3,
FALSE
);
@@ -57,9 +59,9 @@ SELECT madlib_keras_fit_multiple_model(
SELECT assert(
model_arch_table = 'iris_model_arch' AND
validation_table is NULL AND
- model_info = 'public.iris_multiple_model_info' AND
+ model_info = 'pg_temp.iris_multiple_model_info' AND
source_table = 'iris_data_packed' AND
- model = 'public.iris_multiple_model' AND
+ model = 'pg_temp.iris_multiple_model' AND
dependent_varname = 'class_text' AND
independent_varname = 'attributes' AND
madlib_version is NOT NULL AND
@@ -71,40 +73,40 @@ SELECT assert(
dependent_vartype LIKE '%char%' AND
normalizing_const = 1,
'Keras Fit Multiple Output Summary Validation failed. Actual:' || __to_char(summary))
-FROM (SELECT * FROM public.iris_multiple_model_summary) summary;
+FROM (SELECT * FROM pg_temp.iris_multiple_model_summary) summary;
-- Run Predict
-DROP TABLE IF EXISTS public.iris_predict;
+DROP TABLE IF EXISTS pg_temp.iris_predict;
SELECT madlib_keras_predict(
- 'public.iris_multiple_model',
+ 'pg_temp.iris_multiple_model',
'iris_data',
'id',
'attributes',
- 'public.iris_predict',
+ 'pg_temp.iris_predict',
'prob',
NULL,
1);
-- Run Evaluate
-DROP TABLE IF EXISTS public.evaluate_out;
+DROP TABLE IF EXISTS pg_temp.evaluate_out;
SELECT madlib_keras_evaluate(
- 'public.iris_multiple_model',
+ 'pg_temp.iris_multiple_model',
'iris_data_val',
- 'public.evaluate_out',
+ 'pg_temp.evaluate_out',
NULL,
1);
SELECT assert(loss >= 0 AND
metric >= 0 AND
metrics_type = '{accuracy}', 'Evaluate output validation failed. Actual:' || __to_char(evaluate_out))
-FROM public.evaluate_out;
+FROM pg_temp.evaluate_out;
-- Test for one-hot encoded user input data
DROP TABLE if exists iris_multiple_model, iris_multiple_model_summary, iris_multiple_model_info;
SELECT madlib_keras_fit_multiple_model(
'iris_data_one_hot_encoded_packed',
'iris_multiple_model',
- 'public.mst_table',
+ 'pg_temp.mst_table',
3,
FALSE
);
diff --git a/src/ports/postgres/modules/deep_learning/test/madlib_keras_transfer_learning.sql_in b/src/ports/postgres/modules/deep_learning/test/madlib_keras_transfer_learning.sql_in
index 92f2277..c73fc74 100644
--- a/src/ports/postgres/modules/deep_learning/test/madlib_keras_transfer_learning.sql_in
+++ b/src/ports/postgres/modules/deep_learning/test/madlib_keras_transfer_learning.sql_in
@@ -26,9 +26,9 @@ m4_include(`SQLCommon.m4')
`\1../../modules/deep_learning/test/madlib_keras_iris.setup.sql_in'
)
-DROP TABLE IF EXISTS iris_model, iris_model_summary;
+DROP TABLE IF EXISTS pg_temp.iris_model, pg_temp.iris_model_summary;
SELECT madlib_keras_fit('iris_data_packed', -- source table
- 'iris_model', -- model output table
+ 'pg_temp.iris_model', -- model output table
'iris_model_arch', -- model arch table
1, -- model arch id
$$ loss='categorical_crossentropy', optimizer='adam', metrics=['accuracy'] $$, -- compile_params
@@ -45,21 +45,21 @@ SELECT assert(
array_upper(training_loss, 1) = 5 AND
array_upper(training_metrics, 1) = 5,
'metrics compute frequency must be 1.')
-FROM iris_model_summary;
+FROM pg_temp.iris_model_summary;
SELECT assert(
training_loss[5]-training_loss[1] < 0.1 AND
training_metrics[5]-training_metrics[1] > -0.1,
'The loss and accuracy should have improved with more iterations.'
)
-FROM iris_model_summary;
+FROM pg_temp.iris_model_summary;
-- Make a copy of the loss and metrics array, to compare it with runs after
-- warm start and transfer learning.
DROP TABLE IF EXISTS iris_model_first_run;
CREATE TABLE iris_model_first_run AS
SELECT training_loss_final, training_metrics_final
-FROM iris_model_summary;
+FROM pg_temp.iris_model_summary;
-- Copy weights that were learnt from the previous run, for transfer
-- learning. Copy it now, because using warm_start will overwrite it.
@@ -67,7 +67,7 @@ UPDATE iris_model_arch set model_weights = (select model_weights from iris_model
-- Warm start test
SELECT madlib_keras_fit('iris_data_packed', -- source table
- 'iris_model', -- model output table
+ 'pg_temp.iris_model', -- model output table
'iris_model_arch', -- model arch table
2, -- model arch id
$$ loss='categorical_crossentropy', optimizer='adam', metrics=['accuracy'] $$, -- compile_params
@@ -81,7 +81,7 @@ SELECT assert(
array_upper(training_loss, 1) = 2 AND
array_upper(training_metrics, 1) = 2,
'metrics compute frequency must be 1.')
-FROM iris_model_summary;
+FROM pg_temp.iris_model_summary;
SELECT assert(
abs(first.training_loss_final-second.training_loss[1]) < 1e-6 AND
@@ -89,12 +89,12 @@ SELECT assert(
abs(first.training_metrics_final-second.training_metrics[1]) < 1e-10 AND
abs(first.training_metrics_final-second.training_metrics[2]) < 1e-10,
'warm start test failed because training loss and metrics don''t match the expected value from the previous run of keras fit.')
-FROM iris_model_first_run AS first, iris_model_summary AS second;
+FROM iris_model_first_run AS first, pg_temp.iris_model_summary AS second;
-- Transfer learning test
DROP TABLE IF EXISTS iris_model_transfer, iris_model_transfer_summary;
SELECT madlib_keras_fit('iris_data_packed', -- source table
- 'iris_model_transfer', -- model output table
+ 'pg_temp.iris_model_transfer', -- model output table
'iris_model_arch', -- model arch table
2, -- model arch id
$$ loss='categorical_crossentropy', optimizer='adam', metrics=['accuracy'] $$, -- compile_params
@@ -107,7 +107,7 @@ SELECT assert(
array_upper(training_loss, 1) = 2 AND
array_upper(training_metrics, 1) = 2,
'metrics compute frequency must be 1.')
-FROM iris_model_transfer_summary;
+FROM pg_temp.iris_model_transfer_summary;
SELECT assert(
abs(first.training_loss_final-second.training_loss[1]) < 1e-6 AND
@@ -139,11 +139,11 @@ SELECT load_model_selection_table(
]
);
-DROP TABLE if exists iris_multiple_model, iris_multiple_model_summary, iris_multiple_model_info;
+DROP TABLE if exists pg_temp.iris_multiple_model, pg_temp.iris_multiple_model_summary, pg_temp.iris_multiple_model_info;
SELECT setseed(0);
SELECT madlib_keras_fit_multiple_model(
'iris_data_packed',
- 'iris_multiple_model',
+ 'pg_temp.iris_multiple_model',
'mst_table',
3,
FALSE, NULL, 1
@@ -153,12 +153,12 @@ DROP TABLE IF EXISTS iris_model_first_run;
CREATE TABLE iris_model_first_run AS
SELECT mst_key, model_id, training_loss, training_metrics,
training_loss_final, training_metrics_final
-FROM iris_multiple_model_info;
+FROM pg_temp.iris_multiple_model_info;
-- warm start for fit multiple model
SELECT madlib_keras_fit_multiple_model(
'iris_data_packed',
- 'iris_multiple_model',
+ 'pg_temp.iris_multiple_model',
'mst_table',
3,
FALSE,
@@ -170,7 +170,7 @@ SELECT assert(
array_upper(training_loss, 1) = 3 AND
array_upper(training_metrics, 1) = 3,
'metrics compute frequency must be 1.')
-FROM iris_multiple_model_info;
+FROM pg_temp.iris_multiple_model_info;
SELECT assert(
abs(first.training_loss_final-second.training_loss[1]) < 1e-6 AND
@@ -178,7 +178,7 @@ SELECT assert(
abs(first.training_metrics_final-second.training_metrics[1]) < 1e-10 AND
abs(first.training_metrics_final-second.training_metrics[2]) < 1e-10,
'warm start test failed because training loss and metrics don''t match the expected value from the previous run of keras fit.')
-FROM iris_model_first_run AS first, iris_multiple_model_info AS second
+FROM iris_model_first_run AS first, pg_temp.iris_multiple_model_info AS second
WHERE first.mst_key = second.mst_key AND first.model_id = 2;
-- warm start with different mst tables
@@ -298,30 +298,30 @@ SELECT load_model_selection_table(
]
);
-DROP TABLE if exists iris_multiple_model, iris_multiple_model_summary, iris_multiple_model_info;
+DROP TABLE if exists pg_temp.iris_multiple_model, pg_temp.iris_multiple_model_summary, pg_temp.iris_multiple_model_info;
SELECT setseed(0);
SELECT madlib_keras_fit_multiple_model(
'iris_data_packed',
- 'iris_multiple_model',
+ 'pg_temp.iris_multiple_model',
'mst_table',
3,
FALSE, NULL, 1
);
UPDATE iris_model_arch
-SET model_weights = (SELECT model_weights FROM iris_multiple_model WHERE mst_key=1)
+SET model_weights = (SELECT model_weights FROM pg_temp.iris_multiple_model WHERE mst_key=1)
WHERE model_id = 1;
DROP TABLE IF EXISTS iris_model_first_run;
CREATE TABLE iris_model_first_run AS
SELECT mst_key, model_id, training_loss, training_metrics,
training_loss_final, training_metrics_final
-FROM iris_multiple_model_info;
+FROM pg_temp.iris_multiple_model_info;
-DROP TABLE if exists iris_multiple_model, iris_multiple_model_summary, iris_multiple_model_info;
+DROP TABLE if exists pg_temp.iris_multiple_model, pg_temp.iris_multiple_model_summary, pg_temp.iris_multiple_model_info;
SELECT madlib_keras_fit_multiple_model(
'iris_data_packed',
- 'iris_multiple_model',
+ 'pg_temp.iris_multiple_model',
'mst_table',
3,
FALSE, NULL, 1
@@ -330,6 +330,6 @@ SELECT madlib_keras_fit_multiple_model(
SELECT assert(
(first.training_loss_final-second.training_loss_final) > 1e-6,
'Transfer learning test failed because training loss and metrics don''t match the expected value.')
-FROM iris_model_first_run AS first, iris_multiple_model_info AS second
+FROM iris_model_first_run AS first, pg_temp.iris_multiple_model_info AS second
WHERE first.mst_key = second.mst_key AND first.model_id = 1;
!>)