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okislal pushed a commit to branch master
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new 828c265 DL: Enable transfer learning for multi model training
828c265 is described below
commit 828c2651bd487e4a76aaaa0e174813ef00d70c60
Author: Orhan Kislal <[email protected]>
AuthorDate: Mon Nov 4 20:15:18 2019 -0500
DL: Enable transfer learning for multi model training
JIRA: MADLIB-1389
This commit enables transfer learning for multi-model training by
copying the weights from the model arch table.
---
.../madlib_keras_fit_multiple_model.py_in | 4 +-
.../test/madlib_keras_iris.setup.sql_in | 1 +
.../test/madlib_keras_transfer_learning.sql_in | 93 ++++++++++++++++++++++
3 files changed, 97 insertions(+), 1 deletion(-)
diff --git
a/src/ports/postgres/modules/deep_learning/madlib_keras_fit_multiple_model.py_in
b/src/ports/postgres/modules/deep_learning/madlib_keras_fit_multiple_model.py_in
index c3b9aad..6e3389c 100644
---
a/src/ports/postgres/modules/deep_learning/madlib_keras_fit_multiple_model.py_in
+++
b/src/ports/postgres/modules/deep_learning/madlib_keras_fit_multiple_model.py_in
@@ -286,7 +286,9 @@ class FitMultipleModel():
)
model = model_from_json(model_arch)
- serialized_state =
madlib_keras_serializer.serialize_nd_weights(model.get_weights())
+ serialized_state = model_weights if model_weights else \
+
madlib_keras_serializer.serialize_nd_weights(model.get_weights())
+
model_size = sys.getsizeof(serialized_weights) / 1024.0
metrics_list = get_metrics_from_compile_param(
mst[self.compile_params_col])
diff --git
a/src/ports/postgres/modules/deep_learning/test/madlib_keras_iris.setup.sql_in
b/src/ports/postgres/modules/deep_learning/test/madlib_keras_iris.setup.sql_in
index 7167c35..389efa3 100644
---
a/src/ports/postgres/modules/deep_learning/test/madlib_keras_iris.setup.sql_in
+++
b/src/ports/postgres/modules/deep_learning/test/madlib_keras_iris.setup.sql_in
@@ -180,6 +180,7 @@ INSERT INTO iris_data(id, attributes, class_text) VALUES
(150,ARRAY[5.9,3.0,5.1,1.8],'Iris-virginica');
+DROP TABLE IF EXISTS iris_data_one_hot_encoded;
CREATE TABLE iris_data_one_hot_encoded as select id, attributes,
ARRAY[class_text is not distinct from 'Iris-setosa', class_text is not distinct
from 'Iris-versicolor', class_text is not distinct from
'Iris-virginica']::int[] as class_one_hot_encoded
from iris_data;
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 7e400f1..220569d 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
@@ -19,6 +19,8 @@
*
*//* ---------------------------------------------------------------------*/
+m4_include(`SQLCommon.m4')
+
\i m4_regexp(MODULE_PATHNAME,
`\(.*\)libmadlib\.so',
`\1../../modules/deep_learning/test/madlib_keras_iris.setup.sql_in'
@@ -114,3 +116,94 @@ SELECT assert(
abs(first.training_metrics_final-second.training_metrics[2]) < 1e-10,
'Transfer learning test failed because training loss and metrics don''t
match the expected value.')
FROM iris_model_first_run AS first, iris_model_transfer_summary AS second;
+
+-- Rerun the iris setup to discard the changes
+\i m4_regexp(MODULE_PATHNAME,
+ `\(.*\)libmadlib\.so',
+
`\1../../modules/deep_learning/test/madlib_keras_iris.setup.sql_in'
+)
+
+m4_changequote(`<!', `!>')
+m4_ifdef(<!__POSTGRESQL__!>, <!!>, <!
+
+-- Load the same arch again so that we can compare transfer learning results
+SELECT load_keras_model('iris_model_arch', -- Output table,
+$$
+{
+"class_name": "Sequential",
+"keras_version": "2.1.6",
+"config":
+ [{"class_name": "Dense", "config": {"kernel_initializer": {"class_name":
"VarianceScaling",
+ "config": {"distribution": "uniform", "scale": 1.0, "seed": 0, "mode":
"fan_avg"}},
+ "name": "dense_1", "kernel_constraint": null, "bias_regularizer": null,
+ "bias_constraint": null, "dtype": "float32", "activation": "relu",
"trainable": true,
+ "kernel_regularizer": null, "bias_initializer": {"class_name": "Zeros",
+ "config": {}}, "units": 10, "batch_input_shape": [null, 4], "use_bias":
true,
+ "activity_regularizer": null}}, {"class_name": "Dense",
+ "config": {"kernel_initializer": {"class_name": "VarianceScaling",
+ "config": {"distribution": "uniform", "scale": 1.0, "seed": 0, "mode":
"fan_avg"}},
+ "name": "dense_2", "kernel_constraint": null, "bias_regularizer": null,
+ "bias_constraint": null, "activation": "relu", "trainable": true,
"kernel_regularizer": null,
+ "bias_initializer": {"class_name": "Zeros", "config": {}}, "units": 10,
"use_bias": true,
+ "activity_regularizer": null}}, {"class_name": "Dense", "config":
{"kernel_initializer":
+ {"class_name": "VarianceScaling", "config": {"distribution": "uniform",
"scale": 1.0,
+ "seed": 0, "mode": "fan_avg"}}, "name": "dense_3", "kernel_constraint":
null,
+ "bias_regularizer": null, "bias_constraint": null, "activation": "softmax",
+ "trainable": true, "kernel_regularizer": null, "bias_initializer":
{"class_name": "Zeros",
+ "config": {}}, "units": 3, "use_bias": true, "activity_regularizer":
null}}],
+ "backend": "tensorflow"}
+$$
+);
+
+DROP TABLE IF EXISTS mst_table, mst_table_summary;
+SELECT load_model_selection_table(
+ 'iris_model_arch',
+ 'mst_table',
+ ARRAY[1,3],
+ ARRAY[
+
$$loss='categorical_crossentropy',optimizer='Adam(lr=0.01)',metrics=['accuracy']$$,
+ $$loss='categorical_crossentropy',
optimizer='Adam(lr=0.001)',metrics=['accuracy']$$
+ ],
+ ARRAY[
+ $$batch_size=5,epochs=1$$
+ ]
+);
+
+DROP TABLE if exists iris_multiple_model, iris_multiple_model_summary,
iris_multiple_model_info;
+SELECT setseed(0);
+SELECT madlib_keras_fit_multiple_model(
+ 'iris_data_packed',
+ 'iris_multiple_model',
+ 'mst_table',
+ 3,
+ 0
+);
+
+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;
+
+UPDATE iris_model_arch
+SET model_weights = (SELECT model_weights FROM iris_multiple_model WHERE
mst_key=1)
+WHERE model_id = 1;
+
+DROP TABLE if exists iris_multiple_model, iris_multiple_model_summary,
iris_multiple_model_info;
+SELECT madlib_keras_fit_multiple_model(
+ 'iris_data_packed',
+ 'iris_multiple_model',
+ 'mst_table',
+ 3,
+ 0
+);
+
+SELECT assert(
+ abs(first.training_loss_final-second.training_loss[1]) < 1e-6 AND
+ abs(first.training_loss_final-second.training_loss[2]) < 1e-6 AND
+ abs(first.training_metrics_final-second.training_metrics[1]) < 1e-10 AND
+ abs(first.training_metrics_final-second.training_metrics[2]) < 1e-10,
+ '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
+WHERE first.mst_key = second.mst_key AND first.model_id = 2;
+!>)
