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new fd04db3 update user docs for loading model arch
fd04db3 is described below
commit fd04db3f96c07a865a345b3072f9d0b4c3cc5bda
Author: Frank McQuillan <fmcquil...@pivotal.io>
AuthorDate: Thu Mar 28 17:53:32 2019 -0700
update user docs for loading model arch
---
doc/mainpage.dox.in | 8 +-
.../deep_learning/keras_model_arch_table.sql_in | 224 +++++++++++++++++++--
.../utilities/minibatch_preprocessing_dl.sql_in | 3 +
3 files changed, 211 insertions(+), 24 deletions(-)
diff --git a/doc/mainpage.dox.in b/doc/mainpage.dox.in
index 826e8d7..e221319 100644
--- a/doc/mainpage.dox.in
+++ b/doc/mainpage.dox.in
@@ -287,11 +287,11 @@ Interface and implementation are subject to change.
@{
@defgroup grp_cg Conjugate Gradient
@defgroup grp_dl Deep Learning
- @brief A collection of deep learning interfaces.
- @details A collection of deep learning interfaces.
+ @brief A collection of modules for deep learning.
+ @details A collection of modules for deep learning.
@{
- @defgroup grp_minibatch_preprocessing_dl Mini-Batch Preprocessor for
Image Data
- @defgroup grp_keras_model_arch Helper Function to Load Model
Architectures to Table
+ @defgroup grp_keras_model_arch Load Model Architecture
+ @defgroup grp_minibatch_preprocessing_dl Mini-Batch Preprocessor for
Images
@}
@defgroup grp_bayes Naive Bayes Classification
@defgroup grp_sample Random Sampling
diff --git
a/src/ports/postgres/modules/deep_learning/keras_model_arch_table.sql_in
b/src/ports/postgres/modules/deep_learning/keras_model_arch_table.sql_in
index 7626107..bb734ab 100644
--- a/src/ports/postgres/modules/deep_learning/keras_model_arch_table.sql_in
+++ b/src/ports/postgres/modules/deep_learning/keras_model_arch_table.sql_in
@@ -30,22 +30,28 @@ m4_include(`SQLCommon.m4')
/**
@addtogroup grp_keras_model_arch
+@brief Utility function to load model architectures and weights into a table
for
+use by deep learning algorithms.
+
<div class="toc"><b>Contents</b><ul>
-<li class="level1"><a href="#load_keras_model">Helper Function to Load Model
Architectures to Table</a></li>
-<li class="level1"><a href="#delete_keras_model">Helper Function to Delete
Model Architectures from Table</a></li>
+<li class="level1"><a href="#load_keras_model">Load Model Architecture</a></li>
+<li class="level1"><a href="#delete_keras_model">Delete Model
Architecture</a></li>
<li class="level1"><a href="#example">Examples</a></li>
</ul></div>
-The architecture of the model to be used in madlib_keras_train()
-function must be stored in a table, the details of which must be
-provided as parameters to the madlib_keras_train module. load_keras_model is
-a helper function to help users insert JSON blobs of Keras model
-architectures into a table. If the output table already exists, the model_arch
-specified will be added as a new row into the table. The output table could
thus
-act as a repository of Keras model architectures.
+This utility function loads model architectures and
+weights into a table for use by deep learning algorithms.
+Model architecture is in JSON form
+and model weights are in the form of double precision arrays.
+If the output table already exists, a new row is inserted
+into the table so it can act as a repository for multiple model
+architectures.
+
+There is also a utility function to delete a model architecture
+from the model architecture table.
-delete_keras_model can be used to delete the model architecture corresponding
-to the provided model_id from the model architecture repository table
(keras_model_arch_table).
+@anchor load_keras_model
+@par Load Model Architecture
<pre class="syntax">
load_keras_model(
@@ -56,17 +62,17 @@ load_keras_model(
\b Arguments
<dl class="arglist">
<dt>keras_model_arch_table</dt>
- <dd>VARCHAR. Output table to load keras model arch.
+ <dd>VARCHAR. Output table to load keras model architecture.
</dd>
<dt>model_arch</dt>
- <dd>JSON. JSON of the model architecture to insert.
+ <dd>JSON. JSON of the model architecture to load.
</dd>
</dl>
<b>Output table</b>
<br>
- The output table produced by load_keras_model contains the following
columns:
+ The output table contains the following columns:
<table class="output">
<tr>
<th>model_id</th>
@@ -80,17 +86,19 @@ load_keras_model(
</tr>
<tr>
<th>model_weights</th>
- <td>DOUBLE PRECISION[]. Weights of the model for warm start.
+ <td>DOUBLE PRECISION[]. Weights of the model which may be use for warm
start.
</td>
</tr>
<tr>
<th>__internal_madlib_id__</th>
- <td>TEXT. Unique id for model arch.
+ <td>TEXT. Unique id for model arch. This is an id used internally be
MADlib.
</td>
</tr>
</table>
</br>
+@anchor delete_keras_model
+@par Delete Model Architecture
<pre class="syntax">
delete_keras_model(
@@ -101,18 +109,194 @@ delete_keras_model(
\b Arguments
<dl class="arglist">
<dt>keras_model_arch_table</dt>
- <dd>VARCHAR. Table containing Keras model architectures.
+ <dd>VARCHAR. Table containing model architectures.
</dd>
<dt>model_id</dt>
- <dd>INTEGER. The id of the model arch to be deleted.
+ <dd>INTEGER. The id of the model architecture to be deleted.
</dd>
</dl>
@anchor example
@par Examples
--# TBD
-
+-# Define or obtain model. Let's say we have a Keras model
+architecture that looks like this:
+<pre class="example">
+model = Sequential()
+model.add(Dense(2, input_dim=3, name='dense_1'))
+model.add(Dense(3, name='dense_2'))
+...
+model.to_json
+</pre>
+This is represented by the following JSON:
+<pre class="example">
+'{"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": null, "mode": "fan_avg"}}, "name": "dense_1",
+"kernel_constraint": null, "bias_regularizer": null, "bias_constraint":
+null, "dtype": "float32", "activation": "linear", "trainable": true,
+"kernel_regularizer": null, "bias_initializer": {"class_name": "Zeros",
+"config": {}}, "units": 2, "batch_input_shape": [null, 3],
+"use_bias": true, "activity_regularizer": null}}, {"class_name": "Dense",
+"config": {"kernel_initializer": {"class_name": "VarianceScaling",
+"config": {"distribution": "uniform", "scale": 1.0, "seed": null,
+"mode": "fan_avg"}}, "name": "new_dense", "kernel_constraint": null,
+"bias_regularizer": null, "bias_constraint": null, "activation": "linear",
+"trainable": true, "kernel_regularizer": null,
+"bias_initializer": {"class_name": "Zeros", "config": {}},
+"units": 10, "use_bias": true, "activity_regularizer": null}}],
+"backend": "tensorflow"}'
+</pre>
+-# Load the model into the model architecture table:
+<pre class="example">
+DROP TABLE IF EXISTS model_arch_library;
+SELECT madlib.load_keras_model('model_arch_library', -- Output table
+$$
+{"class_name": "Sequential", "keras_version": "2.1.6",
+"config": [{"class_name": "Dense", "config": {"kernel_initializer":
+{"class_name": "VarianceScaling", "config": {"distribution": "uniform",
+"scale": 1.0, "seed": null, "mode": "fan_avg"}}, "name": "dense_1",
+"kernel_constraint": null, "bias_regularizer": null, "bias_constraint":
+null, "dtype": "float32", "activation": "linear", "trainable": true,
+"kernel_regularizer": null, "bias_initializer": {"class_name": "Zeros",
+"config": {}}, "units": 2, "batch_input_shape": [null, 3],
+"use_bias": true, "activity_regularizer": null}}, {"class_name": "Dense",
+"config": {"kernel_initializer": {"class_name": "VarianceScaling",
+"config": {"distribution": "uniform", "scale": 1.0, "seed": null,
+"mode": "fan_avg"}}, "name": "new_dense", "kernel_constraint": null,
+"bias_regularizer": null, "bias_constraint": null, "activation": "linear",
+"trainable": true, "kernel_regularizer": null,
+"bias_initializer": {"class_name": "Zeros", "config": {}},
+"units": 10, "use_bias": true, "activity_regularizer": null}}],
+"backend": "tensorflow"}
+$$ ::json -- JSON blob
+);
+SELECT * FROM model_arch_library;
+</pre>
+<pre class="result">
+ model_id | model_arch
| model_weights | __internal_madlib_id__
+----------+-----------------------------------------------------------------------------+---------------+----------------------------------------------
+ 1 |
| | __madlib_temp_79462163_1553817233_28408205__
+ : {"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": null, "mode": "fan_avg"}}, "name": "dense_1",
+ : "kernel_constraint": null, "bias_regularizer": null,
"bias_constraint":
+ : null, "dtype": "float32", "activation": "linear", "trainable":
true,
+ : "kernel_regularizer": null, "bias_initializer": {"class_name":
"Zeros",
+ : "config": {}}, "units": 2, "batch_input_shape": [null, 3],
+ : "use_bias": true, "activity_regularizer": null}}, {"class_name":
"Dense",
+ : "config": {"kernel_initializer": {"class_name": "VarianceScaling",
+ : "config": {"distribution": "uniform", "scale": 1.0, "seed": null,
+ : "mode": "fan_avg"}}, "name": "new_dense", "kernel_constraint":
null,
+ : "bias_regularizer": null, "bias_constraint": null, "activation":
"linear",
+ : "trainable": true, "kernel_regularizer": null,
+ : "bias_initializer": {"class_name": "Zeros", "config": {}},
+ : "units": 10, "use_bias": true, "activity_regularizer": null}}],
+ : "backend": "tensorflow"}
+ :
+(1 row)
+</pre>
+-# Load another model into the same table:
+<pre class="example">
+SELECT madlib.load_keras_model('model_arch_library', -- Output table
+$$
+{"class_name": "Sequential", "keras_version": "2.1.6",
+"config": [{"class_name": "Dense", "config": {"kernel_initializer":
+{"class_name": "VarianceScaling", "config": {"distribution": "uniform",
+"scale": 1.0, "seed": null, "mode": "fan_avg"}}, "name": "dense_1",
+"kernel_constraint": null, "bias_regularizer": null, "bias_constraint":
+null, "dtype": "float32", "activation": "linear", "trainable": true,
+"kernel_regularizer": null, "bias_initializer": {"class_name": "Zeros",
+"config": {}}, "units": 2, "batch_input_shape": [null, 3],
+"use_bias": true, "activity_regularizer": null}}, {"class_name": "Dense",
+"config": {"kernel_initializer": {"class_name": "VarianceScaling",
+"config": {"distribution": "uniform", "scale": 1.0, "seed": null,
+"mode": "fan_avg"}}, "name": "new_dense", "kernel_constraint": null,
+"bias_regularizer": null, "bias_constraint": null, "activation": "linear",
+"trainable": true, "kernel_regularizer": null,
+"bias_initializer": {"class_name": "Zeros", "config": {}},
+"units": 10, "use_bias": true, "activity_regularizer": null}}],
+"backend": "tensorflow"}
+$$ ::json -- JSON blob
+);
+SELECT * FROM model_arch_library;
+</pre>
+<pre class="result">
+ model_id | model_arch
| model_weights | __internal_madlib_id__
+----------+-----------------------------------------------------------------------------+---------------+----------------------------------------------
+ 1 |
| | __madlib_temp_79462163_1553817233_28408205__
+ : {"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": null, "mode": "fan_avg"}}, "name": "dense_1",
+ : "kernel_constraint": null, "bias_regularizer": null,
"bias_constraint":
+ : null, "dtype": "float32", "activation": "linear", "trainable":
true,
+ : "kernel_regularizer": null, "bias_initializer": {"class_name":
"Zeros",
+ : "config": {}}, "units": 2, "batch_input_shape": [null, 3],
+ : "use_bias": true, "activity_regularizer": null}}, {"class_name":
"Dense",
+ : "config": {"kernel_initializer": {"class_name": "VarianceScaling",
+ : "config": {"distribution": "uniform", "scale": 1.0, "seed": null,
+ : "mode": "fan_avg"}}, "name": "new_dense", "kernel_constraint":
null,
+ : "bias_regularizer": null, "bias_constraint": null, "activation":
"linear",
+ : "trainable": true, "kernel_regularizer": null,
+ : "bias_initializer": {"class_name": "Zeros", "config": {}},
+ : "units": 10, "use_bias": true, "activity_regularizer": null}}],
+ : "backend": "tensorflow"}
+ :
+ 2 |
| | __madlib_temp_86851986_1553817356_19026896__
+ : {"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": null, "mode": "fan_avg"}}, "name": "dense_1",
+ : "kernel_constraint": null, "bias_regularizer": null,
"bias_constraint":
+ : null, "dtype": "float32", "activation": "linear", "trainable":
true,
+ : "kernel_regularizer": null, "bias_initializer": {"class_name":
"Zeros",
+ : "config": {}}, "units": 2, "batch_input_shape": [null, 3],
+ : "use_bias": true, "activity_regularizer": null}}, {"class_name":
"Dense",
+ : "config": {"kernel_initializer": {"class_name": "VarianceScaling",
+ : "config": {"distribution": "uniform", "scale": 1.0, "seed": null,
+ : "mode": "fan_avg"}}, "name": "new_dense", "kernel_constraint":
null,
+ : "bias_regularizer": null, "bias_constraint": null, "activation":
"linear",
+ : "trainable": true, "kernel_regularizer": null,
+ : "bias_initializer": {"class_name": "Zeros", "config": {}},
+ : "units": 10, "use_bias": true, "activity_regularizer": null}}],
+ : "backend": "tensorflow"}
+ :
+(2 rows)
+</pre>
+-# Delete one of the models:
+<pre class="example">
+SELECT madlib.delete_keras_model('model_arch_library', -- Output table
+ 1 -- Model id
+ );
+SELECT * FROM model_arch_library;
+</pre>
+<pre class="result">
+ model_id | model_arch
| model_weights | __internal_madlib_id__
+----------+----------------------------------------------------------------------------+---------------+----------------------------------------------
+ 2 |
| | __madlib_temp_41851307_1553819507_11044889__
+ : {"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": null, "mode": "fan_avg"}}, "name": "dense_1",
+ : "kernel_constraint": null, "bias_regularizer": null,
"bias_constraint":
+ : null, "dtype": "float32", "activation": "linear", "trainable":
true,
+ : "kernel_regularizer": null, "bias_initializer": {"class_name":
"Zeros",
+ : "config": {}}, "units": 2, "batch_input_shape": [null, 3],
+ : "use_bias": true, "activity_regularizer": null}}, {"class_name":
"Dense",
+ : "config": {"kernel_initializer": {"class_name": "VarianceScaling",
+ : "config": {"distribution": "uniform", "scale": 1.0, "seed": null,
+ : "mode": "fan_avg"}}, "name": "new_dense", "kernel_constraint":
null,
+ : "bias_regularizer": null, "bias_constraint": null, "activation":
"linear",
+ : "trainable": true, "kernel_regularizer": null,
+ : "bias_initializer": {"class_name": "Zeros", "config": {}},
+ : "units": 10, "use_bias": true, "activity_regularizer": null}}],
+ : "backend": "tensorflow"}
+ :
+(1 row)
+</pre>
*/
-- Function to add a keras model to arch table
diff --git
a/src/ports/postgres/modules/utilities/minibatch_preprocessing_dl.sql_in
b/src/ports/postgres/modules/utilities/minibatch_preprocessing_dl.sql_in
index 3be1ec0..67e216d 100644
--- a/src/ports/postgres/modules/utilities/minibatch_preprocessing_dl.sql_in
+++ b/src/ports/postgres/modules/utilities/minibatch_preprocessing_dl.sql_in
@@ -29,6 +29,9 @@ m4_include(`SQLCommon.m4')
/**
@addtogroup grp_minibatch_preprocessing_dl
+@brief Utility that prepares input image data for use by models
+that support mini-batch as an optimization option.
+
<div class="toc"><b>Contents</b><ul>
<li class="level1"><a href="#minibatch_preprocessor_dl">Mini-Batch
Preprocessor for Image Data</a></li>
<li class="level1"><a href="#example">Examples</a></li>
