Skip to content
New issue

Have a question about this project? Sign up for a free GitHub account to open an issue and contact its maintainers and the community.

Sign up for GitHub

By clicking “Sign up for GitHub”, you agree to our terms of service and privacy statement. We’ll occasionally send you account related emails.

Already on GitHub? Sign in to your account

Jump to bottom

Issue 149: VGG-like Convolutional Neural Network Classifier #152

Merged
merged 5 commits into from
Apr 20, 2019
Merged

Issue 149: VGG-like Convolutional Neural Network Classifier #152

Show file tree
Hide file tree
Changes from all commits
Commits
Show all changes
5 commits
Select commit Hold shift + click to select a range
7b2666b
add `keras.Sequential.VGGCNNClassifier` primitive
Hector-hedb12 Apr 4, 2019
78a563c
create pipeline for `keras.Sequential.VGGCNNClassifier` primitive
Hector-hedb12 Apr 4, 2019
3a68063
remove `batch_size` tunable parameter
Hector-hedb12 Apr 15, 2019
904a33c
add `verbose` fixed parameter
Hector-hedb12 Apr 15, 2019
24c9abd
default `verbose` to 0
Hector-hedb12 Apr 15, 2019
File filter

Filter by extension

Filter by extension
Conversations
Failed to load comments.
Loading
Jump to
Jump to file
Failed to load files.
Loading
Diff view
Diff view
272 changes: 272 additions & 0 deletions mlprimitives/jsons/keras.Sequential.VGGCNNClassifier.json
View file
Open in desktop
Original file line number Diff line number Diff line change
@@ -0,0 +1,272 @@
{
"name": "keras.Sequential.VGGCNNClassifier",
"contributors": [
"Hector Dominguez <hedb_12@hotmail.com>"
],
"description": "VGG-like Convolutional Neural Network Classifier",
"classifiers": {
"type": "estimator",
"subtype": "classifier"
},
"modalities": [],
"primitive": "mlprimitives.adapters.keras.Sequential",
"fit": {
"method": "fit",
"args": [
{
"name": "X",
"type": "ndarray"
},
{
"name": "y",
"type": "array"
},
{
"name": "classes",
"type": "int",
"description": "Number of classes"
}
]
},
"produce": {
"method": "predict",
"args": [
{
"name": "X",
"type": "ndarray"
}
],
"output": [
{
"name": "y",
"type": "array"
}
]
},
"hyperparameters": {
"fixed": {
"classification": {
"type": "bool",
"default": true
},
"conv2d_1_filters": {
"type": "int",
"default": 32
},
"input_shape": {
"type": "list",
"default": [
224,
224,
3
]
},
"conv2d_2_filters": {
"type": "int",
"default": 32
},
"conv2d_3_filters": {
"type": "int",
"default": 32
},
"conv2d_4_filters": {
"type": "int",
"default": 32
},
"loss": {
"type": "str",
"default": "keras.losses.categorical_crossentropy"
},
"optimizer": {
"type": "str",
"default": "keras.optimizers.SGD"
},
"metrics": {
"type": "list",
"default": [
"accuracy"
]
},
"epochs": {
"type": "int",
"default": 20
},
"verbose": {
"type": "int",
"default": 0,
"range": [
0,
2
]
},
"layers": {
"type": "list",
"default": [
{
"class": "keras.layers.Conv2D",
"parameters": {
"filters": "conv2d_1_filters",
"kernel_size": "conv2d_1_kernel_size",
"activation": "relu",
"input_shape": "input_shape"
}
},
{
"class": "keras.layers.Conv2D",
"parameters": {
"filters": "conv2d_2_filters",
"kernel_size": "conv2d_2_kernel_size",
"activation": "relu"
}
},
{
"class": "keras.layers.MaxPooling2D",
"parameters": {
"pool_size": "maxpooling2d_1_pool_size"
}
},
{
"class": "keras.layers.Dropout",
"parameters": {
"rate": "dropout_1_rate"
}
},
{
"class": "keras.layers.Conv2D",
"parameters": {
"filters": "conv2d_3_filters",
"kernel_size": "conv2d_3_kernel_size",
"activation": "relu"
}
},
{
"class": "keras.layers.Conv2D",
"parameters": {
"filters": "conv2d_4_filters",
"kernel_size": "conv2d_4_kernel_size",
"activation": "relu"
}
},
{
"class": "keras.layers.MaxPooling2D",
"parameters": {
"pool_size": "maxpooling2d_2_pool_size"
}
},
{
"class": "keras.layers.Dropout",
"parameters": {
"rate": "dropout_2_rate"
}
},
{
"class": "keras.layers.Flatten",
"parameters": {}
},
{
"class": "keras.layers.Dense",
"parameters": {
"units": "dense_units",
"activation": "relu"
}
},
{
"class": "keras.layers.Dropout",
"parameters": {
"rate": "dropout_3_rate"
}
},
{
"class": "keras.layers.Dense",
"parameters": {
"units": "classes",
"activation": "softmax"
}
}
]
}
},
"tunable": {
"conv2d_1_kernel_size": {
"type": "int",
"default": 3,
"range": [
3,
10
]
},
"conv2d_2_kernel_size": {
"type": "int",
"default": 3,
"range": [
3,
10
]
},
"maxpooling2d_1_pool_size": {
"type": "int",
"default": 2,
"range": [
2,
10
]
},
"dropout_1_rate": {
"type": "float",
"default": 0.0,
"range": [
0.0,
0.75
]
},
"conv2d_3_kernel_size": {
"type": "int",
"default": 3,
"range": [
3,
10
]
},
"conv2d_4_kernel_size": {
"type": "int",
"default": 3,
"range": [
3,
10
]
},
"maxpooling2d_2_pool_size": {
"type": "int",
"default": 2,
"range": [
2,
10
]
},
"dropout_2_rate": {
"type": "float",
"default": 0.0,
"range": [
0.0,
0.75
]
},
"dense_units": {
"type": "int",
"default": 64,
"range": [
1,
500
]
},
"dropout_3_rate": {
"type": "float",
"default": 0.5,
"range": [
0.0,
0.75
]
}
}
}
}
33 changes: 33 additions & 0 deletions pipelines/keras.Sequential.VGGCNNClassifier.json
View file
Open in desktop
Original file line number Diff line number Diff line change
@@ -0,0 +1,33 @@
{
"metadata": {
"name": "keras.Sequential.VGGCNNClassifier",
"data_type": "image",
"task_type": "classification"
},
"validation": {
"dataset": "usps",
"context": {}
},
"primitives": [
"mlprimitives.custom.counters.UniqueCounter",
"keras.Sequential.VGGCNNClassifier"
],
"input_names": {
"mlprimitives.custom.counters.UniqueCounter#1": {
"X": "y"
}
},
"output_names": {
"mlprimitives.custom.counters.UniqueCounter#1": {
"counts": "classes"
}
},
"init_params": {
"mlprimitives.custom.counters.UniqueCounter#1": {
"add": 1
},
"keras.Sequential.VGGCNNClassifier#1": {
"epochs": 1
}
}
}