-
Notifications
You must be signed in to change notification settings - Fork 38
Commit
This commit does not belong to any branch on this repository, and may belong to a fork outside of the repository.
Merge pull request #152 from Hector-hedb12/issue_149_vgg_like_convnet
Issue 149: VGG-like Convolutional Neural Network Classifier
- Loading branch information
Showing
2 changed files
with
305 additions
and
0 deletions.
There are no files selected for viewing
272 changes: 272 additions & 0 deletions
272
mlprimitives/jsons/keras.Sequential.VGGCNNClassifier.json
This file contains bidirectional Unicode text that may be interpreted or compiled differently than what appears below. To review, open the file in an editor that reveals hidden Unicode characters.
Learn more about bidirectional Unicode characters
| Original file line number | Diff line number | Diff line change |
|---|---|---|
| @@ -0,0 +1,272 @@ | ||
| { | ||
| "name": "keras.Sequential.VGGCNNClassifier", | ||
| "contributors": [ | ||
| "Hector Dominguez <[email protected]>" | ||
| ], | ||
| "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 | ||
| ] | ||
| } | ||
| } | ||
| } | ||
| } |
This file contains bidirectional Unicode text that may be interpreted or compiled differently than what appears below. To review, open the file in an editor that reveals hidden Unicode characters.
Learn more about bidirectional Unicode characters
| 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 | ||
| } | ||
| } | ||
| } |