CIFAR10 CNN Example

#readme.md

CIFAR10 VGG Example

This example demonstrates how to build a VGG-like convolutional neural network for CIFAR10 dataset.

cifar10.ml

#!/usr/bin/env owl
(* This example demonstrates how to build a VGG-like convolutional neural
 * network for CIFAR10 dataset.
 *)

open Owl
open Neural.S
open Neural.S.Graph


let make_network input_shape =
  input input_shape
  |> normalisation
  |> conv2d [|3;3;3;32|] [|1;1|] ~act_typ:Activation.Relu
  |> conv2d [|3;3;32;32|] [|1;1|] ~act_typ:Activation.Relu ~padding:VALID
  |> max_pool2d [|2;2|] [|2;2|] ~padding:VALID
  |> dropout 0.1
  |> conv2d [|3;3;32;64|] [|1;1|] ~act_typ:Activation.Relu
  |> conv2d [|3;3;64;64|] [|1;1|] ~act_typ:Activation.Relu ~padding:VALID
  |> max_pool2d [|2;2|] [|2;2|] ~padding:VALID
  |> dropout 0.1
  |> fully_connected 512 ~act_typ:Activation.Relu
  |> linear 10 ~act_typ:Activation.(Softmax 1)
  |> get_network


let train () =
  let x, _, y = Dataset.load_cifar_train_data 1 in
  let network = make_network [|32;32;3|] in
  Graph.print network;
  let params = Params.config
    ~batch:(Batch.Mini 100) ~learning_rate:(Learning_Rate.Adagrad 0.01)
    ~checkpoint:(Checkpoint.Epoch 1.) 10.
  in
  Graph.train ~params network x y

gist.id

2e7c902812a7ae0547e24f7ea743c7e6