if __name__ == "__main__":
x = T.matrix('x')
dataset = "/u/gulcehrc/pento64x64_simple_2k_seed_312555.npy"
ds = Dataset()
print "starting pretrain"
ds.setup_pretraining_dataset(data_path=dataset)
train_set_patches, train_set_pre, train_set_labels = ds.Xtrain_patches, ds.Xtrain_presences, ds.Ytrain
test_set_patches, test_set_pre, test_set_labels = ds.Xtest_patches, ds.Xtest_presences, ds.Ytest
prmlp = PreMLP(x, n_epochs=2)
post_mlp = PosttrainMLP(x, n_in=64 * 11, n_hidden=400, n_out=10)
print "starting pre-training"
pre_train_probs = train_prmlp(prmlp, train_set_patches, train_set_pre)
print "starting the pre-testing"
pre_test_probs = test_prmlp(prmlp, test_set_patches, test_set_pre)
print "starting post-training"
post_mlp.posttrain(learning_rate=0.001,
data=pre_train_probs,
n_epochs=4,
labels=train_set_labels,
batch_size=60,
save_costs_file=True,
cost_type="negativelikelihood")
