--- a
+++ b/mains/main_GMVAE_spatial.py
@@ -0,0 +1,31 @@
+#!/usr/bin/env python
+import tensorflow as tf
+
+from models.gaussian_mixture_variational_autoencoder_spatial import gaussian_mixture_variational_autoencoder_spatial
+from trainers.GMVAE_spatial import GMVAE_spatial
+from utils import Evaluation
+from utils.default_config_setup import get_config, get_options, get_datasets, Dataset
+
+tf.reset_default_graph()
+dataset = Dataset.BRAINWEB
+options = get_options(batchsize=8, learningrate=5e-5, numEpochs=1, zDim=128, outputWidth=128, outputHeight=128)
+options['data']['dir'] = options["globals"][dataset.value]
+datasetHC, datasetPC = get_datasets(options, dataset=dataset)
+config = get_config(trainer=GMVAE_spatial, options=options, optimizer='ADAM', intermediateResolutions=[8, 8], dropout_rate=0.1, dataset=datasetHC)
+
+config.dim_c = 9
+config.dim_z = 1
+config.dim_w = 1
+config.c_lambda = 1
+config.restore_lr = 1e-3
+config.restore_steps = 150
+config.tv_lambda = -1.0
+
+# Create an instance of the model and train it
+model = GMVAE_spatial(tf.Session(), config, network=gaussian_mixture_variational_autoencoder_spatial)
+
+# Train it
+model.train(datasetHC, )
+
+# Evaluate
+Evaluation.evaluate(datasetPC, model, options, description=f"{type(datasetHC).__name__}-{options['threshold']}", epoch=str(options['train']['numEpochs']))