--- a
+++ b/model_definition/baseline.py
@@ -0,0 +1,68 @@
+import tensorflow as tf
+import config
+
+from model_utils import calculate_conv_output_size
+
+
+n_x = config.IMAGE_PXL_SIZE_X
+n_y = config.IMAGE_PXL_SIZE_Y
+n_z = config.SLICES
+
+# This handles padding in both convolution and pooling layers
+strides = [[1, 1, 1],
+           [2, 4, 4],
+           [1, 1, 1],
+           [2, 2, 2],
+           [1, 1, 1],
+           [2, 2, 2]]
+
+filters = [[3, 5, 5],
+            [3, 5, 5],
+            [3, 3, 3],
+            [3, 3, 3],
+            [3, 3, 3],
+            [3, 3, 3]]
+            
+padding_types = ['VALID'] * 6
+
+
+baseline_config = {
+    'weights': [
+        # Convolution layers
+        ('wc1', tf.truncated_normal([3, 5, 5, config.NUM_CHANNELS, 16], stddev=0.01)),
+        ('wc2', tf.truncated_normal([3, 3, 3, 16, 32], stddev=0.01)),
+        ('wc3', tf.truncated_normal([3, 3, 3, 32, 32], stddev=0.01)),
+        # Fully connected layers
+        ('wd1', tf.truncated_normal([calculate_conv_output_size(n_x, n_y, n_z, 
+                                                                strides, 
+                                                                filters,
+                                                                padding_types, 
+                                                                32), 
+                                    100], stddev=0.01)),
+        ('wout', tf.truncated_normal([100, config.N_CLASSES], stddev=0.01))
+    ],
+    'biases': [
+        # Convolution layers
+        ('bc1', tf.zeros([16])),
+        ('bc2', tf.constant(1.0, shape=[32])),
+        ('bc3', tf.zeros([32])),
+        # Fully connected layers
+        ('bd1', tf.constant(1.0, shape=[100])),
+        ('bout', tf.constant(1.0, shape=[config.N_CLASSES]))
+    ],
+    'pool_strides': [
+        [1, 2, 4, 4, 1],
+        [1, 2, 2, 2, 1],
+        [1, 2, 2, 2, 1],
+    ],
+    'pool_windows': [
+        [1, 3, 5, 5, 1],
+        [1, 3, 3, 3, 1],
+        [1, 3, 3, 3, 1],
+    ],
+    'strides': [
+        [1, 1, 1, 1, 1],
+        [1, 1, 1, 1, 1],
+        [1, 1, 1, 1, 1],
+    ]
+}
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