added Autoencoder3D import + commented out L1 loss for x2x

run.py

@@ -39,7 +39,7 @@ import torch.utils.data as data
 import numpy as np
 
 from solver import Solver
-from BrainMapperAE import BrainMapperAE3D
+from BrainMapperAE import BrainMapperAE3D, AutoEncoder3D
 from utils.data_utils import get_datasets
 from utils.settings import Settings
 import utils.data_evaluation_utils as evaluations
@@ -195,7 +195,8 @@ def train(data_parameters, training_parameters, network_parameters, misc_paramet
         if training_parameters['use_pre_trained']:
             BrainMapperModel = torch.load(training_parameters['pre_trained_path'])
         else:
-            BrainMapperModel = BrainMapperAE3D(network_parameters)
+            # BrainMapperModel = BrainMapperAE3D(network_parameters)
+            BrainMapperModel = AutoEncoder3D(network_parameters) # temprorary change for testing encoder-decoder effective receptive field
 
         custom_weight_reset_flag = network_parameters['custom_weight_reset_flag']
 
@@ -265,7 +266,7 @@ def train(data_parameters, training_parameters, network_parameters, misc_paramet
             data_parameters['target_data_train'] = data_parameters['input_data_train']
             data_parameters['target_data_validation'] = data_parameters['input_data_validation']
 
-            loss_function = torch.nn.L1Loss()
+            # loss_function = torch.nn.L1Loss()
 
             _ = _train_runner(data_parameters, 
                             training_parameters, 
@@ -281,7 +282,7 @@ def train(data_parameters, training_parameters, network_parameters, misc_paramet
             data_parameters['input_data_train'] = data_parameters['target_data_train']
             data_parameters['input_data_validation'] = data_parameters['target_data_validation']
 
-            loss_function = torch.nn.L1Loss()
+            # loss_function = torch.nn.L1Loss()
 
             _ = _train_runner(data_parameters, 
                             training_parameters, 
@@ -366,6 +367,7 @@ def evaluate_mapping(mapping_evaluation_parameters):
                                  device, 
                                  exit_on_error)
 
+
 def delete_files(folder):
     """ Clear Folder Contents
 
@@ -422,8 +424,6 @@ if __name__ == '__main__':
         train(data_parameters, training_parameters,
               network_parameters, misc_parameters)
 
-    # NOTE: THE EVAL FUNCTIONS HAVE NOT YET BEEN DEBUGGED (16/04/20)
-
     elif arguments.mode == 'evaluate-mapping':
         logging.basicConfig(filename='evaluate-mapping-error.log')
         settings_evaluation = Settings(evaluation_settings_file_name)