update

Author: amirakbarnejad

cli/inflow_cli.py

@@ -1643,5 +1643,7 @@ def _convert_TrueFalse_to_bool(dict_input):
 # TODO: prioritise saving of the model checkpoint (i.e. move before anything else, including the saving of model predicitons).
 #     Because with model checkpoint, the predictions are recoverable but the reverse isn't possible.
 
+# TODO: assert that the paths in the config files are absolute paths (and not relative paths).
+
 
 

cli/mintflow_cli_recover_outputs.py

@@ -229,8 +229,6 @@ def try_mkdir(path_in):
     )
 )
 
-print("\n\n\n >>>>>>>> succesfully parsed the config files.")
-assert False
 
 # TODO: parse other config files ===
 
@@ -270,7 +268,7 @@ def try_mkdir(path_in):
 gc.collect()
 
 # set device ===
-if config_training['flag_use_GPU']:
+if args.flag_use_cuda: #config_training['flag_use_GPU']:
     if torch.cuda.is_available():
         device = torch.device("cuda:0")
     else:
@@ -284,6 +282,7 @@ def try_mkdir(path_in):
 if args.flag_verbose:
     print("\n\nDevice is set to {}.\n\n".format(device))
 
+
 # Create list tissue training =========
 
 def _convert_TrueFalse_to_bool(dict_input):
@@ -305,6 +304,7 @@ def _convert_TrueFalse_to_bool(dict_input):
 
     return dict_input
 
+
 list_slice = []
 for dict_current_anndata in config_data_train:
     current_anndata = sc.read_h5ad(dict_current_anndata['file'])
@@ -366,6 +366,8 @@ def _convert_TrueFalse_to_bool(dict_input):
     print("\n\n")
 
 
+assert False
+
 # create test_list_slice for evaluation ===
 test_list_slice = []
 for dict_current_anndata in config_data_test: