fingerprinted now should work correctly

modules/blocks.py

@@ -1,11 +1,13 @@
+from pathlib import Path
 from typing import Union
 
 import torch
 import warnings
 
 from torch import nn
-
+import sys
-from modules.utils import AutoPad, Interpolate, ShapeMixin, F_x, Flatten
+sys.path.append(str(Path(__file__).parent))
+from .util import AutoPad, Interpolate, ShapeMixin, F_x, Flatten
 
 DEVICE = torch.device('cuda' if torch.cuda.is_available() else 'cpu')
 

modules/model_parts.py

@@ -4,7 +4,7 @@
 import torch
 from torch import nn
 
-from modules.utils import ShapeMixin
+from .util import ShapeMixin
 
 
 class Generator(nn.Module):

modules/util.py

@@ -10,7 +10,7 @@ import pytorch_lightning as pl
 
 # Utility - Modules
 ###################
-from utils.model_io import ModelParameters
+from ..utils.model_io import ModelParameters
 
 
 class ShapeMixin:

utils/config.py

@@ -39,10 +39,15 @@ class Config(ConfigParser, ABC):
         h = hashlib.md5()
         params = deepcopy(self.as_dict)
         del params['model']['type']
-        del params['model']['secondary_type']
         del params['data']['worker']
         del params['main']
-        h.update(str(params).encode())
+        del params['project']
+        # Flatten the dict of dicts
+        for section in list(params.keys()):
+            params.update({f'{section}_{key}': val for key, val in params[section].items()})
+            del params[section]
+        _, vals = zip(*sorted(params.items(), key=lambda tup: tup[0]))
+        h.update(str(vals).encode())
         fingerprint = h.hexdigest()
         return fingerprint
 

utils/logging.py

@@ -5,7 +5,7 @@ from pytorch_lightning.loggers.base import LightningLoggerBase
 from pytorch_lightning.loggers.neptune import NeptuneLogger
 from pytorch_lightning.loggers.test_tube import TestTubeLogger
 
-from utils.config import Config
+from .config import Config
 
 
 class Logger(LightningLoggerBase, ABC):

utils/parallel.py

@@ -23,3 +23,5 @@ def run_n_in_parallel(f, n, processes=0, **kwargs):
         p.join()
 
     return results
+
+raise NotImplementedError()