reformatting the training file

src/code/training.py

@@ -3,11 +3,14 @@ import sys
 from fastai.vision.all import *
 from torchvision.utils import save_image
 
+
 class ImageImageDataLoaders(DataLoaders):
     "Basic wrapper around several `DataLoader`s with factory methods for Image to Image problems"
+
     @classmethod
     @delegates(DataLoaders.from_dblock)
-    def from_label_func(cls, path, fnames, label_func, valid_pct=0.2, seed=None, item_tfms=None, batch_tfms=None, **kwargs):
+    def from_label_func(cls, path, fnames, label_func, valid_pct=0.2, seed=None, item_tfms=None,
+                        batch_tfms=None, **kwargs):
         "Create from list of `fnames` in `path`s with `label_func`."
         dblock = DataBlock(blocks=(ImageBlock(cls=PILImage), ImageBlock(cls=PILImageBW)),
                            splitter=RandomSplitter(valid_pct, seed=seed),
@@ -26,8 +29,9 @@ def get_y_fn(x):
 
 
 def create_data(data_path):
-    fnames = get_files(data_path/'train', extensions='.jpg')
-    data = ImageImageDataLoaders.from_label_func(data_path/'train', seed=42, bs=4, num_workers=0, fnames=fnames, label_func=get_y_fn)
+    fnames = get_files(data_path / 'train', extensions='.jpg')
+    data = ImageImageDataLoaders.from_label_func(data_path / 'train', seed=42, bs=4, num_workers=0,
+                                                 fnames=fnames, label_func=get_y_fn)
     return data
 
 
@@ -37,7 +41,8 @@ if __name__ == "__main__":
         sys.exit(0)
 
     data = create_data(Path(sys.argv[1]))
-    learner = unet_learner(data, resnet34, metrics=rmse, wd=1e-2, n_out=3, loss_func=MSELossFlat(), path='src/test/')
+    learner = unet_learner(data, resnet34, metrics=rmse, wd=1e-2, n_out=3, loss_func=MSELossFlat(),
+                           path='src/test/')
     print("Training model...")
     learner.fine_tune(1)
     print("Saving model...")