Minor Multiple class refactor

abraia/multiple.py

@@ -44,9 +44,7 @@ def load_metadata(self, path):
 
     def load_envi(self, path):
         dest = self.cache_file(path)
-        raw = f"{dest.split('.')[0]}.raw"
-        if not os.path.exists(raw):
-            self.download_file(f"{path.split('.')[0]}.raw", raw)
+        raw = self.cache_file(f"{path.split('.')[0]}.raw")
         return np.array(spectral.io.envi.open(dest, raw)[:, :, :])
 
     def load_mat(self, path):

abraia/torch.py

@@ -22,16 +22,13 @@
 device = torch.device("cuda:0" if torch.cuda.is_available() else "cpu")
 
 
+# TODO: Remove with next version
 def download_file(path):
-    dest = os.path.join(tempdir, path)
-    if not os.path.exists(dest):
-        os.makedirs(os.path.dirname(dest), exist_ok=True)
-        multiple.download_file(path, dest)
-    return dest
+    return multiple.cache_file(path)
 
 
 def read_image(path):
-    dest = download_file(path)
+    dest = multiple.cache_file(path)
     return Image.open(dest).convert('RGB')
 
 
@@ -81,7 +78,7 @@ def save_model(path, model, device='cpu'):
 
 
 def load_model(path, class_names):
-    dest = download_file(path)
+    dest = multiple.cache_file(path)
     model = create_model(class_names, pretrained=False)
     model.load_state_dict(torch.load(dest))
     return model
@@ -98,12 +95,14 @@ def export_onnx(path, model, device='cpu'):
     multiple.upload_file(src, path)
 
 
+# TODO: Remove with next version
 def save_json(path, values):
-    multiple.save_file(path, json.dumps(values))
+    multiple.save_json(path, values)
 
 
+# TODO: Remove with next version
 def load_json(path):
-    return json.loads(multiple.load_file(path))
+    return multiple.load_json(path)
 
 
 transform = transforms.Compose([
@@ -112,8 +111,7 @@ def load_json(path):
     transforms.ToTensor(),
     transforms.Normalize(
         mean=[0.485, 0.456, 0.406],
-        std=[0.229, 0.224, 0.225]
-    )
+        std=[0.229, 0.224, 0.225])
 ])
 
 
@@ -145,27 +143,22 @@ def train_model(model, dataloaders, criterion=None, optimizer=None, scheduler=No
 
             running_loss = 0.0
             running_corrects = 0
-
-            # Iterate over data.
+            # Iterate over data
             for inputs, labels in dataloaders[phase]:
                 inputs = inputs.to(device)
                 labels = labels.to(device)
-
                 # zero the parameter gradients
                 optimizer.zero_grad()
-
                 # forward
                 # track history if only in train
                 with torch.set_grad_enabled(phase == 'train'):
                     outputs = model(inputs)
                     _, preds = torch.max(outputs, 1)
                     loss = criterion(outputs, labels)
-
                     # backward + optimize only if in training phase
                     if phase == 'train':
                         loss.backward()
                         optimizer.step()
-
                 # statistics
                 running_loss += loss.item() * inputs.size(0)
                 running_corrects += torch.sum(preds == labels.data)
@@ -174,20 +167,17 @@ def train_model(model, dataloaders, criterion=None, optimizer=None, scheduler=No
 
             epoch_loss = running_loss / len(dataloaders[phase].dataset)
             epoch_acc = running_corrects.double() / len(dataloaders[phase].dataset)
-
             print(f'{phase} Loss: {epoch_loss:.4f} Acc: {epoch_acc:.4f}')
 
             # deep copy the model
             if phase == 'val' and epoch_acc > best_acc:
                 best_acc = epoch_acc
                 best_model_wts = copy.deepcopy(model.state_dict())
-
+            
         print()
-
     time_elapsed = time.time() - since
     print(f'Training complete in {time_elapsed // 60:.0f}m {time_elapsed % 60:.0f}s')
     print(f'Best val Acc: {best_acc:4f}')
-
     # load best model weights
     model.load_state_dict(best_model_wts)
     return model

scripts/abraia

@@ -42,7 +42,7 @@ def input_files(src):
 
 
 @click.group('abraia')
-@click.version_option('0.13.2')
+@click.version_option('0.13.3')
 def cli():
     """Abraia CLI tool"""
     pass
@@ -64,7 +64,7 @@ def configure():
 @cli.command()
 def info():
     """Show user account information"""
-    click.echo('abraia, version 0.13.2\n')
+    click.echo('abraia, version 0.13.3\n')
     click.echo('Go to [' + click.style('https://abraia.me/console/', fg='green') + '] to see your account information\n')
 
 

setup.py

@@ -12,7 +12,7 @@
 
 setup(
     name='abraia',
-    version='0.13.2',
+    version='0.13.3',
     description='Abraia Multiple SDK',
     long_description=long_description,
     long_description_content_type='text/markdown',