♻️ experiment.configs

labml_nn/capsule_networks/mnist.py

@@ -153,8 +153,7 @@ def main():
     conf = Configs()
     experiment.create(name='mnist_latest')
     experiment.configs(conf, {'optimizer.optimizer': 'Adam',
-                              'device.cuda_device': 1},
-                       'run')
+                              'device.cuda_device': 1})
     with experiment.start():
         conf.run()
 

labml_nn/gan/dcgan.py

@@ -106,8 +106,7 @@ def main():
     experiment.configs(conf,
                        {'discriminator': 'cnn',
                         'generator': 'cnn',
-                        'label_smoothing': 0.01},
-                       'run')
+                        'label_smoothing': 0.01})
     with experiment.start():
         conf.run()
 

labml_nn/gan/simple_mnist_experiment.py

@@ -233,8 +233,7 @@ def main():
     conf = Configs()
     experiment.create(name='mnist_gan', comment='test')
     experiment.configs(conf,
-                       {'label_smoothing': 0.01},
-                       'run')
+                       {'label_smoothing': 0.01})
     with experiment.start():
         conf.run()
 

labml_nn/transformers/knn/build_index.py

@@ -33,7 +33,7 @@ def load_experiment(run_uuid: str, checkpoint: Optional[int] = None):
     # This experiment is just an evaluation; i.e. nothing is tracked or saved
     experiment.evaluate()
     # Initialize configurations
-    experiment.configs(conf, conf_dict, 'run')
+    experiment.configs(conf, conf_dict)
     # Set models for saving/loading
     experiment.add_pytorch_models(get_modules(conf))
     # Specify the experiment to load from

labml_nn/transformers/knn/train_model.py

@@ -331,10 +331,7 @@ def main():
                         'transformer.d_model': 256,
                         'transformer.d_ff': 1024,
                         'transformer.n_heads': 8,
-                        'transformer.n_layers': 6},
-                       # We need to load the function `TrainValidConfigs.run` and
-                       # everything that it's dependent on
-                       'run')
+                        'transformer.n_layers': 6})
 
     # Set models for saving and loading
     experiment.add_pytorch_models(get_modules(conf))