prefix -> run_id

benchmarks/benchmark_optimizer.py

@@ -21,7 +21,7 @@ from hivemind.utils.crypto import RSAPrivateKey
 @dataclass(frozen=True)
 class TrainingArguments:
     seed: int = 42
-    prefix: str = "my_exp"
+    run_id: str = "my_exp"
 
     num_peers: int = 8
     num_clients: int = 3
@@ -77,7 +77,7 @@ def benchmark_optimizer(args: TrainingArguments):
         assert isinstance(model, torch.nn.Module), "model_arch must evaluate to a pytorch module"
 
         optimizer = Optimizer(
-            run_id=args.prefix,
+            run_id=args.run_id,
             target_batch_size=args.target_batch_size,
             batch_size_per_step=batch_size,
             params=model.parameters(),