add param compatability check

open_lm/main.py

@@ -227,9 +227,31 @@ def save_checkpoint(
                     os.remove(prev)
 
 
+def check_args(args):
+    resume_latest = args.resume == "latest"
+    args.log_path = None
+
+    if args.hf_model is not None and args.hf_seq_len is None:
+        raise ValueError("If passing --hf-model, must also pass --hf-seq-len to be used for training/fine-tuning.")
+
+    if args.hf_model is not None and args.fsdp and args.hf_fsdp_block is None:
+        raise ValueError("If passing --hf-model and --fsdp, must also pass --hf-fspd-block.")
+
+    if resume_latest:
+        # If using remote_sync, need to check the remote instead of the local checkpoints folder.
+        if args.remote_sync is not None:
+            if args.save_most_recent:
+                raise ValueError("Cannot use save-most-recent with remote_sync and resume latest.")
+            if args.remote_sync_protocol != "s3":
+                raise ValueError("Sync protocol not supported when using resume latest.")
+
+
 def main(args):
     args = parse_args(args)
 
+    # Check the arg list for any incompatibilities.
+    check_args(args)
+
     requires_training = args.train_data or args.dataset_type == "synthetic" or args.dataset_manifest is not None
 
     if torch.cuda.is_available():
@@ -243,12 +265,6 @@ def main(args):
     # fully initialize distributed device environment
     device = init_distributed_device(args)
 
-    if args.hf_model is not None and args.hf_seq_len is None:
-        raise ValueError("If passing --hf-model, must also pass --hf-seq-len to be used for training/fine-tuning.")
-
-    if args.hf_model is not None and args.fsdp and args.hf_fsdp_block is None:
-        raise ValueError("If passing --hf-model and --fsdp, must also pass --hf-fspd-block.")
-
     # get the name of the experiments
     if args.name is None:
         # sanitize model name for filesystem / uri use, easier if we don't use / in name as a rule?
@@ -303,13 +319,7 @@ def main(args):
     if resume_latest:
         resume_from = None
         checkpoint_path = args.checkpoint_path
-        # If using remote_sync, need to check the remote instead of the local checkpoints folder.
-        if args.remote_sync is not None:
-            checkpoint_path = os.path.join(args.remote_sync, args.name)
-            if args.save_most_recent:
-                raise ValueError("Cannot use save-most-recent with remote_sync and resume latest.")
-            if args.remote_sync_protocol != "s3":
-                raise ValueError("Sync protocol not supported when using resume latest.")
+
         if is_master(args):
             # Checking for existing checkpoint via master rank only. It is possible for
             # different rank processes to see different files if a shared file-system is under