[v1] add seed for training and fix gradient checkpointing (#10211)

src/llamafactory/v1/config/arg_parser.py

@@ -21,6 +21,7 @@ from omegaconf import OmegaConf
 from transformers import HfArgumentParser
 
 from ..utils.env import is_env_enabled
+from ..utils.helper import set_seed
 from .data_args import DataArguments
 from .model_args import ModelArguments
 from .sample_args import SampleArguments
@@ -56,6 +57,14 @@ def get_args(args: InputArgument = None) -> tuple[ModelArguments, DataArguments,
             print(f"Got unknown args, potentially deprecated arguments: {unknown_args}")
             raise ValueError(f"Some specified arguments are not used by the HfArgumentParser: {unknown_args}")
 
+    # Seed as early as possible after argument parsing so all downstream
+    # components (dist init, dataloader, model init in run_* entrypoints) share the same RNG state.
+    for arg in parsed_args:
+        seed = getattr(arg, "seed", None)
+        if seed is not None:
+            set_seed(seed)
+            break
+
     return tuple(parsed_args)
 
 

src/llamafactory/v1/config/training_args.py

@@ -66,7 +66,7 @@ class TrainingArguments:
         metadata={"help": "Number of workers for batching."},
     )
     enable_activation_checkpointing: bool = field(
-        default=True,
+        default=False,
         metadata={"help": "Enable activation checkpointing for training."},
     )
     dist_config: PluginConfig | None = field(
@@ -81,6 +81,10 @@ class TrainingArguments:
         default=None,
         metadata={"help": "Learning rate scheduler configuration for training."},
     )
+    seed: int = field(
+        default=42,
+        metadata={"help": "Random seed that will be set at the beginning of training."},
+    )
 
     def __post_init__(self) -> None:
         self.dist_config = get_plugin_config(self.dist_config)