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bugfix

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DU Wenjie
2025-12-26 17:41:57 +08:00
parent 7840049189
commit ea4229851b
2 changed files with 8 additions and 6 deletions
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6
scripts/base_eval.py
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@@ -149,8 +149,8 @@ def main():
parser = argparse.ArgumentParser()
parser.add_argument('--hf-path', type=str, default=None, help='HuggingFace model path to evaluate')
parser.add_argument('--max-per-task', type=int, default=-1, help='Max examples per task to evaluate (-1 = disable)')
parser.add_argument('--model_tag', type=str, default=None, help='optional model tag for the output directory name')
parser.add_argument('--model_step', type=str, default=None, help='optional model step for the output directory name')
parser.add_argument('--model-tag', type=str, default=None, help='optional model tag for the output directory name')
parser.add_argument('--step', type=str, default=None, help='optional model step for the output directory name')
args = parser.parse_args()
# distributed / precision setup
@@ -168,7 +168,7 @@ def main():
model_slug = hf_path.replace("/", "-") # for the output csv file
else:
# load a local model from the file system
model, tokenizer, meta = load_model("base", device, phase="eval", model_tag=args.model_tag, step=args.model_step)
model, tokenizer, meta = load_model("base", device, phase="eval", model_tag=args.model_tag, step=args.step)
model_name = f"base_model (step {meta['step']})" # just for logging
model_slug = f"base_model_{meta['step']:06d}" # for the output csv file

8
scripts/chat_rl.py
View File

@@ -31,6 +31,8 @@ from tasks.gsm8k import GSM8K
# RL hyperparameters
run = "dummy" # wandb run name
source = "sft" # mid|sft
model_tag = None # model tag to load the model from (base model or midtrained model)
step = None # step to load the model from (base model or midtrained model)
dtype = "bfloat16"
device_batch_size = 8 # no forward pass will go above this to not OOM
examples_per_step = 16 # in total and across all ranks (note: examples, not samples/completions!)
@@ -64,7 +66,7 @@ use_dummy_wandb = run == "dummy" or not master_process
wandb_run = DummyWandb() if use_dummy_wandb else wandb.init(project="nanochat-rl", name=run, config=user_config)
# Init model and tokenizer
model, tokenizer, meta = load_model(source, device, phase="eval")
model, tokenizer, meta = load_model(source, device, phase="eval", model_tag=model_tag, step=step)
engine = Engine(model, tokenizer) # for sampling rollouts
# -----------------------------------------------------------------------------
@@ -307,8 +309,8 @@ for step in range(num_steps):
if master_process and ((step > 0 and step % save_every == 0) or step == num_steps - 1):
base_dir = get_base_dir()
depth = model.config.n_layer
model_tag = f"d{depth}" # base the model tag on the depth of the base model
checkpoint_dir = os.path.join(base_dir, "chatrl_checkpoints", model_tag)
output_dirname = model_tag if model_tag else f"d{depth}" # base the model tag on the depth of the base model
checkpoint_dir = os.path.join(base_dir, "chatrl_checkpoints", output_dirname)
model_config_kwargs = model.config.__dict__ # slightly naughty, abusing the simplicity of GPTConfig, TODO nicer
save_checkpoint(
checkpoint_dir,