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Update load mcore checkpoint #9595

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Update load mcore checkpoint #9595

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eef6720
fix ddp_config
Jintao-Huang Jun 18, 2026
c333bd8
update load_mcore_checkpoint
Jintao-Huang Jun 18, 2026
2e1ab70
Merge branch 'main' into update_load_mcore_checkpoint
Jintao-Huang Jun 24, 2026
cbbfbe9
fix
Jintao-Huang Jun 24, 2026
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18 changes: 9 additions & 9 deletions swift/megatron/utils/megatron_lm_utils.py
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Original file line number Diff line number Diff line change
Expand Up @@ -403,11 +403,11 @@ def load_mcore_checkpoint(args,
tracker_path = os.path.join(load_dir, 'latest_checkpointed_iteration.txt')
iteration = _load_iteration(tracker_path)
checkpoint_dir = os.path.join(load_dir, f'iter_{iteration:07d}')
state_dict = dist_checkpointing.load_common_state_dict(checkpoint_dir)
common_state_dict = dist_checkpointing.load_common_state_dict(checkpoint_dir)

ckpt_tp_pp = (
state_dict['args'].tensor_model_parallel_size,
state_dict['args'].pipeline_model_parallel_size,
common_state_dict['args'].tensor_model_parallel_size,
common_state_dict['args'].pipeline_model_parallel_size,
)
run_tp_pp = (
args.tensor_model_parallel_size,
Expand All @@ -416,14 +416,14 @@ def load_mcore_checkpoint(args,
mismatch_msg = f'(TP, PP) mismatch after resume ({run_tp_pp} vs {ckpt_tp_pp} from checkpoint)'
# Determine if RNG state will be loaded
if (ckpt_tp_pp == run_tp_pp and not finetune and not no_load_rng
and not getattr(state_dict['args'], 'no_save_rng', False)):
and not getattr(common_state_dict['args'], 'no_save_rng', False)):
gen_sd_rng_state = _get_rng_state() # we can load the rng state
else:
gen_sd_rng_state = None
if ckpt_tp_pp != run_tp_pp:
logger.info(f'{mismatch_msg}: RNG state will be ignored')
sharded_sd_metadata = state_dict.get('content_metadata')
if (not finetune and not no_load_optim and not getattr(state_dict['args'], 'no_save_optim', False)):
sharded_sd_metadata = common_state_dict.get('content_metadata')
if (not finetune and not no_load_optim and not getattr(common_state_dict['args'], 'no_save_optim', False)):
gen_sd_optim = optimizer
gen_sd_opt_param_scheduler = opt_param_scheduler

Expand Down Expand Up @@ -463,16 +463,16 @@ def load_mcore_checkpoint(args,

if finetune:
iteration = 0
if 'args' in state_dict and not finetune:
args.consumed_train_samples = getattr(state_dict['args'], 'consumed_train_samples', 0)
if 'args' in common_state_dict and not finetune:
args.consumed_train_samples = getattr(common_state_dict['args'], 'consumed_train_samples', 0)

if len(ddp_models) == 1:
ddp_models[0].load_state_dict(state_dict['model'], strict=False)
else:
for i, m in enumerate(ddp_models):
if f'model{i}' not in state_dict:
continue
m.load_state_dict(state_dict[f'model{i}'])
m.load_state_dict(state_dict[f'model{i}'], strict=False)

if not finetune and not no_load_optim:
if optimizer is not None:
Expand Down
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