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[sync] Save memory using main_param for moe in param_l2_norm #2091

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[sync] Save memory using main_param for moe in param_l2_norm #2091

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17 changes: 14 additions & 3 deletions src/megatron/bridge/training/utils/train_utils.py
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Original file line number Diff line number Diff line change
Expand Up @@ -127,7 +127,7 @@ def calc_params_l2_norm(

return calc_dtensor_params_l2_norm(params)

# Seperate moe and dense params
# Separate moe and dense params
params_data = []
moe_params_data = []
sharded_params_data = []
Expand All @@ -141,10 +141,21 @@ def calc_params_l2_norm(
continue
assert is_not_tp_duplicate
if not getattr(param, "allreduce", True):
# TODO: Implement memory optimization for MoE parameters.
assert param_is_not_shared(param)
param = to_local_if_dtensor(param)
moe_params_data.append(param.data.float() if model_config.bf16 else param.data)
if model_config.bf16:
if not force_create_fp32_copy and hasattr(param, "main_param"):
if getattr(param, "main_param_sharded", False):
if param.main_param is not None:
sharded_params_data.append(param.main_param)
else:
moe_params_data.append(param.main_param)
else:
# Fallback to original logic of making a fp32 copy of the
# parameter if `.main_param` attribute is not available.
moe_params_data.append(param.data.float())
else:
moe_params_data.append(param.data)
else:
if param_is_not_shared(param):
param = to_local_if_dtensor(param)
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