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Changes in create_optimizer to support tensor parallelism with SMP #16880

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Apr 22, 2022
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Changes in create_optimizer to support tensor parallelism with SMP #16880

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changes in create optimizer to support tensor parallelism with SMP
Apr 20, 2022
05cb2d5
Update src/transformers/trainer.py
cavdard Apr 22, 2022
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13 changes: 9 additions & 4 deletions src/transformers/trainer.py
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Original file line number Diff line number Diff line change
Expand Up @@ -843,16 +843,21 @@ def create_optimizer(self):
We provide a reasonable default that works well. If you want to use something else, you can pass a tuple in the
Trainer's init through `optimizers`, or subclass and override this method in a subclass.
"""
if is_sagemaker_mp_enabled():
opt_model = self.model_wrapped
else:
opt_model = self.model
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if self.optimizer is None:
decay_parameters = get_parameter_names(self.model, [nn.LayerNorm])
decay_parameters = get_parameter_names(opt_model, [nn.LayerNorm])
decay_parameters = [name for name in decay_parameters if "bias" not in name]
optimizer_grouped_parameters = [
{
"params": [p for n, p in self.model.named_parameters() if n in decay_parameters],
"params": [p for n, p in opt_model.named_parameters() if n in decay_parameters],
"weight_decay": self.args.weight_decay,
},
{
"params": [p for n, p in self.model.named_parameters() if n not in decay_parameters],
"params": [p for n, p in opt_model.named_parameters() if n not in decay_parameters],
"weight_decay": 0.0,
},
]
Expand All @@ -872,7 +877,7 @@ def create_optimizer(self):

manager = bitsandbytes.optim.GlobalOptimManager.get_instance()

for module in self.model.modules():
for module in opt_model.modules():
if isinstance(module, nn.Embedding):
manager.register_module_override(module, "weight", {"optim_bits": 32})
logger.debug(f"bitsandbytes: will optimize {module} in fp32")
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