Precisely track nvme optimizer offload (#6963)

Fix #4998
This commit is contained in:
Olatunji Ruwase 2025-01-23 11:42:06 -05:00 коммит произвёл GitHub
Родитель de4596bedc
Коммит 470dd6dceb
Не найден ключ, соответствующий данной подписи
Идентификатор ключа GPG: B5690EEEBB952194
4 изменённых файлов: 16 добавлений и 15 удалений

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@ -799,10 +799,8 @@ class DeepSpeedEngine(Module):
def zero_elastic_checkpoint(self):
return self._config.zero_config.elastic_checkpoint
def zero_has_nvme_offload(self):
if not hasattr(self.optimizer, "swap_optimizer"):
return False
return self.optimizer.swap_optimizer or self.optimizer.params_in_nvme_and_cpu
def zero_nvme_offload_optimizer(self):
return getattr(self.optimizer, "swap_optimizer", False)
def zero_max_live_parameters(self):
return self._config.zero_config.max_live_parameters
@ -2865,7 +2863,7 @@ class DeepSpeedEngine(Module):
if not success:
self.optimizer._restore_from_bit16_weights()
if self.zero_has_nvme_offload():
if self.zero_nvme_offload_optimizer():
from shutil import copytree, disk_usage
offload_dir = self.optimizer.optimizer_swapper.swap_folder
offload_ckpt_dir = os.path.join(load_dir, tag, "offloaded_tensors")
@ -3205,7 +3203,7 @@ class DeepSpeedEngine(Module):
self._create_zero_checkpoint_files(save_dir, tag)
self._save_zero_checkpoint(save_dir, tag)
if self.zero_has_nvme_offload():
if self.zero_nvme_offload_optimizer():
from shutil import copytree, disk_usage
offload_dir = self.optimizer.optimizer_swapper.swap_folder
offload_ckpt_dir = os.path.join(save_dir, tag, "offloaded_tensors")

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@ -153,6 +153,11 @@ class OptimizerSwapper(object):
'timer_names',
]
def purge_state(self):
for swap_info in self.swap_params_info.values():
swap_info.tensors = [swap_info.tensors[0]]
swap_info.has_state_tensors = False
def swappable_tensor(self, param=None, numel=None):
assert param is not None or numel is not None, "Either param or numel must be provided"
if param is not None:

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@ -2652,11 +2652,9 @@ class DeepSpeedZeroOptimizer_Stage3(ZeROOptimizer):
self.optimizer.load_state_dict(state_dict[OPTIMIZER_STATE_DICT])
self._clear_fp32_optimizer_param_groups()
if self.swap_optimizer or self.params_in_nvme_and_cpu:
if self.swap_optimizer:
# Purge the swapped optimizer state, it was initialized to the freshly created model and not the checkpoint
for swap_info in self.optimizer_swapper.swap_params_info.values():
swap_info.tensors = [swap_info.tensors[0]]
swap_info.has_state_tensors = False
self.optimizer_swapper.purge_state()
if self.swap_optimizer:
# Touch all parameters to synchronize all buffers
@ -2773,11 +2771,9 @@ class DeepSpeedZeroOptimizer_Stage3(ZeROOptimizer):
else:
optim_sd[OPTIMIZER_STATE_DICT]['state'][0][key] = key_tensor
if self.swap_optimizer or self.params_in_nvme_and_cpu:
if self.swap_optimizer:
# Purge the swapped optimizer state, it was initialized to the freshly created model and not the checkpoint
for swap_info in self.optimizer_swapper.swap_params_info.values():
swap_info.tensors = [swap_info.tensors[0]]
swap_info.has_state_tensors = False
self.optimizer_swapper.purge_state()
if self.swap_optimizer:
# Touch all parameters to synchronize all buffers

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@ -22,8 +22,10 @@ class TestNVMeCheckpointing(DistributedTest):
world_size = 1
@pytest.mark.parametrize('param_offload_device, optim_offload_device',
[(OffloadDeviceEnum.cpu, OffloadDeviceEnum.cpu),
[(OffloadDeviceEnum.none, OffloadDeviceEnum.nvme),
(OffloadDeviceEnum.cpu, OffloadDeviceEnum.nvme),
(OffloadDeviceEnum.nvme, OffloadDeviceEnum.none),
(OffloadDeviceEnum.nvme, OffloadDeviceEnum.cpu),
(OffloadDeviceEnum.nvme, OffloadDeviceEnum.nvme)])
def test_nvme_checkpointing(self, tmpdir, param_offload_device, optim_offload_device):
zero_dir, ckpt_dir = os.path.join(tmpdir, "zero"), os.path.join(tmpdir, "checkpoint")