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Lazy loader needs to cache named buffers of layers in the disk cache

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Gnome Ann
2022-06-20 17:08:52 -04:00
parent ab5ab79003
commit 1620ac4148
1 changed files with 4 additions and 1 deletions
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5
aiserver.py
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@@ -1718,7 +1718,6 @@ def load_model(use_gpu=True, gpu_layers=None, disk_layers=None, initial_load=Fal
lazy_load_callback.nested = True lazy_load_callback.nested = True
device_map: Dict[str, Union[str, int]] = {} device_map: Dict[str, Union[str, int]] = {}
offload_map: Dict[str, str] = {}
@functools.lru_cache(maxsize=None) @functools.lru_cache(maxsize=None)
def get_original_key(key): def get_original_key(key):
@@ -1801,6 +1800,9 @@ def load_model(use_gpu=True, gpu_layers=None, disk_layers=None, initial_load=Fal
finally: finally:
if utils.num_shards is None or utils.current_shard >= utils.num_shards: if utils.num_shards is None or utils.current_shard >= utils.num_shards:
if utils.offload_index: if utils.offload_index:
for name, tensor in vars.named_buffers:
if name not in utils.offload_index:
accelerate.utils.offload_weight(tensor, name, "accelerate-disk-cache", index=utils.offload_index)
accelerate.utils.save_offload_index(utils.offload_index, "accelerate-disk-cache") accelerate.utils.save_offload_index(utils.offload_index, "accelerate-disk-cache")
utils.bar.close() utils.bar.close()
utils.bar = None utils.bar = None
@@ -1895,6 +1897,7 @@ def load_model(use_gpu=True, gpu_layers=None, disk_layers=None, initial_load=Fal
metamodel = GPTNeoForCausalLM.from_config(model_config) metamodel = GPTNeoForCausalLM.from_config(model_config)
vars.layers_module_names = utils.get_layers_module_names(metamodel) vars.layers_module_names = utils.get_layers_module_names(metamodel)
vars.module_names = list(metamodel.state_dict().keys()) vars.module_names = list(metamodel.state_dict().keys())
vars.named_buffers = list(metamodel.named_buffers(recurse=True))
with maybe_use_float16(), torch_lazy_loader.use_lazy_torch_load(enable=vars.lazy_load, callback=get_lazy_load_callback(utils.num_layers(model_config)) if vars.lazy_load else None, dematerialized_modules=True): with maybe_use_float16(), torch_lazy_loader.use_lazy_torch_load(enable=vars.lazy_load, callback=get_lazy_load_callback(utils.num_layers(model_config)) if vars.lazy_load else None, dematerialized_modules=True):
if(vars.lazy_load): # torch_lazy_loader.py and low_cpu_mem_usage can't be used at the same time if(vars.lazy_load): # torch_lazy_loader.py and low_cpu_mem_usage can't be used at the same time
lowmem = {} lowmem = {}