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import os
from collections import OrderedDict
from safetensors.torch import save_file
from jobs.process.BaseProcess import BaseProcess
from toolkit.metadata import get_meta_for_safetensors
from toolkit.train_tools import get_torch_dtype
class BaseMergeProcess(BaseProcess):
def __init__(
self,
process_id: int,
job,
config: OrderedDict
):
super().__init__(process_id, job, config)
self.process_id: int
self.config: OrderedDict
self.output_path = self.get_conf('output_path', required=True)
self.dtype = self.get_conf('dtype', self.job.dtype)
self.torch_dtype = get_torch_dtype(self.dtype)
def run(self):
# implement in child class
# be sure to call super().run() first
pass
def save(self, state_dict):
# prepare meta
save_meta = get_meta_for_safetensors(self.meta, self.job.name)
# save
os.makedirs(os.path.dirname(self.output_path), exist_ok=True)
for key in list(state_dict.keys()):
v = state_dict[key]
v = v.detach().clone().to("cpu").to(self.torch_dtype)
state_dict[key] = v
# having issues with meta
save_file(state_dict, self.output_path, save_meta)
print(f"Saved to {self.output_path}")
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