Making large AI models cheaper, faster and more accessible
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import torch
from colossalai.tensor.colo_tensor import ColoTensor
def _convert_tensor(tensor: torch.Tensor) -> ColoTensor:
return ColoTensor(tensor)
def convert_parameter(module: torch.nn.Module, param_name: str):
# Perform some validation first.
if not hasattr(module, param_name):
raise ValueError(f'module: {module} does not have parameter with name: {param_name}')
tensor = getattr(module, param_name)
if not isinstance(tensor, torch.Tensor):
raise ValueError(
f'Expected {type(module).__name__}.{param_name} to be a Tensor, but found {type(tensor).__name__}')
if not tensor.is_contiguous():
raise ValueError(f'param: {param_name} is not a contiguous Tensor')
st = _convert_tensor(tensor)
# Replace param with ColoTensor.
# Need to delete the attribute first since param_name might be
# torch.nn.Parameter and can't be replaced with ColoTensor which is
# not torch.nn.Parameter.
delattr(module, param_name)
# Now we can set the attribute appropriately.
setattr(module, param_name, st)