ColossalAI/colossalai/gemini/tensor/utils.py

38 lines
1.3 KiB
Python

import torch
import torch.distributed as dist
from torch.distributed import distributed_c10d
from colossalai.gemini.tensor.stateful_tensor import StatefulTensorV2
def _convert_tensor(tensor: torch.Tensor) -> StatefulTensorV2:
if not tensor.is_contiguous():
raise ValueError('input tensor is not a contiguous Tensor')
return StatefulTensorV2(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 StatefulTensorV2.
# Need to delete the attribute first since param_name might be
# torch.nn.Parameter and can't be replaced with StatefulTensorV2 which is
# not torch.nn.Parameter.
delattr(module, param_name)
# Now we can set the attribute appropriately.
setattr(module, param_name, st)