mirror of https://github.com/hpcaitech/ColossalAI
73 lines
2.6 KiB
Python
73 lines
2.6 KiB
Python
from .colo_tensor import ColoTensor
|
|
from .const import TensorType
|
|
import torch
|
|
from colossalai.tensor import TensorSpec, distspec
|
|
from copy import copy
|
|
from typing import Optional
|
|
|
|
class ColoParameter(ColoTensor, torch.nn.Parameter):
|
|
r"""A kind of ColoTensor to be considered as a module parameter.
|
|
|
|
"""
|
|
|
|
def __new__(cls,
|
|
data: Optional[torch.Tensor] = None,
|
|
requires_grad: bool = True,
|
|
spec: TensorSpec = TensorSpec(distspec.replicate())) -> 'ColoParameter':
|
|
if data is None:
|
|
data = torch.empty(0)
|
|
return torch.Tensor._make_subclass(cls, data, requires_grad)
|
|
|
|
def __init__(self,
|
|
data: Optional[torch.Tensor] = None,
|
|
requires_grad: bool = True,
|
|
spec: TensorSpec = TensorSpec(distspec.replicate())) -> None:
|
|
self._spec = copy(spec)
|
|
self._type = TensorType.MODEL
|
|
self._graph_node = None
|
|
|
|
# a list contains modules sharing this ColoParameter with others.
|
|
self._shared_param_modules = []
|
|
|
|
@property
|
|
def shared_param_modules(self):
|
|
return self._shared_param_modules
|
|
|
|
@staticmethod
|
|
def from_torch_tensor(tensor: torch.Tensor,
|
|
requires_grad: bool = True,
|
|
spec: TensorSpec = TensorSpec(distspec.replicate())) -> 'ColoParameter':
|
|
tensor = tensor.as_subclass(ColoParameter)
|
|
tensor.__init__(tensor, requires_grad=requires_grad, spec=spec)
|
|
return tensor
|
|
|
|
def __repr__(self):
|
|
return f'ColoParameter: {torch.Tensor.__repr__(self)}'
|
|
|
|
def __deepcopy__(self, memo):
|
|
if id(self) in memo:
|
|
return memo[id(self)]
|
|
else:
|
|
with torch._C.DisableTorchFunction():
|
|
data = self.data.clone()
|
|
tensor = ColoParameter(data, self.requires_grad, spec=copy(self.spec))
|
|
memo[id(self)] = tensor
|
|
return tensor
|
|
|
|
def __reduce_ex__(self, proto):
|
|
# Adapted from torch._utils._rebuild_parameter
|
|
# def _rebuild_colo_parameter(data, requires_grad, backward_hooks):
|
|
# colo_param = ColoParameter(data, requires_grad)
|
|
# colo_param._backward_hooks = backward_hooks
|
|
# return colo_param
|
|
|
|
# return (
|
|
# _rebuild_colo_parameter,
|
|
# (self.data, self.requires_grad, OrderedDict())
|
|
# )
|
|
|
|
# TODO(jzy) we don't support object reflection now.
|
|
# distspec cannot be pickled or rebuilt because it's tightly connected to runtime attribute `process_group`.
|
|
raise NotImplementedError
|
|
|