Spaces:
Running
on
Zero
Running
on
Zero
File size: 1,425 Bytes
e75a609 |
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 |
"""
"""
from typing import cast
import torch
from huggingface_hub import hf_hub_download
from spaces.zero.torch.aoti import ZeroGPUCompiledModel
from spaces.zero.torch.aoti import ZeroGPUWeights
from torch._functorch._aot_autograd.subclass_parametrization import unwrap_tensor_subclass_parameters
def _shallow_clone_module(module: torch.nn.Module) -> torch.nn.Module:
clone = object.__new__(module.__class__)
clone.__dict__ = module.__dict__.copy()
clone._parameters = module._parameters.copy()
clone._buffers = module._buffers.copy()
clone._modules = {k: _shallow_clone_module(v) for k, v in module._modules.items() if v is not None}
return clone
def aoti_blocks_load(module: torch.nn.Module, repo_id: str, variant: str | None = None):
repeated_blocks = cast(list[str], module._repeated_blocks)
aoti_files = {name: hf_hub_download(
repo_id=repo_id,
filename='package.pt2',
subfolder=name if variant is None else f'{name}.{variant}',
) for name in repeated_blocks}
for block_name, aoti_file in aoti_files.items():
for block in module.modules():
if block.__class__.__name__ == block_name:
block_ = _shallow_clone_module(block)
unwrap_tensor_subclass_parameters(block_)
weights = ZeroGPUWeights(block_.state_dict())
block.forward = ZeroGPUCompiledModel(aoti_file, weights)
|