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strint 2025-10-21 02:27:40 +08:00
parent 49561788cf
commit 8aeebbf7ef
1 changed files with 18 additions and 7 deletions
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25
comfy/model_patcher.py
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@ -794,17 +794,28 @@ class ModelPatcher:
"""Convert all parameters and buffers to memory-mapped tensors
This method mimics PyTorch's Module.to() behavior but converts
tensors to memory-mapped format instead.
tensors to memory-mapped format instead, using _apply() method.
Note: For Parameters, we modify .data in-place because
MemoryMappedTensor cannot be wrapped in torch.nn.Parameter.
For buffers, _apply() will automatically update the reference.
"""
import pdb; pdb.set_trace()
logging.info(f"model {self.__class__.__name__} is calling to_mmap method")
def convert_fn(t):
if isinstance(t, torch.Tensor) and not isinstance(t, torch.nn.Parameter):
"""Convert function for _apply()
- For Parameters: modify .data and return the Parameter object
- For buffers (plain Tensors): return new MemoryMappedTensor
"""
if isinstance(t, torch.nn.Parameter):
# For parameters, modify data in-place and return the parameter
if isinstance(t.data, torch.Tensor):
t.data = to_mmap(t.data)
return t
elif isinstance(t, torch.Tensor):
# For buffers (plain tensors), return the converted tensor
return to_mmap(t)
elif isinstance(t, torch.nn.Parameter):
# For parameters, convert the data and wrap back in Parameter
param_mmap = to_mmap(t.data)
return torch.nn.Parameter(param_mmap, requires_grad=t.requires_grad)
return t
return self._apply(convert_fn)