ComfyUI/comfy/memory_management.py
2026-01-13 19:55:35 +10:00

52 lines
1.8 KiB
Python

import torch
from comfy.quant_ops import QuantizedTensor
def vram_aligned_size(tensor):
if isinstance(tensor, list):
return sum([vram_aligned_size(t) for t in tensor])
if isinstance(tensor, QuantizedTensor):
inner_tensors, _ = tensor.__tensor_flatten__()
return vram_aligned_size([ getattr(tensor, attr) for attr in inner_tensors ])
if tensor is None:
return 0
size = tensor.numel() * tensor.element_size()
aligment_req = 1024
return (size + aligment_req - 1) // aligment_req * aligment_req
def interpret_gathered_like(tensors, gathered):
offset = 0
dest_views = []
if gathered.dim() != 1 or gathered.element_size() != 1:
raise ValueError(f"Buffer must be 1D and single-byte (got {gathered.dim()}D {gathered.dtype})")
for tensor in tensors:
if tensor is None:
dest_views.append(None)
continue
if isinstance(tensor, QuantizedTensor):
inner_tensors, qt_ctx = tensor.__tensor_flatten__()
templates = { attr: getattr(tensor, attr) for attr in inner_tensors }
else:
templates = { "data": tensor }
actuals = {}
for attr, template in templates.items():
size = template.numel() * template.element_size()
if offset + size > gathered.numel():
raise ValueError(f"Buffer too small: needs {offset + size} bytes, but only has {gathered.numel()}. ")
actuals[attr] = gathered[offset:offset+size].view(dtype=template.dtype).view(template.shape)
offset += vram_aligned_size(template)
if isinstance(tensor, QuantizedTensor):
dest_views.append(QuantizedTensor.__tensor_unflatten__(actuals, qt_ctx, 0, 0))
else:
dest_views.append(actuals["data"])
return dest_views