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move string_to_seed to utils.py

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This needs to be visible by ops which may want to do stochastic rounding on
the fly.
This commit is contained in:
Rattus 2026-01-08 18:21:50 +10:00
parent babccae951
commit f1e8ccae5c
2 changed files with 17 additions and 17 deletions
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21
comfy/model_patcher.py
View File

@ -40,19 +40,6 @@ from comfy.quant_ops import QuantizedTensor
from comfy.patcher_extension import CallbacksMP, PatcherInjection, WrappersMP from comfy.patcher_extension import CallbacksMP, PatcherInjection, WrappersMP
def string_to_seed(data):
crc = 0xFFFFFFFF
for byte in data:
if isinstance(byte, str):
byte = ord(byte)
crc ^= byte
for _ in range(8):
if crc & 1:
crc = (crc >> 1) ^ 0xEDB88320
else:
crc >>= 1
return crc ^ 0xFFFFFFFF
def set_model_options_patch_replace(model_options, patch, name, block_name, number, transformer_index=None): def set_model_options_patch_replace(model_options, patch, name, block_name, number, transformer_index=None):
to = model_options["transformer_options"].copy() to = model_options["transformer_options"].copy()
@ -653,7 +640,7 @@ class ModelPatcher:
out_weight = comfy.lora.calculate_weight(self.patches[key], temp_weight, key) out_weight = comfy.lora.calculate_weight(self.patches[key], temp_weight, key)
if set_func is None: if set_func is None:
out_weight = comfy.float.stochastic_rounding(out_weight, weight.dtype, seed=string_to_seed(key)) out_weight = comfy.float.stochastic_rounding(out_weight, weight.dtype, seed=comfy.utils.string_to_seed(key))
if return_weight: if return_weight:
return out_weight return out_weight
elif inplace_update: elif inplace_update:
@ -661,7 +648,7 @@ class ModelPatcher:
else: else:
comfy.utils.set_attr_param(self.model, key, out_weight) comfy.utils.set_attr_param(self.model, key, out_weight)
else: else:
return set_func(out_weight, inplace_update=inplace_update, seed=string_to_seed(key), return_weight=return_weight) return set_func(out_weight, inplace_update=inplace_update, seed=comfy.utils.string_to_seed(key), return_weight=return_weight)
def pin_weight_to_device(self, key): def pin_weight_to_device(self, key):
weight, set_func, convert_func = get_key_weight(self.model, key) weight, set_func, convert_func = get_key_weight(self.model, key)
@ -1341,10 +1328,10 @@ class ModelPatcher:
key, original_weights=original_weights) key, original_weights=original_weights)
del original_weights[key] del original_weights[key]
if set_func is None: if set_func is None:
out_weight = comfy.float.stochastic_rounding(out_weight, weight.dtype, seed=string_to_seed(key)) out_weight = comfy.float.stochastic_rounding(out_weight, weight.dtype, seed=comfy.utils.string_to_seed(key))
comfy.utils.copy_to_param(self.model, key, out_weight) comfy.utils.copy_to_param(self.model, key, out_weight)
else: else:
set_func(out_weight, inplace_update=True, seed=string_to_seed(key)) set_func(out_weight, inplace_update=True, seed=comfy.utils.string_to_seed(key))
if self.hook_mode == comfy.hooks.EnumHookMode.MaxSpeed: if self.hook_mode == comfy.hooks.EnumHookMode.MaxSpeed:
# TODO: disable caching if not enough system RAM to do so # TODO: disable caching if not enough system RAM to do so
target_device = self.offload_device target_device = self.offload_device

13
comfy/utils.py
View File

@ -1267,3 +1267,16 @@ def convert_old_quants(state_dict, model_prefix="", metadata={}):
state_dict["{}.comfy_quant".format(k)] = torch.tensor(list(json.dumps(v).encode('utf-8')), dtype=torch.uint8) state_dict["{}.comfy_quant".format(k)] = torch.tensor(list(json.dumps(v).encode('utf-8')), dtype=torch.uint8)
return state_dict, metadata return state_dict, metadata
def string_to_seed(data):
crc = 0xFFFFFFFF
for byte in data:
if isinstance(byte, str):
byte = ord(byte)
crc ^= byte
for _ in range(8):
if crc & 1:
crc = (crc >> 1) ^ 0xEDB88320
else:
crc >>= 1
return crc ^ 0xFFFFFFFF