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Faster workflow cancelling. #10301

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Merged
merged 1 commit into from
Oct 14, 2025
Merged

Faster workflow cancelling. #10301

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12 changes: 12 additions & 0 deletions comfy/ops.py
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Original file line number Diff line number Diff line change
Expand Up @@ -24,6 +24,8 @@
import comfy.rmsnorm
import contextlib

def run_every_op():
comfy.model_management.throw_exception_if_processing_interrupted()

def scaled_dot_product_attention(q, k, v, *args, **kwargs):
return torch.nn.functional.scaled_dot_product_attention(q, k, v, *args, **kwargs)
Expand Down Expand Up @@ -109,6 +111,7 @@ def forward_comfy_cast_weights(self, input):
return torch.nn.functional.linear(input, weight, bias)

def forward(self, *args, **kwargs):
run_every_op()
if self.comfy_cast_weights or len(self.weight_function) > 0 or len(self.bias_function) > 0:
return self.forward_comfy_cast_weights(*args, **kwargs)
else:
Expand All @@ -123,6 +126,7 @@ def forward_comfy_cast_weights(self, input):
return self._conv_forward(input, weight, bias)

def forward(self, *args, **kwargs):
run_every_op()
if self.comfy_cast_weights or len(self.weight_function) > 0 or len(self.bias_function) > 0:
return self.forward_comfy_cast_weights(*args, **kwargs)
else:
Expand All @@ -137,6 +141,7 @@ def forward_comfy_cast_weights(self, input):
return self._conv_forward(input, weight, bias)

def forward(self, *args, **kwargs):
run_every_op()
if self.comfy_cast_weights or len(self.weight_function) > 0 or len(self.bias_function) > 0:
return self.forward_comfy_cast_weights(*args, **kwargs)
else:
Expand All @@ -151,6 +156,7 @@ def forward_comfy_cast_weights(self, input):
return self._conv_forward(input, weight, bias)

def forward(self, *args, **kwargs):
run_every_op()
if self.comfy_cast_weights or len(self.weight_function) > 0 or len(self.bias_function) > 0:
return self.forward_comfy_cast_weights(*args, **kwargs)
else:
Expand All @@ -165,6 +171,7 @@ def forward_comfy_cast_weights(self, input):
return torch.nn.functional.group_norm(input, self.num_groups, weight, bias, self.eps)

def forward(self, *args, **kwargs):
run_every_op()
if self.comfy_cast_weights or len(self.weight_function) > 0 or len(self.bias_function) > 0:
return self.forward_comfy_cast_weights(*args, **kwargs)
else:
Expand All @@ -183,6 +190,7 @@ def forward_comfy_cast_weights(self, input):
return torch.nn.functional.layer_norm(input, self.normalized_shape, weight, bias, self.eps)

def forward(self, *args, **kwargs):
run_every_op()
if self.comfy_cast_weights or len(self.weight_function) > 0 or len(self.bias_function) > 0:
return self.forward_comfy_cast_weights(*args, **kwargs)
else:
Expand All @@ -202,6 +210,7 @@ def forward_comfy_cast_weights(self, input):
# return torch.nn.functional.rms_norm(input, self.normalized_shape, weight, self.eps)

def forward(self, *args, **kwargs):
run_every_op()
if self.comfy_cast_weights or len(self.weight_function) > 0 or len(self.bias_function) > 0:
return self.forward_comfy_cast_weights(*args, **kwargs)
else:
Expand All @@ -223,6 +232,7 @@ def forward_comfy_cast_weights(self, input, output_size=None):
output_padding, self.groups, self.dilation)

def forward(self, *args, **kwargs):
run_every_op()
if self.comfy_cast_weights or len(self.weight_function) > 0 or len(self.bias_function) > 0:
return self.forward_comfy_cast_weights(*args, **kwargs)
else:
Expand All @@ -244,6 +254,7 @@ def forward_comfy_cast_weights(self, input, output_size=None):
output_padding, self.groups, self.dilation)

def forward(self, *args, **kwargs):
run_every_op()
if self.comfy_cast_weights or len(self.weight_function) > 0 or len(self.bias_function) > 0:
return self.forward_comfy_cast_weights(*args, **kwargs)
else:
Expand All @@ -262,6 +273,7 @@ def forward_comfy_cast_weights(self, input, out_dtype=None):
return torch.nn.functional.embedding(input, weight, self.padding_idx, self.max_norm, self.norm_type, self.scale_grad_by_freq, self.sparse).to(dtype=output_dtype)

def forward(self, *args, **kwargs):
run_every_op()
if self.comfy_cast_weights or len(self.weight_function) > 0 or len(self.bias_function) > 0:
return self.forward_comfy_cast_weights(*args, **kwargs)
else:
Expand Down