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Bugfixes for slider reference

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This commit is contained in:
Jaret Burkett
2023-09-10 18:36:23 -06:00
parent b5ec8e4eb1
commit 083cefa78c
2 changed files with 10 additions and 2 deletions
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8
extensions_built_in/image_reference_slider_trainer/ImageReferenceSliderTrainerProcess.py
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@@ -159,7 +159,13 @@ class ImageReferenceSliderTrainerProcess(BaseSDTrainProcess):
# if training text encoder enable grads, else do context of no grad # if training text encoder enable grads, else do context of no grad
with torch.set_grad_enabled(self.train_config.train_text_encoder): with torch.set_grad_enabled(self.train_config.train_text_encoder):
conditional_embeds = self.sd.encode_prompt(prompts).to(self.device_torch, dtype=dtype) # fix issue with them being tuples sometimes
prompt_list = []
for prompt in prompts:
if isinstance(prompt, tuple):
prompt = prompt[0]
prompt_list.append(prompt)
conditional_embeds = self.sd.encode_prompt(prompt_list).to(self.device_torch, dtype=dtype)
conditional_embeds = concat_prompt_embeds([conditional_embeds, conditional_embeds]) conditional_embeds = concat_prompt_embeds([conditional_embeds, conditional_embeds])
# if self.model_config.is_xl: # if self.model_config.is_xl:

4
toolkit/network_mixins.py
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@@ -55,7 +55,7 @@ class ToolkitModuleMixin:
self.is_checkpointing = False self.is_checkpointing = False
self.is_normalizing = False self.is_normalizing = False
self.normalize_scaler = 1.0 self.normalize_scaler = 1.0
self._multiplier: Union[float, list, torch.Tensor] = 1.0 self._multiplier: Union[float, list, torch.Tensor] = None
# this allows us to set different multipliers on a per item in a batch basis # this allows us to set different multipliers on a per item in a batch basis
# allowing us to run positive and negative weights in the same batch # allowing us to run positive and negative weights in the same batch
@@ -123,6 +123,8 @@ class ToolkitModuleMixin:
return lx * scale return lx * scale
def forward(self: Module, x): def forward(self: Module, x):
if self._multiplier is None:
self.set_multiplier(0.0)
org_forwarded = self.org_forward(x) org_forwarded = self.org_forward(x)
lora_output = self._call_forward(x) lora_output = self._call_forward(x)