Make T2IAdapter work with uncond_multiplier (results are not great when < 1.0, but match up exactly with auto1111 results)

adv_control/control.py

@@ -95,6 +95,23 @@ class T2IAdapterAdvanced(T2IAdapter, AdvancedControlBase):
         super().__init__(t2i_model=t2i_model, channels_in=channels_in, compression_ratio=compression_ratio, upscale_algorithm=upscale_algorithm, device=device)
         AdvancedControlBase.__init__(self, super(), timestep_keyframes=timestep_keyframes, weights_default=ControlWeights.t2iadapter())
 
+    def control_merge_inject(self, control_input, control_output, control_prev, output_dtype):
+        # if has uncond multiplier, need to make sure control shapes are the same batch size as expected
+        if self.weights.has_uncond_multiplier:
+            if control_input is not None:
+                for i in range(len(control_input)):
+                    x = control_input[i]
+                    if x is not None:
+                        if x.size(0) < self.batch_size:
+                            control_input[i] = x.repeat(self.batched_number, 1, 1, 1)[:self.batch_size]
+            if control_output is not None:
+                for i in range(len(control_output)):
+                    x = control_output[i]
+                    if x is not None:
+                        if x.size(0) < self.batch_size:
+                            control_output[i] = x.repeat(self.batched_number, 1, 1, 1)[:self.batch_size]
+        return AdvancedControlBase.control_merge_inject(self, control_input, control_output, control_prev, output_dtype)
+
     def get_universal_weights(self) -> ControlWeights:
         raw_weights = [(self.weights.base_multiplier ** float(7 - i)) for i in range(8)]
         raw_weights = [raw_weights[-8], raw_weights[-3], raw_weights[-2], raw_weights[-1]]

adv_control/utils.py

@@ -520,6 +520,7 @@ class AdvancedControlBase:
         # timesteps
         self.t: Tensor = None
         self.batched_number: int = None
+        self.batch_size: int = 0
         # weights + override
         self.weights: ControlWeights = None
         self.weights_default: ControlWeights = weights_default
@@ -573,6 +574,7 @@ class AdvancedControlBase:
     def prepare_current_timestep(self, t: Tensor, batched_number: int):
         self.t = float(t[0])
         self.batched_number = batched_number
+        self.batch_size = len(t)
         # get current step percent
         curr_t: float = self.t
         prev_index = self._current_timestep_index
@@ -667,8 +669,6 @@ class AdvancedControlBase:
         return True
 
     def get_control_inject(self, x_noisy, t, cond, batched_number):
-        if type(batched_number) != IntWithCondOrUncond:
-            logger.warn(f"not IntWithCondOrUncond! {type(batched_number)}")
         # prepare timestep and everything related
         self.prepare_current_timestep(t=t, batched_number=batched_number)
         # if should not perform any actions for the controlnet, exit without doing any work
@@ -869,6 +869,7 @@ class AdvancedControlBase:
         self.context_length = 0
         self.t = None
         self.batched_number = None
+        self.batch_size = 0
         self.weights = None
         self.latent_keyframes = None
         # timestep stuff