[PEFT / LoRA ] Fix text encoder scaling

src/diffusers/models/lora.py

@@ -19,27 +19,24 @@
 from torch import nn
 
 from ..loaders import PatchedLoraProjection, text_encoder_attn_modules, text_encoder_mlp_modules
-from ..utils import logging, scale_lora_layers
+from ..utils import logging
 
 
 logger = logging.get_logger(__name__)  # pylint: disable=invalid-name
 
 
-def adjust_lora_scale_text_encoder(text_encoder, lora_scale: float = 1.0, use_peft_backend: bool = False):
-    if use_peft_backend:
-        scale_lora_layers(text_encoder, weight=lora_scale)
-    else:
-        for _, attn_module in text_encoder_attn_modules(text_encoder):
-            if isinstance(attn_module.q_proj, PatchedLoraProjection):
-                attn_module.q_proj.lora_scale = lora_scale
-                attn_module.k_proj.lora_scale = lora_scale
-                attn_module.v_proj.lora_scale = lora_scale
-                attn_module.out_proj.lora_scale = lora_scale
-
-        for _, mlp_module in text_encoder_mlp_modules(text_encoder):
-            if isinstance(mlp_module.fc1, PatchedLoraProjection):
-                mlp_module.fc1.lora_scale = lora_scale
-                mlp_module.fc2.lora_scale = lora_scale
+def adjust_lora_scale_text_encoder(text_encoder, lora_scale: float = 1.0):
+    for _, attn_module in text_encoder_attn_modules(text_encoder):
+        if isinstance(attn_module.q_proj, PatchedLoraProjection):
+            attn_module.q_proj.lora_scale = lora_scale
+            attn_module.k_proj.lora_scale = lora_scale
+            attn_module.v_proj.lora_scale = lora_scale
+            attn_module.out_proj.lora_scale = lora_scale
+
+    for _, mlp_module in text_encoder_mlp_modules(text_encoder):
+        if isinstance(mlp_module.fc1, PatchedLoraProjection):
+            mlp_module.fc1.lora_scale = lora_scale
+            mlp_module.fc2.lora_scale = lora_scale
 
 
 class LoRALinearLayer(nn.Module):

src/diffusers/pipelines/alt_diffusion/pipeline_alt_diffusion.py

@@ -25,7 +25,7 @@
 from ...models import AutoencoderKL, UNet2DConditionModel
 from ...models.lora import adjust_lora_scale_text_encoder
 from ...schedulers import KarrasDiffusionSchedulers
-from ...utils import deprecate, logging, replace_example_docstring
+from ...utils import deprecate, logging, replace_example_docstring, scale_lora_layers, unscale_lora_layers
 from ...utils.torch_utils import randn_tensor
 from ..pipeline_utils import DiffusionPipeline
 from ..stable_diffusion.safety_checker import StableDiffusionSafetyChecker
@@ -304,7 +304,10 @@ def encode_prompt(
             self._lora_scale = lora_scale
 
             # dynamically adjust the LoRA scale
-            adjust_lora_scale_text_encoder(self.text_encoder, lora_scale, self.use_peft_backend)
+            if not self.use_peft_backend:
+                adjust_lora_scale_text_encoder(self.text_encoder, lora_scale)
+            else:
+                scale_lora_layers(self.text_encoder, lora_scale)
 
         if prompt is not None and isinstance(prompt, str):
             batch_size = 1
@@ -429,6 +432,10 @@ def encode_prompt(
             negative_prompt_embeds = negative_prompt_embeds.repeat(1, num_images_per_prompt, 1)
             negative_prompt_embeds = negative_prompt_embeds.view(batch_size * num_images_per_prompt, seq_len, -1)
 
+        if isinstance(self, LoraLoaderMixin) and self.use_peft_backend:
+            # Retrieve the original scale by scaling back the LoRA layers
+            unscale_lora_layers(self.text_encoder)
+
         return prompt_embeds, negative_prompt_embeds
 
     def run_safety_checker(self, image, device, dtype):

src/diffusers/pipelines/alt_diffusion/pipeline_alt_diffusion_img2img.py

@@ -27,7 +27,14 @@
 from ...models import AutoencoderKL, UNet2DConditionModel
 from ...models.lora import adjust_lora_scale_text_encoder
 from ...schedulers import KarrasDiffusionSchedulers
-from ...utils import PIL_INTERPOLATION, deprecate, logging, replace_example_docstring
+from ...utils import (
+    PIL_INTERPOLATION,
+    deprecate,
+    logging,
+    replace_example_docstring,
+    scale_lora_layers,
+    unscale_lora_layers,
+)
 from ...utils.torch_utils import randn_tensor
 from ..pipeline_utils import DiffusionPipeline
 from ..stable_diffusion.safety_checker import StableDiffusionSafetyChecker
@@ -302,7 +309,10 @@ def encode_prompt(
             self._lora_scale = lora_scale
 
             # dynamically adjust the LoRA scale
-            adjust_lora_scale_text_encoder(self.text_encoder, lora_scale, self.use_peft_backend)
+            if not self.use_peft_backend:
+                adjust_lora_scale_text_encoder(self.text_encoder, lora_scale)
+            else:
+                scale_lora_layers(self.text_encoder, lora_scale)
 
         if prompt is not None and isinstance(prompt, str):
             batch_size = 1
@@ -427,6 +437,10 @@ def encode_prompt(
             negative_prompt_embeds = negative_prompt_embeds.repeat(1, num_images_per_prompt, 1)
             negative_prompt_embeds = negative_prompt_embeds.view(batch_size * num_images_per_prompt, seq_len, -1)
 
+        if isinstance(self, LoraLoaderMixin) and self.use_peft_backend:
+            # Retrieve the original scale by scaling back the LoRA layers
+            unscale_lora_layers(self.text_encoder)
+
         return prompt_embeds, negative_prompt_embeds
 
     def run_safety_checker(self, image, device, dtype):

src/diffusers/pipelines/controlnet/pipeline_controlnet.py

@@ -27,11 +27,7 @@
 from ...models import AutoencoderKL, ControlNetModel, UNet2DConditionModel
 from ...models.lora import adjust_lora_scale_text_encoder
 from ...schedulers import KarrasDiffusionSchedulers
-from ...utils import (
-    deprecate,
-    logging,
-    replace_example_docstring,
-)
+from ...utils import deprecate, logging, replace_example_docstring, scale_lora_layers, unscale_lora_layers
 from ...utils.torch_utils import is_compiled_module, randn_tensor
 from ..pipeline_utils import DiffusionPipeline
 from ..stable_diffusion.pipeline_output import StableDiffusionPipelineOutput
@@ -291,7 +287,10 @@ def encode_prompt(
             self._lora_scale = lora_scale
 
             # dynamically adjust the LoRA scale
-            adjust_lora_scale_text_encoder(self.text_encoder, lora_scale, self.use_peft_backend)
+            if not self.use_peft_backend:
+                adjust_lora_scale_text_encoder(self.text_encoder, lora_scale)
+            else:
+                scale_lora_layers(self.text_encoder, lora_scale)
 
         if prompt is not None and isinstance(prompt, str):
             batch_size = 1
@@ -416,6 +415,10 @@ def encode_prompt(
             negative_prompt_embeds = negative_prompt_embeds.repeat(1, num_images_per_prompt, 1)
             negative_prompt_embeds = negative_prompt_embeds.view(batch_size * num_images_per_prompt, seq_len, -1)
 
+        if isinstance(self, LoraLoaderMixin) and self.use_peft_backend:
+            # Retrieve the original scale by scaling back the LoRA layers
+            unscale_lora_layers(self.text_encoder)
+
         return prompt_embeds, negative_prompt_embeds
 
     # Copied from diffusers.pipelines.stable_diffusion.pipeline_stable_diffusion.StableDiffusionPipeline.run_safety_checker

src/diffusers/pipelines/controlnet/pipeline_controlnet_img2img.py

@@ -30,6 +30,8 @@
     deprecate,
     logging,
     replace_example_docstring,
+    scale_lora_layers,
+    unscale_lora_layers,
 )
 from ...utils.torch_utils import is_compiled_module, randn_tensor
 from ..pipeline_utils import DiffusionPipeline
@@ -315,7 +317,10 @@ def encode_prompt(
             self._lora_scale = lora_scale
 
             # dynamically adjust the LoRA scale
-            adjust_lora_scale_text_encoder(self.text_encoder, lora_scale, self.use_peft_backend)
+            if not self.use_peft_backend:
+                adjust_lora_scale_text_encoder(self.text_encoder, lora_scale)
+            else:
+                scale_lora_layers(self.text_encoder, lora_scale)
 
         if prompt is not None and isinstance(prompt, str):
             batch_size = 1
@@ -440,6 +445,10 @@ def encode_prompt(
             negative_prompt_embeds = negative_prompt_embeds.repeat(1, num_images_per_prompt, 1)
             negative_prompt_embeds = negative_prompt_embeds.view(batch_size * num_images_per_prompt, seq_len, -1)
 
+        if isinstance(self, LoraLoaderMixin) and self.use_peft_backend:
+            # Retrieve the original scale by scaling back the LoRA layers
+            unscale_lora_layers(self.text_encoder)
+
         return prompt_embeds, negative_prompt_embeds
 
     # Copied from diffusers.pipelines.stable_diffusion.pipeline_stable_diffusion.StableDiffusionPipeline.run_safety_checker

src/diffusers/pipelines/controlnet/pipeline_controlnet_inpaint.py

@@ -28,11 +28,7 @@
 from ...models import AutoencoderKL, ControlNetModel, UNet2DConditionModel
 from ...models.lora import adjust_lora_scale_text_encoder
 from ...schedulers import KarrasDiffusionSchedulers
-from ...utils import (
-    deprecate,
-    logging,
-    replace_example_docstring,
-)
+from ...utils import deprecate, logging, replace_example_docstring, scale_lora_layers, unscale_lora_layers
 from ...utils.torch_utils import is_compiled_module, randn_tensor
 from ..pipeline_utils import DiffusionPipeline
 from ..stable_diffusion import StableDiffusionPipelineOutput
@@ -442,7 +438,10 @@ def encode_prompt(
             self._lora_scale = lora_scale
 
             # dynamically adjust the LoRA scale
-            adjust_lora_scale_text_encoder(self.text_encoder, lora_scale, self.use_peft_backend)
+            if not self.use_peft_backend:
+                adjust_lora_scale_text_encoder(self.text_encoder, lora_scale)
+            else:
+                scale_lora_layers(self.text_encoder, lora_scale)
 
         if prompt is not None and isinstance(prompt, str):
             batch_size = 1
@@ -567,6 +566,10 @@ def encode_prompt(
             negative_prompt_embeds = negative_prompt_embeds.repeat(1, num_images_per_prompt, 1)
             negative_prompt_embeds = negative_prompt_embeds.view(batch_size * num_images_per_prompt, seq_len, -1)
 
+        if isinstance(self, LoraLoaderMixin) and self.use_peft_backend:
+            # Retrieve the original scale by scaling back the LoRA layers
+            unscale_lora_layers(self.text_encoder)
+
         return prompt_embeds, negative_prompt_embeds
 
     # Copied from diffusers.pipelines.stable_diffusion.pipeline_stable_diffusion.StableDiffusionPipeline.run_safety_checker

src/diffusers/pipelines/controlnet/pipeline_controlnet_inpaint_sd_xl.py

@@ -36,6 +36,8 @@
     is_invisible_watermark_available,
     logging,
     replace_example_docstring,
+    scale_lora_layers,
+    unscale_lora_layers,
 )
 from ...utils.torch_utils import is_compiled_module, randn_tensor
 from ..pipeline_utils import DiffusionPipeline
@@ -314,8 +316,12 @@ def encode_prompt(
             self._lora_scale = lora_scale
 
             # dynamically adjust the LoRA scale
-            adjust_lora_scale_text_encoder(self.text_encoder, lora_scale, self.use_peft_backend)
-            adjust_lora_scale_text_encoder(self.text_encoder_2, lora_scale, self.use_peft_backend)
+            if not self.use_peft_backend:
+                adjust_lora_scale_text_encoder(self.text_encoder, lora_scale)
+                adjust_lora_scale_text_encoder(self.text_encoder_2, lora_scale)
+            else:
+                scale_lora_layers(self.text_encoder, lora_scale)
+                scale_lora_layers(self.text_encoder_2, lora_scale)
 
         prompt = [prompt] if isinstance(prompt, str) else prompt
 
@@ -452,6 +458,11 @@ def encode_prompt(
                 bs_embed * num_images_per_prompt, -1
             )
 
+        if isinstance(self, StableDiffusionXLLoraLoaderMixin) and self.use_peft_backend:
+            # Retrieve the original scale by scaling back the LoRA layers
+            unscale_lora_layers(self.text_encoder)
+            unscale_lora_layers(self.text_encoder_2)
+
         return prompt_embeds, negative_prompt_embeds, pooled_prompt_embeds, negative_pooled_prompt_embeds
 
     # Copied from diffusers.pipelines.stable_diffusion.pipeline_stable_diffusion.StableDiffusionPipeline.prepare_extra_step_kwargs

src/diffusers/pipelines/controlnet/pipeline_controlnet_sd_xl.py

@@ -35,10 +35,7 @@
 )
 from ...models.lora import adjust_lora_scale_text_encoder
 from ...schedulers import KarrasDiffusionSchedulers
-from ...utils import (
-    logging,
-    replace_example_docstring,
-)
+from ...utils import logging, replace_example_docstring, scale_lora_layers, unscale_lora_layers
 from ...utils.torch_utils import is_compiled_module, randn_tensor
 from ..pipeline_utils import DiffusionPipeline
 from ..stable_diffusion_xl.pipeline_output import StableDiffusionXLPipelineOutput
@@ -288,8 +285,12 @@ def encode_prompt(
             self._lora_scale = lora_scale
 
             # dynamically adjust the LoRA scale
-            adjust_lora_scale_text_encoder(self.text_encoder, lora_scale, self.use_peft_backend)
-            adjust_lora_scale_text_encoder(self.text_encoder_2, lora_scale, self.use_peft_backend)
+            if not self.use_peft_backend:
+                adjust_lora_scale_text_encoder(self.text_encoder, lora_scale)
+                adjust_lora_scale_text_encoder(self.text_encoder_2, lora_scale)
+            else:
+                scale_lora_layers(self.text_encoder, lora_scale)
+                scale_lora_layers(self.text_encoder_2, lora_scale)
 
         prompt = [prompt] if isinstance(prompt, str) else prompt
 
@@ -426,6 +427,11 @@ def encode_prompt(
                 bs_embed * num_images_per_prompt, -1
             )
 
+        if isinstance(self, StableDiffusionXLLoraLoaderMixin) and self.use_peft_backend:
+            # Retrieve the original scale by scaling back the LoRA layers
+            unscale_lora_layers(self.text_encoder)
+            unscale_lora_layers(self.text_encoder_2)
+
         return prompt_embeds, negative_prompt_embeds, pooled_prompt_embeds, negative_pooled_prompt_embeds
 
     # Copied from diffusers.pipelines.stable_diffusion.pipeline_stable_diffusion.StableDiffusionPipeline.prepare_extra_step_kwargs

src/diffusers/pipelines/controlnet/pipeline_controlnet_sd_xl_img2img.py

@@ -38,6 +38,8 @@
 from ...utils import (
     logging,
     replace_example_docstring,
+    scale_lora_layers,
+    unscale_lora_layers,
 )
 from ...utils.torch_utils import is_compiled_module, randn_tensor
 from ..pipeline_utils import DiffusionPipeline
@@ -326,8 +328,12 @@ def encode_prompt(
             self._lora_scale = lora_scale
 
             # dynamically adjust the LoRA scale
-            adjust_lora_scale_text_encoder(self.text_encoder, lora_scale, self.use_peft_backend)
-            adjust_lora_scale_text_encoder(self.text_encoder_2, lora_scale, self.use_peft_backend)
+            if not self.use_peft_backend:
+                adjust_lora_scale_text_encoder(self.text_encoder, lora_scale)
+                adjust_lora_scale_text_encoder(self.text_encoder_2, lora_scale)
+            else:
+                scale_lora_layers(self.text_encoder, lora_scale)
+                scale_lora_layers(self.text_encoder_2, lora_scale)
 
         prompt = [prompt] if isinstance(prompt, str) else prompt
 
@@ -464,6 +470,11 @@ def encode_prompt(
                 bs_embed * num_images_per_prompt, -1
             )
 
+        if isinstance(self, StableDiffusionXLLoraLoaderMixin) and self.use_peft_backend:
+            # Retrieve the original scale by scaling back the LoRA layers
+            unscale_lora_layers(self.text_encoder)
+            unscale_lora_layers(self.text_encoder_2)
+
         return prompt_embeds, negative_prompt_embeds, pooled_prompt_embeds, negative_pooled_prompt_embeds
 
     # Copied from diffusers.pipelines.stable_diffusion.pipeline_stable_diffusion.StableDiffusionPipeline.prepare_extra_step_kwargs

src/diffusers/pipelines/stable_diffusion/pipeline_cycle_diffusion.py

@@ -27,7 +27,7 @@
 from ...models import AutoencoderKL, UNet2DConditionModel
 from ...models.lora import adjust_lora_scale_text_encoder
 from ...schedulers import DDIMScheduler
-from ...utils import PIL_INTERPOLATION, deprecate, logging
+from ...utils import PIL_INTERPOLATION, deprecate, logging, scale_lora_layers, unscale_lora_layers
 from ...utils.torch_utils import randn_tensor
 from ..pipeline_utils import DiffusionPipeline
 from .pipeline_output import StableDiffusionPipelineOutput
@@ -308,7 +308,10 @@ def encode_prompt(
             self._lora_scale = lora_scale
 
             # dynamically adjust the LoRA scale
-            adjust_lora_scale_text_encoder(self.text_encoder, lora_scale, self.use_peft_backend)
+            if not self.use_peft_backend:
+                adjust_lora_scale_text_encoder(self.text_encoder, lora_scale)
+            else:
+                scale_lora_layers(self.text_encoder, lora_scale)
 
         if prompt is not None and isinstance(prompt, str):
             batch_size = 1
@@ -433,6 +436,10 @@ def encode_prompt(
             negative_prompt_embeds = negative_prompt_embeds.repeat(1, num_images_per_prompt, 1)
             negative_prompt_embeds = negative_prompt_embeds.view(batch_size * num_images_per_prompt, seq_len, -1)
 
+        if isinstance(self, LoraLoaderMixin) and self.use_peft_backend:
+            # Retrieve the original scale by scaling back the LoRA layers
+            unscale_lora_layers(self.text_encoder)
+
         return prompt_embeds, negative_prompt_embeds
 
     # Copied from diffusers.pipelines.stable_diffusion.pipeline_stable_diffusion_img2img.StableDiffusionImg2ImgPipeline.check_inputs

src/diffusers/pipelines/stable_diffusion/pipeline_stable_diffusion.py

@@ -25,11 +25,7 @@
 from ...models import AutoencoderKL, UNet2DConditionModel
 from ...models.lora import adjust_lora_scale_text_encoder
 from ...schedulers import KarrasDiffusionSchedulers
-from ...utils import (
-    deprecate,
-    logging,
-    replace_example_docstring,
-)
+from ...utils import deprecate, logging, replace_example_docstring, scale_lora_layers, unscale_lora_layers
 from ...utils.torch_utils import randn_tensor
 from ..pipeline_utils import DiffusionPipeline
 from .pipeline_output import StableDiffusionPipelineOutput
@@ -301,7 +297,10 @@ def encode_prompt(
             self._lora_scale = lora_scale
 
             # dynamically adjust the LoRA scale
-            adjust_lora_scale_text_encoder(self.text_encoder, lora_scale, self.use_peft_backend)
+            if not self.use_peft_backend:
+                adjust_lora_scale_text_encoder(self.text_encoder, lora_scale)
+            else:
+                scale_lora_layers(self.text_encoder, lora_scale)
 
         if prompt is not None and isinstance(prompt, str):
             batch_size = 1
@@ -426,6 +425,10 @@ def encode_prompt(
             negative_prompt_embeds = negative_prompt_embeds.repeat(1, num_images_per_prompt, 1)
             negative_prompt_embeds = negative_prompt_embeds.view(batch_size * num_images_per_prompt, seq_len, -1)
 
+        if isinstance(self, LoraLoaderMixin) and self.use_peft_backend:
+            # Retrieve the original scale by scaling back the LoRA layers
+            unscale_lora_layers(self.text_encoder)
+
         return prompt_embeds, negative_prompt_embeds
 
     def run_safety_checker(self, image, device, dtype):