From 5c3d6a60828e7791bfe9e04c6ce2e4837970dd1a Mon Sep 17 00:00:00 2001
From: Kent Keirsey <kentk@hey.com>
Date: Tue, 14 Oct 2025 11:01:41 -0400
Subject: [PATCH 01/10] fix to make zero set to null

---
 .../_experimental/sd_dpo_lora/config.py       |  5 ++--
 .../pipelines/flux/lora/config.py             |  6 ++--
 .../pipelines/stable_diffusion/lora/config.py |  5 ++--
 .../textual_inversion/config.py               |  2 +-
 .../stable_diffusion_xl/finetune/config.py    |  2 +-
 .../stable_diffusion_xl/lora/config.py        |  5 ++--
 .../lora_and_textual_inversion/config.py      |  8 ++---
 .../config_groups/flux_lora_config_group.py   | 13 ++++----
 .../ui/config_groups/sd_lora_config_group.py  | 15 ++++++----
 .../sd_textual_inversion_config_group.py      |  5 ++--
 .../sdxl_finetune_config_group.py             |  5 ++--
 ...lora_and_textual_inversion_config_group.py | 30 ++++++++++++++-----
 .../config_groups/sdxl_lora_config_group.py   | 15 ++++++----
 .../sdxl_textual_inversion_config_group.py    |  5 ++--
 14 files changed, 75 insertions(+), 46 deletions(-)

diff --git a/src/invoke_training/pipelines/_experimental/sd_dpo_lora/config.py b/src/invoke_training/pipelines/_experimental/sd_dpo_lora/config.py
index f6ad39a4..988a8b8a 100644
--- a/src/invoke_training/pipelines/_experimental/sd_dpo_lora/config.py
+++ b/src/invoke_training/pipelines/_experimental/sd_dpo_lora/config.py
@@ -95,11 +95,12 @@ class SdDirectPreferenceOptimizationLoraConfig(BasePipelineConfig):
 
     text_encoder_learning_rate: float | None = None
     """The learning rate to use for the text encoder model. If set, this overrides the optimizer's default learning
-    rate.
+    rate. Set to null or 0 to use the optimizer's default learning rate.
     """
 
     unet_learning_rate: float | None = None
     """The learning rate to use for the UNet model. If set, this overrides the optimizer's default learning rate.
+    Set to null or 0 to use the optimizer's default learning rate.
     """
 
     lr_scheduler: Literal[
@@ -194,7 +195,7 @@ class SdDirectPreferenceOptimizationLoraConfig(BasePipelineConfig):
     """
 
     max_grad_norm: float | None = None
-    """Max gradient norm for clipping. Set to None for no clipping.
+    """Max gradient norm for clipping. Set to null or 0 for no clipping.
     """
 
     validation_prompts: list[str] = []
diff --git a/src/invoke_training/pipelines/flux/lora/config.py b/src/invoke_training/pipelines/flux/lora/config.py
index e631fb71..eaa67405 100644
--- a/src/invoke_training/pipelines/flux/lora/config.py
+++ b/src/invoke_training/pipelines/flux/lora/config.py
@@ -52,12 +52,12 @@ class FluxLoraConfig(BasePipelineConfig):
 
     text_encoder_learning_rate: float | None = 1e-4
     """The learning rate to use for the text encoder model. If set, this overrides the optimizer's default learning
-    rate.
+    rate. Set to null or 0 to use the optimizer's default learning rate.
     """
 
     transformer_learning_rate: float | None = 1e-4
     """The learning rate to use for the transformer model. If set, this overrides the optimizer's default learning
-    rate.
+    rate. Set to null or 0 to use the optimizer's default learning rate.
     """
 
     lr_scheduler: Literal[
@@ -176,7 +176,7 @@ class FluxLoraConfig(BasePipelineConfig):
     """
 
     max_grad_norm: float | None = None
-    """Max gradient norm for clipping. Set to None for no clipping.
+    """Max gradient norm for clipping. Set to null or 0 for no clipping.
     """
 
     validation_prompts: list[str] = []
diff --git a/src/invoke_training/pipelines/stable_diffusion/lora/config.py b/src/invoke_training/pipelines/stable_diffusion/lora/config.py
index 2a472506..0e9c08ce 100644
--- a/src/invoke_training/pipelines/stable_diffusion/lora/config.py
+++ b/src/invoke_training/pipelines/stable_diffusion/lora/config.py
@@ -59,11 +59,12 @@ class SdLoraConfig(BasePipelineConfig):
 
     text_encoder_learning_rate: float | None = None
     """The learning rate to use for the text encoder model. If set, this overrides the optimizer's default learning
-    rate.
+    rate. Set to null or 0 to use the optimizer's default learning rate.
     """
 
     unet_learning_rate: float | None = None
     """The learning rate to use for the UNet model. If set, this overrides the optimizer's default learning rate.
+    Set to null or 0 to use the optimizer's default learning rate.
     """
 
     lr_scheduler: Literal[
@@ -188,7 +189,7 @@ class SdLoraConfig(BasePipelineConfig):
     """
 
     max_grad_norm: float | None = None
-    """Max gradient norm for clipping. Set to None for no clipping.
+    """Max gradient norm for clipping. Set to null or 0 for no clipping.
     """
 
     validation_prompts: list[str] = []
diff --git a/src/invoke_training/pipelines/stable_diffusion/textual_inversion/config.py b/src/invoke_training/pipelines/stable_diffusion/textual_inversion/config.py
index 4b763b84..69295d5a 100644
--- a/src/invoke_training/pipelines/stable_diffusion/textual_inversion/config.py
+++ b/src/invoke_training/pipelines/stable_diffusion/textual_inversion/config.py
@@ -160,7 +160,7 @@ class SdTextualInversionConfig(BasePipelineConfig):
     """
 
     max_grad_norm: float | None = None
-    """Maximum gradient norm for gradient clipping. Set to `None` for no clipping.
+    """Maximum gradient norm for gradient clipping. Set to `null` or 0 for no clipping.
     """
 
     validation_prompts: list[str] = []
diff --git a/src/invoke_training/pipelines/stable_diffusion_xl/finetune/config.py b/src/invoke_training/pipelines/stable_diffusion_xl/finetune/config.py
index 08dbfce8..6230ca82 100644
--- a/src/invoke_training/pipelines/stable_diffusion_xl/finetune/config.py
+++ b/src/invoke_training/pipelines/stable_diffusion_xl/finetune/config.py
@@ -125,7 +125,7 @@ class SdxlFinetuneConfig(BasePipelineConfig):
     """
 
     max_grad_norm: float | None = None
-    """Max gradient norm for clipping. Set to None for no clipping.
+    """Max gradient norm for clipping. Set to null or 0 for no clipping.
     """
 
     validation_prompts: list[str] = []
diff --git a/src/invoke_training/pipelines/stable_diffusion_xl/lora/config.py b/src/invoke_training/pipelines/stable_diffusion_xl/lora/config.py
index 125db57a..390e8f90 100644
--- a/src/invoke_training/pipelines/stable_diffusion_xl/lora/config.py
+++ b/src/invoke_training/pipelines/stable_diffusion_xl/lora/config.py
@@ -59,11 +59,12 @@ class SdxlLoraConfig(BasePipelineConfig):
 
     text_encoder_learning_rate: float | None = None
     """The learning rate to use for the text encoder model. If set, this overrides the optimizer's default learning
-    rate.
+    rate. Set to null or 0 to use the optimizer's default learning rate.
     """
 
     unet_learning_rate: float | None = None
     """The learning rate to use for the UNet model. If set, this overrides the optimizer's default learning rate.
+    Set to null or 0 to use the optimizer's default learning rate.
     """
 
     lr_scheduler: Literal[
@@ -188,7 +189,7 @@ class SdxlLoraConfig(BasePipelineConfig):
     """
 
     max_grad_norm: float | None = None
-    """Max gradient norm for clipping. Set to None for no clipping.
+    """Max gradient norm for clipping. Set to null or 0 for no clipping.
     """
 
     validation_prompts: list[str] = []
diff --git a/src/invoke_training/pipelines/stable_diffusion_xl/lora_and_textual_inversion/config.py b/src/invoke_training/pipelines/stable_diffusion_xl/lora_and_textual_inversion/config.py
index d348e493..b72fd5e2 100644
--- a/src/invoke_training/pipelines/stable_diffusion_xl/lora_and_textual_inversion/config.py
+++ b/src/invoke_training/pipelines/stable_diffusion_xl/lora_and_textual_inversion/config.py
@@ -85,15 +85,15 @@ class SdxlLoraAndTextualInversionConfig(BasePipelineConfig):
     optimizer: AdamOptimizerConfig | ProdigyOptimizerConfig = AdamOptimizerConfig()
 
     text_encoder_learning_rate: float = 1e-5
-    """The learning rate to use for the text encoder model.
+    """The learning rate to use for the text encoder model. Set to 0 to use the optimizer's default learning rate.
     """
 
     unet_learning_rate: float = 1e-4
-    """The learning rate to use for the UNet model.
+    """The learning rate to use for the UNet model. Set to 0 to use the optimizer's default learning rate.
     """
 
     textual_inversion_learning_rate: float = 1e-3
-    """The learning rate to use for textual inversion training of the embeddings.
+    """The learning rate to use for textual inversion training of the embeddings. Set to 0 to use the optimizer's default learning rate.
     """
 
     lr_scheduler: Literal[
@@ -187,7 +187,7 @@ class SdxlLoraAndTextualInversionConfig(BasePipelineConfig):
     """
 
     max_grad_norm: float | None = None
-    """Max gradient norm for clipping. Set to None for no clipping.
+    """Max gradient norm for clipping. Set to null or 0 for no clipping.
     """
 
     validation_prompts: list[str] = []
diff --git a/src/invoke_training/ui/config_groups/flux_lora_config_group.py b/src/invoke_training/ui/config_groups/flux_lora_config_group.py
index 69b6c93f..2648e446 100644
--- a/src/invoke_training/ui/config_groups/flux_lora_config_group.py
+++ b/src/invoke_training/ui/config_groups/flux_lora_config_group.py
@@ -67,7 +67,7 @@ def __init__(self):
             with gr.Row():
                 self.transformer_learning_rate = gr.Number(
                     label="Transformer Learning Rate",
-                    info="The transformer learning rate. If None, then it is inherited from the base optimizer "
+                    info="The transformer learning rate. Set to 0 or leave empty to inherit from the base optimizer "
                     "learning rate.",
                     interactive=True,
                 )
@@ -103,7 +103,7 @@ def __init__(self):
                 )
                 self.max_grad_norm = gr.Number(
                     label="Max Gradient Norm",
-                    info="Max gradient norm for clipping. Set to None for no clipping.",
+                    info="Max gradient norm for clipping. Set to 0 or leave empty for no clipping (null).",
                     interactive=True,
                 )
                 self.train_batch_size = gr.Number(
@@ -314,12 +314,14 @@ def safe_pop(component, default=None):
             new_config.model = safe_pop(self.model, new_config.model)
             new_config.train_transformer = safe_pop(self.train_transformer, new_config.train_transformer)
             new_config.train_text_encoder = safe_pop(self.train_text_encoder, new_config.train_text_encoder)
-            new_config.transformer_learning_rate = safe_pop(
+            transformer_lr_value = safe_pop(
                 self.transformer_learning_rate, new_config.transformer_learning_rate
             )
-            new_config.text_encoder_learning_rate = safe_pop(
+            new_config.transformer_learning_rate = None if transformer_lr_value == 0 else transformer_lr_value
+            text_encoder_lr_value = safe_pop(
                 self.text_encoder_learning_rate, new_config.text_encoder_learning_rate
             )
+            new_config.text_encoder_learning_rate = None if text_encoder_lr_value == 0 else text_encoder_lr_value
             new_config.gradient_accumulation_steps = safe_pop(
                 self.gradient_accumulation_steps, new_config.gradient_accumulation_steps
             )
@@ -330,7 +332,8 @@ def safe_pop(component, default=None):
 
             new_config.lora_rank_dim = safe_pop(self.lora_rank_dim, new_config.lora_rank_dim)
             new_config.min_snr_gamma = safe_pop(self.min_snr_gamma, new_config.min_snr_gamma)
-            new_config.max_grad_norm = safe_pop(self.max_grad_norm, new_config.max_grad_norm)
+            max_grad_norm_value = safe_pop(self.max_grad_norm, new_config.max_grad_norm)
+            new_config.max_grad_norm = None if max_grad_norm_value == 0 else max_grad_norm_value
             new_config.train_batch_size = safe_pop(self.train_batch_size, new_config.train_batch_size)
             new_config.weight_dtype = safe_pop(self.weight_dtype, new_config.weight_dtype)
             new_config.mixed_precision = safe_pop(self.mixed_precision, new_config.mixed_precision)
diff --git a/src/invoke_training/ui/config_groups/sd_lora_config_group.py b/src/invoke_training/ui/config_groups/sd_lora_config_group.py
index e77a4048..62364ac5 100644
--- a/src/invoke_training/ui/config_groups/sd_lora_config_group.py
+++ b/src/invoke_training/ui/config_groups/sd_lora_config_group.py
@@ -109,12 +109,12 @@ def __init__(self):
             with gr.Row():
                 self.unet_learning_rate = gr.Number(
                     label="UNet Learning Rate",
-                    info="The UNet learning rate. If None, then it is inherited from the base optimizer learning rate.",
+                    info="The UNet learning rate. Set to 0 or leave empty to inherit from the base optimizer learning rate.",
                     interactive=True,
                 )
                 self.text_encoder_learning_rate = gr.Number(
                     label="Text Encoder Learning Rate",
-                    info="The text encoder learning rate. If None, then it is inherited from the base optimizer "
+                    info="The text encoder learning rate. Set to 0 or leave empty to inherit from the base optimizer "
                     "learning rate.",
                     interactive=True,
                 )
@@ -153,7 +153,7 @@ def __init__(self):
                 )
                 self.max_grad_norm = gr.Number(
                     label="Max Gradient Norm",
-                    info="Max gradient norm for clipping. Set to None for no clipping.",
+                    info="Max gradient norm for clipping. Set to 0 or leave empty for no clipping (null).",
                     interactive=True,
                 )
                 self.train_batch_size = gr.Number(
@@ -223,13 +223,16 @@ def update_config_with_ui_component_data(
         new_config.hf_variant = ui_data.pop(self.hf_variant) or None
         new_config.max_checkpoints = ui_data.pop(self.max_checkpoints)
         new_config.train_unet = ui_data.pop(self.train_unet)
-        new_config.unet_learning_rate = ui_data.pop(self.unet_learning_rate)
+        unet_lr_value = ui_data.pop(self.unet_learning_rate)
+        new_config.unet_learning_rate = None if unet_lr_value == 0 else unet_lr_value
         new_config.train_text_encoder = ui_data.pop(self.train_text_encoder)
-        new_config.text_encoder_learning_rate = ui_data.pop(self.text_encoder_learning_rate)
+        text_encoder_lr_value = ui_data.pop(self.text_encoder_learning_rate)
+        new_config.text_encoder_learning_rate = None if text_encoder_lr_value == 0 else text_encoder_lr_value
         new_config.lr_scheduler = ui_data.pop(self.lr_scheduler)
         new_config.lr_warmup_steps = ui_data.pop(self.lr_warmup_steps)
         new_config.use_masks = ui_data.pop(self.use_masks)
-        new_config.max_grad_norm = ui_data.pop(self.max_grad_norm)
+        max_grad_norm_value = ui_data.pop(self.max_grad_norm)
+        new_config.max_grad_norm = None if max_grad_norm_value == 0 else max_grad_norm_value
         new_config.train_batch_size = ui_data.pop(self.train_batch_size)
         new_config.cache_text_encoder_outputs = ui_data.pop(self.cache_text_encoder_outputs)
         new_config.cache_vae_outputs = ui_data.pop(self.cache_vae_outputs)
diff --git a/src/invoke_training/ui/config_groups/sd_textual_inversion_config_group.py b/src/invoke_training/ui/config_groups/sd_textual_inversion_config_group.py
index 55fa9dd8..484159d6 100644
--- a/src/invoke_training/ui/config_groups/sd_textual_inversion_config_group.py
+++ b/src/invoke_training/ui/config_groups/sd_textual_inversion_config_group.py
@@ -154,7 +154,7 @@ def __init__(self):
                 )
                 self.max_grad_norm = gr.Number(
                     label="Max Gradient Norm",
-                    info="Max gradient norm for clipping. Set to None for no clipping.",
+                    info="Max gradient norm for clipping. Set to 0 or leave empty for no clipping (null).",
                     interactive=True,
                 )
                 self.train_batch_size = gr.Number(
@@ -230,7 +230,8 @@ def update_config_with_ui_component_data(
         new_config.lr_scheduler = ui_data.pop(self.lr_scheduler)
         new_config.lr_warmup_steps = ui_data.pop(self.lr_warmup_steps)
         new_config.use_masks = ui_data.pop(self.use_masks)
-        new_config.max_grad_norm = ui_data.pop(self.max_grad_norm)
+        max_grad_norm_value = ui_data.pop(self.max_grad_norm)
+        new_config.max_grad_norm = None if max_grad_norm_value == 0 else max_grad_norm_value
         new_config.train_batch_size = ui_data.pop(self.train_batch_size)
         new_config.cache_vae_outputs = ui_data.pop(self.cache_vae_outputs)
         new_config.enable_cpu_offload_during_validation = ui_data.pop(self.enable_cpu_offload_during_validation)
diff --git a/src/invoke_training/ui/config_groups/sdxl_finetune_config_group.py b/src/invoke_training/ui/config_groups/sdxl_finetune_config_group.py
index 363c318e..572151c2 100644
--- a/src/invoke_training/ui/config_groups/sdxl_finetune_config_group.py
+++ b/src/invoke_training/ui/config_groups/sdxl_finetune_config_group.py
@@ -151,7 +151,7 @@ def __init__(self):
                 )
                 self.max_grad_norm = gr.Number(
                     label="Max Gradient Norm",
-                    info="Max gradient norm for clipping. Set to None for no clipping.",
+                    info="Max gradient norm for clipping. Set to 0 or leave empty for no clipping (null).",
                     interactive=True,
                 )
                 self.train_batch_size = gr.Number(
@@ -227,7 +227,8 @@ def update_config_with_ui_component_data(
         new_config.lr_warmup_steps = ui_data.pop(self.lr_warmup_steps)
         new_config.use_masks = ui_data.pop(self.use_masks)
         new_config.min_snr_gamma = ui_data.pop(self.min_snr_gamma)
-        new_config.max_grad_norm = ui_data.pop(self.max_grad_norm)
+        max_grad_norm_value = ui_data.pop(self.max_grad_norm)
+        new_config.max_grad_norm = None if max_grad_norm_value == 0 else max_grad_norm_value
         new_config.train_batch_size = ui_data.pop(self.train_batch_size)
         new_config.cache_text_encoder_outputs = ui_data.pop(self.cache_text_encoder_outputs)
         new_config.cache_vae_outputs = ui_data.pop(self.cache_vae_outputs)
diff --git a/src/invoke_training/ui/config_groups/sdxl_lora_and_textual_inversion_config_group.py b/src/invoke_training/ui/config_groups/sdxl_lora_and_textual_inversion_config_group.py
index 657c8ebb..2edaea7c 100644
--- a/src/invoke_training/ui/config_groups/sdxl_lora_and_textual_inversion_config_group.py
+++ b/src/invoke_training/ui/config_groups/sdxl_lora_and_textual_inversion_config_group.py
@@ -145,10 +145,20 @@ def __init__(self):
                 self.train_text_encoder = gr.Checkbox(label="Train Text Encoder", interactive=True)
                 self.train_ti = gr.Checkbox(label="Train Textual Inversion Token", scale=2, interactive=True)
             with gr.Row():
-                self.unet_learning_rate = gr.Number(label="UNet Learning Rate", interactive=True)
-                self.text_encoder_learning_rate = gr.Number(label="Text Encoder Learning Rate", interactive=True)
+                self.unet_learning_rate = gr.Number(
+                    label="UNet Learning Rate",
+                    info="The UNet learning rate. Set to 0 or leave empty to inherit from the base optimizer learning rate.",
+                    interactive=True,
+                )
+                self.text_encoder_learning_rate = gr.Number(
+                    label="Text Encoder Learning Rate",
+                    info="The text encoder learning rate. Set to 0 or leave empty to inherit from the base optimizer learning rate.",
+                    interactive=True,
+                )
                 self.textual_inversion_learning_rate = gr.Number(
-                    label="Textual Inversion Learning Rate", interactive=True
+                    label="Textual Inversion Learning Rate",
+                    info="The textual inversion learning rate. Set to 0 or leave empty to inherit from the base optimizer learning rate.",
+                    interactive=True,
                 )
                 self.ti_train_steps_ratio = gr.Number(label="Textual Inversion Train Steps Ratio", interactive=True)
             with gr.Row():
@@ -186,7 +196,7 @@ def __init__(self):
                 )
                 self.max_grad_norm = gr.Number(
                     label="Max Gradient Norm",
-                    info="Max gradient norm for clipping. Set to None for no clipping.",
+                    info="Max gradient norm for clipping. Set to 0 or leave empty for no clipping (null).",
                     interactive=True,
                 )
                 self.train_batch_size = gr.Number(
@@ -273,14 +283,18 @@ def update_config_with_ui_component_data(
         new_config.train_unet = ui_data.pop(self.train_unet)
         new_config.train_text_encoder = ui_data.pop(self.train_text_encoder)
         new_config.train_ti = ui_data.pop(self.train_ti)
-        new_config.unet_learning_rate = ui_data.pop(self.unet_learning_rate)
-        new_config.text_encoder_learning_rate = ui_data.pop(self.text_encoder_learning_rate)
-        new_config.textual_inversion_learning_rate = ui_data.pop(self.textual_inversion_learning_rate)
+        unet_lr_value = ui_data.pop(self.unet_learning_rate)
+        new_config.unet_learning_rate = None if unet_lr_value == 0 else unet_lr_value
+        text_encoder_lr_value = ui_data.pop(self.text_encoder_learning_rate)
+        new_config.text_encoder_learning_rate = None if text_encoder_lr_value == 0 else text_encoder_lr_value
+        ti_lr_value = ui_data.pop(self.textual_inversion_learning_rate)
+        new_config.textual_inversion_learning_rate = None if ti_lr_value == 0 else ti_lr_value
         new_config.ti_train_steps_ratio = ui_data.pop(self.ti_train_steps_ratio)
         new_config.lr_scheduler = ui_data.pop(self.lr_scheduler)
         new_config.lr_warmup_steps = ui_data.pop(self.lr_warmup_steps)
         new_config.use_masks = ui_data.pop(self.use_masks)
-        new_config.max_grad_norm = ui_data.pop(self.max_grad_norm)
+        max_grad_norm_value = ui_data.pop(self.max_grad_norm)
+        new_config.max_grad_norm = None if max_grad_norm_value == 0 else max_grad_norm_value
         new_config.train_batch_size = ui_data.pop(self.train_batch_size)
         new_config.cache_text_encoder_outputs = ui_data.pop(self.cache_text_encoder_outputs)
         new_config.cache_vae_outputs = ui_data.pop(self.cache_vae_outputs)
diff --git a/src/invoke_training/ui/config_groups/sdxl_lora_config_group.py b/src/invoke_training/ui/config_groups/sdxl_lora_config_group.py
index 70ad8bf2..bbee2693 100644
--- a/src/invoke_training/ui/config_groups/sdxl_lora_config_group.py
+++ b/src/invoke_training/ui/config_groups/sdxl_lora_config_group.py
@@ -115,12 +115,12 @@ def __init__(self):
             with gr.Row():
                 self.unet_learning_rate = gr.Number(
                     label="UNet Learning Rate",
-                    info="The UNet learning rate. If None, then it is inherited from the base optimizer learning rate.",
+                    info="The UNet learning rate. Set to 0 or leave empty to inherit from the base optimizer learning rate.",
                     interactive=True,
                 )
                 self.text_encoder_learning_rate = gr.Number(
                     label="Text Encoder Learning Rate",
-                    info="The text encoder learning rate. If None, then it is inherited from the base optimizer "
+                    info="The text encoder learning rate. Set to 0 or leave empty to inherit from the base optimizer "
                     "learning rate.",
                     interactive=True,
                 )
@@ -159,7 +159,7 @@ def __init__(self):
                 )
                 self.max_grad_norm = gr.Number(
                     label="Max Gradient Norm",
-                    info="Max gradient norm for clipping. Set to None for no clipping.",
+                    info="Max gradient norm for clipping. Set to 0 or leave empty for no clipping (null).",
                     interactive=True,
                 )
                 self.train_batch_size = gr.Number(
@@ -233,13 +233,16 @@ def update_config_with_ui_component_data(
         new_config.vae_model = ui_data.pop(self.vae_model) or None
         new_config.max_checkpoints = ui_data.pop(self.max_checkpoints)
         new_config.train_unet = ui_data.pop(self.train_unet)
-        new_config.unet_learning_rate = ui_data.pop(self.unet_learning_rate)
+        unet_lr_value = ui_data.pop(self.unet_learning_rate)
+        new_config.unet_learning_rate = None if unet_lr_value == 0 else unet_lr_value
         new_config.train_text_encoder = ui_data.pop(self.train_text_encoder)
-        new_config.text_encoder_learning_rate = ui_data.pop(self.text_encoder_learning_rate)
+        text_encoder_lr_value = ui_data.pop(self.text_encoder_learning_rate)
+        new_config.text_encoder_learning_rate = None if text_encoder_lr_value == 0 else text_encoder_lr_value
         new_config.lr_scheduler = ui_data.pop(self.lr_scheduler)
         new_config.lr_warmup_steps = ui_data.pop(self.lr_warmup_steps)
         new_config.use_masks = ui_data.pop(self.use_masks)
-        new_config.max_grad_norm = ui_data.pop(self.max_grad_norm)
+        max_grad_norm_value = ui_data.pop(self.max_grad_norm)
+        new_config.max_grad_norm = None if max_grad_norm_value == 0 else max_grad_norm_value
         new_config.train_batch_size = ui_data.pop(self.train_batch_size)
         new_config.cache_text_encoder_outputs = ui_data.pop(self.cache_text_encoder_outputs)
         new_config.cache_vae_outputs = ui_data.pop(self.cache_vae_outputs)
diff --git a/src/invoke_training/ui/config_groups/sdxl_textual_inversion_config_group.py b/src/invoke_training/ui/config_groups/sdxl_textual_inversion_config_group.py
index 14610610..dcc477b3 100644
--- a/src/invoke_training/ui/config_groups/sdxl_textual_inversion_config_group.py
+++ b/src/invoke_training/ui/config_groups/sdxl_textual_inversion_config_group.py
@@ -160,7 +160,7 @@ def __init__(self):
                 )
                 self.max_grad_norm = gr.Number(
                     label="Max Gradient Norm",
-                    info="Max gradient norm for clipping. Set to None for no clipping.",
+                    info="Max gradient norm for clipping. Set to 0 or leave empty for no clipping (null).",
                     interactive=True,
                 )
                 self.train_batch_size = gr.Number(
@@ -238,7 +238,8 @@ def update_config_with_ui_component_data(
         new_config.lr_scheduler = ui_data.pop(self.lr_scheduler)
         new_config.lr_warmup_steps = ui_data.pop(self.lr_warmup_steps)
         new_config.use_masks = ui_data.pop(self.use_masks)
-        new_config.max_grad_norm = ui_data.pop(self.max_grad_norm)
+        max_grad_norm_value = ui_data.pop(self.max_grad_norm)
+        new_config.max_grad_norm = None if max_grad_norm_value == 0 else max_grad_norm_value
         new_config.train_batch_size = ui_data.pop(self.train_batch_size)
         new_config.cache_vae_outputs = ui_data.pop(self.cache_vae_outputs)
         new_config.enable_cpu_offload_during_validation = ui_data.pop(self.enable_cpu_offload_during_validation)

From 1b757eb10b905822ed574384e0f4e9e2be41d419 Mon Sep 17 00:00:00 2001
From: Kent Keirsey <kentk@hey.com>
Date: Tue, 14 Oct 2025 13:28:50 -0400
Subject: [PATCH 02/10] update last config

---
 .../lora_and_textual_inversion/config.py             | 12 ++++++------
 1 file changed, 6 insertions(+), 6 deletions(-)

diff --git a/src/invoke_training/pipelines/stable_diffusion_xl/lora_and_textual_inversion/config.py b/src/invoke_training/pipelines/stable_diffusion_xl/lora_and_textual_inversion/config.py
index b72fd5e2..dd390841 100644
--- a/src/invoke_training/pipelines/stable_diffusion_xl/lora_and_textual_inversion/config.py
+++ b/src/invoke_training/pipelines/stable_diffusion_xl/lora_and_textual_inversion/config.py
@@ -84,16 +84,16 @@ class SdxlLoraAndTextualInversionConfig(BasePipelineConfig):
 
     optimizer: AdamOptimizerConfig | ProdigyOptimizerConfig = AdamOptimizerConfig()
 
-    text_encoder_learning_rate: float = 1e-5
-    """The learning rate to use for the text encoder model. Set to 0 to use the optimizer's default learning rate.
+    text_encoder_learning_rate: float | None = 1e-5
+    """The learning rate to use for the text encoder model. Set to null or 0 to use the optimizer's default learning rate.
     """
 
-    unet_learning_rate: float = 1e-4
-    """The learning rate to use for the UNet model. Set to 0 to use the optimizer's default learning rate.
+    unet_learning_rate: float | None = 1e-4
+    """The learning rate to use for the UNet model. Set to null or 0 to use the optimizer's default learning rate.
     """
 
-    textual_inversion_learning_rate: float = 1e-3
-    """The learning rate to use for textual inversion training of the embeddings. Set to 0 to use the optimizer's default learning rate.
+    textual_inversion_learning_rate: float | None = 1e-3
+    """The learning rate to use for textual inversion training of the embeddings. Set to null or 0 to use the optimizer's default learning rate.
     """
 
     lr_scheduler: Literal[

From aa5adf799a7e57e89fde4f89bb04154933138f0c Mon Sep 17 00:00:00 2001
From: Kent Keirsey <kentk@hey.com>
Date: Tue, 14 Oct 2025 13:34:24 -0400
Subject: [PATCH 03/10] fix lint

---
 pyproject.toml                                           | 2 +-
 .../lora_and_textual_inversion/config.py                 | 3 ++-
 .../ui/config_groups/flux_lora_config_group.py           | 8 ++------
 .../ui/config_groups/sd_lora_config_group.py             | 3 ++-
 .../sdxl_lora_and_textual_inversion_config_group.py      | 9 ++++++---
 .../ui/config_groups/sdxl_lora_config_group.py           | 3 ++-
 6 files changed, 15 insertions(+), 13 deletions(-)

diff --git a/pyproject.toml b/pyproject.toml
index 1de0410b..afbbe709 100644
--- a/pyproject.toml
+++ b/pyproject.toml
@@ -69,7 +69,7 @@ dependencies = [
 
 [tool.ruff]
 src = ["src"]
-select = ["E", "F", "W", "C9", "N8", "I"]
+lint.select = ["E", "F", "W", "C9", "N8", "I"]
 target-version = "py39"
 line-length = 120
 
diff --git a/src/invoke_training/pipelines/stable_diffusion_xl/lora_and_textual_inversion/config.py b/src/invoke_training/pipelines/stable_diffusion_xl/lora_and_textual_inversion/config.py
index dd390841..dcd70c92 100644
--- a/src/invoke_training/pipelines/stable_diffusion_xl/lora_and_textual_inversion/config.py
+++ b/src/invoke_training/pipelines/stable_diffusion_xl/lora_and_textual_inversion/config.py
@@ -93,7 +93,8 @@ class SdxlLoraAndTextualInversionConfig(BasePipelineConfig):
     """
 
     textual_inversion_learning_rate: float | None = 1e-3
-    """The learning rate to use for textual inversion training of the embeddings. Set to null or 0 to use the optimizer's default learning rate.
+    """The learning rate to use for textual inversion training of the embeddings. Set to null or 0 to use the
+    optimizer's default learning rate.
     """
 
     lr_scheduler: Literal[
diff --git a/src/invoke_training/ui/config_groups/flux_lora_config_group.py b/src/invoke_training/ui/config_groups/flux_lora_config_group.py
index 2648e446..10af605c 100644
--- a/src/invoke_training/ui/config_groups/flux_lora_config_group.py
+++ b/src/invoke_training/ui/config_groups/flux_lora_config_group.py
@@ -314,13 +314,9 @@ def safe_pop(component, default=None):
             new_config.model = safe_pop(self.model, new_config.model)
             new_config.train_transformer = safe_pop(self.train_transformer, new_config.train_transformer)
             new_config.train_text_encoder = safe_pop(self.train_text_encoder, new_config.train_text_encoder)
-            transformer_lr_value = safe_pop(
-                self.transformer_learning_rate, new_config.transformer_learning_rate
-            )
+            transformer_lr_value = safe_pop(self.transformer_learning_rate, new_config.transformer_learning_rate)
             new_config.transformer_learning_rate = None if transformer_lr_value == 0 else transformer_lr_value
-            text_encoder_lr_value = safe_pop(
-                self.text_encoder_learning_rate, new_config.text_encoder_learning_rate
-            )
+            text_encoder_lr_value = safe_pop(self.text_encoder_learning_rate, new_config.text_encoder_learning_rate)
             new_config.text_encoder_learning_rate = None if text_encoder_lr_value == 0 else text_encoder_lr_value
             new_config.gradient_accumulation_steps = safe_pop(
                 self.gradient_accumulation_steps, new_config.gradient_accumulation_steps
diff --git a/src/invoke_training/ui/config_groups/sd_lora_config_group.py b/src/invoke_training/ui/config_groups/sd_lora_config_group.py
index 62364ac5..e3ad87cd 100644
--- a/src/invoke_training/ui/config_groups/sd_lora_config_group.py
+++ b/src/invoke_training/ui/config_groups/sd_lora_config_group.py
@@ -109,7 +109,8 @@ def __init__(self):
             with gr.Row():
                 self.unet_learning_rate = gr.Number(
                     label="UNet Learning Rate",
-                    info="The UNet learning rate. Set to 0 or leave empty to inherit from the base optimizer learning rate.",
+                    info="The UNet learning rate. Set to 0 or leave empty to inherit from the base optimizer "
+                    "learning rate.",
                     interactive=True,
                 )
                 self.text_encoder_learning_rate = gr.Number(
diff --git a/src/invoke_training/ui/config_groups/sdxl_lora_and_textual_inversion_config_group.py b/src/invoke_training/ui/config_groups/sdxl_lora_and_textual_inversion_config_group.py
index 2edaea7c..f9b1dba0 100644
--- a/src/invoke_training/ui/config_groups/sdxl_lora_and_textual_inversion_config_group.py
+++ b/src/invoke_training/ui/config_groups/sdxl_lora_and_textual_inversion_config_group.py
@@ -147,17 +147,20 @@ def __init__(self):
             with gr.Row():
                 self.unet_learning_rate = gr.Number(
                     label="UNet Learning Rate",
-                    info="The UNet learning rate. Set to 0 or leave empty to inherit from the base optimizer learning rate.",
+                    info="The UNet learning rate. Set to 0 or leave empty to inherit from the base optimizer "
+                    "learning rate.",
                     interactive=True,
                 )
                 self.text_encoder_learning_rate = gr.Number(
                     label="Text Encoder Learning Rate",
-                    info="The text encoder learning rate. Set to 0 or leave empty to inherit from the base optimizer learning rate.",
+                    info="The text encoder learning rate. Set to 0 or leave empty to inherit from the base optimizer "
+                    "learning rate.",
                     interactive=True,
                 )
                 self.textual_inversion_learning_rate = gr.Number(
                     label="Textual Inversion Learning Rate",
-                    info="The textual inversion learning rate. Set to 0 or leave empty to inherit from the base optimizer learning rate.",
+                    info="The textual inversion learning rate. Set to 0 or leave empty to inherit from the base optimizer "
+                    "learning rate.",
                     interactive=True,
                 )
                 self.ti_train_steps_ratio = gr.Number(label="Textual Inversion Train Steps Ratio", interactive=True)
diff --git a/src/invoke_training/ui/config_groups/sdxl_lora_config_group.py b/src/invoke_training/ui/config_groups/sdxl_lora_config_group.py
index bbee2693..be111193 100644
--- a/src/invoke_training/ui/config_groups/sdxl_lora_config_group.py
+++ b/src/invoke_training/ui/config_groups/sdxl_lora_config_group.py
@@ -115,7 +115,8 @@ def __init__(self):
             with gr.Row():
                 self.unet_learning_rate = gr.Number(
                     label="UNet Learning Rate",
-                    info="The UNet learning rate. Set to 0 or leave empty to inherit from the base optimizer learning rate.",
+                    info="The UNet learning rate. Set to 0 or leave empty to inherit from the base optimizer "
+                    "learning rate.",
                     interactive=True,
                 )
                 self.text_encoder_learning_rate = gr.Number(

From 4de3682a44fc222ce43e84dd9ca1dfd095e5a5fc Mon Sep 17 00:00:00 2001
From: Kent Keirsey <kentk@hey.com>
Date: Tue, 14 Oct 2025 13:48:28 -0400
Subject: [PATCH 04/10] Fix Flux Config

---
 .../ui/config_groups/flux_lora_config_group.py                | 4 +---
 1 file changed, 1 insertion(+), 3 deletions(-)

diff --git a/src/invoke_training/ui/config_groups/flux_lora_config_group.py b/src/invoke_training/ui/config_groups/flux_lora_config_group.py
index 10af605c..b9b49819 100644
--- a/src/invoke_training/ui/config_groups/flux_lora_config_group.py
+++ b/src/invoke_training/ui/config_groups/flux_lora_config_group.py
@@ -313,11 +313,9 @@ def safe_pop(component, default=None):
             # Set basic properties
             new_config.model = safe_pop(self.model, new_config.model)
             new_config.train_transformer = safe_pop(self.train_transformer, new_config.train_transformer)
-            new_config.train_text_encoder = safe_pop(self.train_text_encoder, new_config.train_text_encoder)
+            # Note: train_text_encoder and text_encoder_learning_rate are not supported for Flux LoRA
             transformer_lr_value = safe_pop(self.transformer_learning_rate, new_config.transformer_learning_rate)
             new_config.transformer_learning_rate = None if transformer_lr_value == 0 else transformer_lr_value
-            text_encoder_lr_value = safe_pop(self.text_encoder_learning_rate, new_config.text_encoder_learning_rate)
-            new_config.text_encoder_learning_rate = None if text_encoder_lr_value == 0 else text_encoder_lr_value
             new_config.gradient_accumulation_steps = safe_pop(
                 self.gradient_accumulation_steps, new_config.gradient_accumulation_steps
             )

From e378224910d655f07dbd9ba4d4adb8f0ab71976d Mon Sep 17 00:00:00 2001
From: Kent Keirsey <kentk@hey.com>
Date: Tue, 14 Oct 2025 13:49:59 -0400
Subject: [PATCH 05/10] ruff

---
 .../stable_diffusion_xl/lora_and_textual_inversion/config.py  | 3 +--
 .../sdxl_lora_and_textual_inversion_config_group.py           | 4 ++--
 2 files changed, 3 insertions(+), 4 deletions(-)

diff --git a/src/invoke_training/pipelines/stable_diffusion_xl/lora_and_textual_inversion/config.py b/src/invoke_training/pipelines/stable_diffusion_xl/lora_and_textual_inversion/config.py
index dcd70c92..266dc057 100644
--- a/src/invoke_training/pipelines/stable_diffusion_xl/lora_and_textual_inversion/config.py
+++ b/src/invoke_training/pipelines/stable_diffusion_xl/lora_and_textual_inversion/config.py
@@ -85,8 +85,7 @@ class SdxlLoraAndTextualInversionConfig(BasePipelineConfig):
     optimizer: AdamOptimizerConfig | ProdigyOptimizerConfig = AdamOptimizerConfig()
 
     text_encoder_learning_rate: float | None = 1e-5
-    """The learning rate to use for the text encoder model. Set to null or 0 to use the optimizer's default learning rate.
-    """
+    """The learning rate to use for the text encoder model. Set to null or 0 to use the optimizer's default learning rate."""
 
     unet_learning_rate: float | None = 1e-4
     """The learning rate to use for the UNet model. Set to null or 0 to use the optimizer's default learning rate.
diff --git a/src/invoke_training/ui/config_groups/sdxl_lora_and_textual_inversion_config_group.py b/src/invoke_training/ui/config_groups/sdxl_lora_and_textual_inversion_config_group.py
index f9b1dba0..2bb041c0 100644
--- a/src/invoke_training/ui/config_groups/sdxl_lora_and_textual_inversion_config_group.py
+++ b/src/invoke_training/ui/config_groups/sdxl_lora_and_textual_inversion_config_group.py
@@ -159,8 +159,8 @@ def __init__(self):
                 )
                 self.textual_inversion_learning_rate = gr.Number(
                     label="Textual Inversion Learning Rate",
-                    info="The textual inversion learning rate. Set to 0 or leave empty to inherit from the base optimizer "
-                    "learning rate.",
+                    info="The textual inversion learning rate. Set to 0 or leave empty to inherit from the base "
+                    "optimizer learning rate.",
                     interactive=True,
                 )
                 self.ti_train_steps_ratio = gr.Number(label="Textual Inversion Train Steps Ratio", interactive=True)

From 6627e75ef8582d76b79fa8e30c5321603b111f30 Mon Sep 17 00:00:00 2001
From: Kent Keirsey <kentk@hey.com>
Date: Tue, 14 Oct 2025 13:56:58 -0400
Subject: [PATCH 06/10] fix ruff, again.

---
 .../stable_diffusion_xl/lora_and_textual_inversion/config.py   | 3 ++-
 1 file changed, 2 insertions(+), 1 deletion(-)

diff --git a/src/invoke_training/pipelines/stable_diffusion_xl/lora_and_textual_inversion/config.py b/src/invoke_training/pipelines/stable_diffusion_xl/lora_and_textual_inversion/config.py
index 266dc057..dcd70c92 100644
--- a/src/invoke_training/pipelines/stable_diffusion_xl/lora_and_textual_inversion/config.py
+++ b/src/invoke_training/pipelines/stable_diffusion_xl/lora_and_textual_inversion/config.py
@@ -85,7 +85,8 @@ class SdxlLoraAndTextualInversionConfig(BasePipelineConfig):
     optimizer: AdamOptimizerConfig | ProdigyOptimizerConfig = AdamOptimizerConfig()
 
     text_encoder_learning_rate: float | None = 1e-5
-    """The learning rate to use for the text encoder model. Set to null or 0 to use the optimizer's default learning rate."""
+    """The learning rate to use for the text encoder model. Set to null or 0 to use the optimizer's default learning rate.
+    """
 
     unet_learning_rate: float | None = 1e-4
     """The learning rate to use for the UNet model. Set to null or 0 to use the optimizer's default learning rate.

From f534cc89cd850422e7531e885d3aaba5697e9f71 Mon Sep 17 00:00:00 2001
From: Kent Keirsey <kentk@hey.com>
Date: Tue, 14 Oct 2025 14:13:39 -0400
Subject: [PATCH 07/10] now ruff?

---
 .../stable_diffusion/textual_inversion/train.py      | 12 +++++-------
 .../pipelines/stable_diffusion_xl/lora/train.py      |  6 +++---
 .../stable_diffusion_xl/textual_inversion/train.py   | 12 +++++-------
 src/invoke_training/ui/gradio_blocks/pipeline_tab.py | 12 +++++-------
 4 files changed, 18 insertions(+), 24 deletions(-)

diff --git a/src/invoke_training/pipelines/stable_diffusion/textual_inversion/train.py b/src/invoke_training/pipelines/stable_diffusion/textual_inversion/train.py
index 9400d281..cbc529f2 100644
--- a/src/invoke_training/pipelines/stable_diffusion/textual_inversion/train.py
+++ b/src/invoke_training/pipelines/stable_diffusion/textual_inversion/train.py
@@ -90,13 +90,11 @@ def _initialize_placeholder_tokens(
     - Initialize the new token embeddings from either an existing token, or an initial TI embedding file.
     """
     if (
-        sum(
-            [
-                config.initializer_token is not None,
-                config.initial_embedding_file is not None,
-                config.initial_phrase is not None,
-            ]
-        )
+        sum([
+            config.initializer_token is not None,
+            config.initial_embedding_file is not None,
+            config.initial_phrase is not None,
+        ])
         != 1
     ):
         raise ValueError(
diff --git a/src/invoke_training/pipelines/stable_diffusion_xl/lora/train.py b/src/invoke_training/pipelines/stable_diffusion_xl/lora/train.py
index 489e7a9e..543401a1 100644
--- a/src/invoke_training/pipelines/stable_diffusion_xl/lora/train.py
+++ b/src/invoke_training/pipelines/stable_diffusion_xl/lora/train.py
@@ -254,9 +254,9 @@ def compute_time_ids(original_size, crops_coords_top_left):
         add_time_ids = add_time_ids.to(accelerator.device, dtype=weight_dtype)
         return add_time_ids
 
-    add_time_ids = torch.cat(
-        [compute_time_ids(s, c) for s, c in zip(data_batch["original_size_hw"], data_batch["crop_top_left_yx"])]
-    )
+    add_time_ids = torch.cat([
+        compute_time_ids(s, c) for s, c in zip(data_batch["original_size_hw"], data_batch["crop_top_left_yx"])
+    ])
     unet_conditions = {"time_ids": add_time_ids}
 
     # Get the text embedding for conditioning.
diff --git a/src/invoke_training/pipelines/stable_diffusion_xl/textual_inversion/train.py b/src/invoke_training/pipelines/stable_diffusion_xl/textual_inversion/train.py
index 3ddb0515..1c88eef7 100644
--- a/src/invoke_training/pipelines/stable_diffusion_xl/textual_inversion/train.py
+++ b/src/invoke_training/pipelines/stable_diffusion_xl/textual_inversion/train.py
@@ -106,13 +106,11 @@ def _initialize_placeholder_tokens(
     """
 
     if (
-        sum(
-            [
-                getattr(config, "initializer_token", None) is not None,
-                getattr(config, "initial_embedding_file", None) is not None,
-                getattr(config, "initial_phrase", None) is not None,
-            ]
-        )
+        sum([
+            getattr(config, "initializer_token", None) is not None,
+            getattr(config, "initial_embedding_file", None) is not None,
+            getattr(config, "initial_phrase", None) is not None,
+        ])
         != 1
     ):
         raise ValueError(
diff --git a/src/invoke_training/ui/gradio_blocks/pipeline_tab.py b/src/invoke_training/ui/gradio_blocks/pipeline_tab.py
index 3c2f8611..b2d82f7a 100644
--- a/src/invoke_training/ui/gradio_blocks/pipeline_tab.py
+++ b/src/invoke_training/ui/gradio_blocks/pipeline_tab.py
@@ -140,13 +140,11 @@ def on_generate_config_button_click(self, data: dict):
             # (in case some values were rounded or otherwise modified
             # in the process).
             update_dict = self.pipeline_config_group.update_ui_components_with_config_data(self._current_config)
-            update_dict.update(
-                {
-                    self._config_yaml: yaml.safe_dump(
-                        self._current_config.model_dump(), default_flow_style=False, sort_keys=False
-                    )
-                }
-            )
+            update_dict.update({
+                self._config_yaml: yaml.safe_dump(
+                    self._current_config.model_dump(), default_flow_style=False, sort_keys=False
+                )
+            })
             return update_dict
         except Exception as e:
             print(f"Error generating config: {e}")

From cd59a12c5db9016b445f3367df2ad0e00927fcbc Mon Sep 17 00:00:00 2001
From: Kent Keirsey <kentk@hey.com>
Date: Tue, 14 Oct 2025 14:26:14 -0400
Subject: [PATCH 08/10] fix length

---
 .../stable_diffusion_xl/lora_and_textual_inversion/config.py   | 3 ++-
 1 file changed, 2 insertions(+), 1 deletion(-)

diff --git a/src/invoke_training/pipelines/stable_diffusion_xl/lora_and_textual_inversion/config.py b/src/invoke_training/pipelines/stable_diffusion_xl/lora_and_textual_inversion/config.py
index dcd70c92..13c34b6a 100644
--- a/src/invoke_training/pipelines/stable_diffusion_xl/lora_and_textual_inversion/config.py
+++ b/src/invoke_training/pipelines/stable_diffusion_xl/lora_and_textual_inversion/config.py
@@ -85,7 +85,8 @@ class SdxlLoraAndTextualInversionConfig(BasePipelineConfig):
     optimizer: AdamOptimizerConfig | ProdigyOptimizerConfig = AdamOptimizerConfig()
 
     text_encoder_learning_rate: float | None = 1e-5
-    """The learning rate to use for the text encoder model. Set to null or 0 to use the optimizer's default learning rate.
+    """The learning rate to use for the text encoder model. Set to null or 0 to use the optimizer's default learning 
+    rate.
     """
 
     unet_learning_rate: float | None = 1e-4

From 273052fd35c83a1924d3d7a268fbea3f6d03a8e4 Mon Sep 17 00:00:00 2001
From: Kent Keirsey <kentk@hey.com>
Date: Tue, 14 Oct 2025 14:40:58 -0400
Subject: [PATCH 09/10] final

---
 .../stable_diffusion_xl/lora_and_textual_inversion/config.py    | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/src/invoke_training/pipelines/stable_diffusion_xl/lora_and_textual_inversion/config.py b/src/invoke_training/pipelines/stable_diffusion_xl/lora_and_textual_inversion/config.py
index 13c34b6a..a2cc6876 100644
--- a/src/invoke_training/pipelines/stable_diffusion_xl/lora_and_textual_inversion/config.py
+++ b/src/invoke_training/pipelines/stable_diffusion_xl/lora_and_textual_inversion/config.py
@@ -85,7 +85,7 @@ class SdxlLoraAndTextualInversionConfig(BasePipelineConfig):
     optimizer: AdamOptimizerConfig | ProdigyOptimizerConfig = AdamOptimizerConfig()
 
     text_encoder_learning_rate: float | None = 1e-5
-    """The learning rate to use for the text encoder model. Set to null or 0 to use the optimizer's default learning 
+    """The learning rate to use for the text encoder model. Set to null or 0 to use the optimizer's default learning
     rate.
     """
 

From e685da2b2265104170a3cbb2b1e35d8626a1e672 Mon Sep 17 00:00:00 2001
From: Kent Keirsey <kentk@hey.com>
Date: Tue, 14 Oct 2025 16:51:30 -0400
Subject: [PATCH 10/10] format updates

---
 .../stable_diffusion/textual_inversion/train.py      | 12 +++++++-----
 .../pipelines/stable_diffusion_xl/lora/train.py      |  6 +++---
 .../stable_diffusion_xl/textual_inversion/train.py   | 12 +++++++-----
 src/invoke_training/ui/gradio_blocks/pipeline_tab.py | 12 +++++++-----
 4 files changed, 24 insertions(+), 18 deletions(-)

diff --git a/src/invoke_training/pipelines/stable_diffusion/textual_inversion/train.py b/src/invoke_training/pipelines/stable_diffusion/textual_inversion/train.py
index cbc529f2..9400d281 100644
--- a/src/invoke_training/pipelines/stable_diffusion/textual_inversion/train.py
+++ b/src/invoke_training/pipelines/stable_diffusion/textual_inversion/train.py
@@ -90,11 +90,13 @@ def _initialize_placeholder_tokens(
     - Initialize the new token embeddings from either an existing token, or an initial TI embedding file.
     """
     if (
-        sum([
-            config.initializer_token is not None,
-            config.initial_embedding_file is not None,
-            config.initial_phrase is not None,
-        ])
+        sum(
+            [
+                config.initializer_token is not None,
+                config.initial_embedding_file is not None,
+                config.initial_phrase is not None,
+            ]
+        )
         != 1
     ):
         raise ValueError(
diff --git a/src/invoke_training/pipelines/stable_diffusion_xl/lora/train.py b/src/invoke_training/pipelines/stable_diffusion_xl/lora/train.py
index 543401a1..489e7a9e 100644
--- a/src/invoke_training/pipelines/stable_diffusion_xl/lora/train.py
+++ b/src/invoke_training/pipelines/stable_diffusion_xl/lora/train.py
@@ -254,9 +254,9 @@ def compute_time_ids(original_size, crops_coords_top_left):
         add_time_ids = add_time_ids.to(accelerator.device, dtype=weight_dtype)
         return add_time_ids
 
-    add_time_ids = torch.cat([
-        compute_time_ids(s, c) for s, c in zip(data_batch["original_size_hw"], data_batch["crop_top_left_yx"])
-    ])
+    add_time_ids = torch.cat(
+        [compute_time_ids(s, c) for s, c in zip(data_batch["original_size_hw"], data_batch["crop_top_left_yx"])]
+    )
     unet_conditions = {"time_ids": add_time_ids}
 
     # Get the text embedding for conditioning.
diff --git a/src/invoke_training/pipelines/stable_diffusion_xl/textual_inversion/train.py b/src/invoke_training/pipelines/stable_diffusion_xl/textual_inversion/train.py
index 1c88eef7..3ddb0515 100644
--- a/src/invoke_training/pipelines/stable_diffusion_xl/textual_inversion/train.py
+++ b/src/invoke_training/pipelines/stable_diffusion_xl/textual_inversion/train.py
@@ -106,11 +106,13 @@ def _initialize_placeholder_tokens(
     """
 
     if (
-        sum([
-            getattr(config, "initializer_token", None) is not None,
-            getattr(config, "initial_embedding_file", None) is not None,
-            getattr(config, "initial_phrase", None) is not None,
-        ])
+        sum(
+            [
+                getattr(config, "initializer_token", None) is not None,
+                getattr(config, "initial_embedding_file", None) is not None,
+                getattr(config, "initial_phrase", None) is not None,
+            ]
+        )
         != 1
     ):
         raise ValueError(
diff --git a/src/invoke_training/ui/gradio_blocks/pipeline_tab.py b/src/invoke_training/ui/gradio_blocks/pipeline_tab.py
index b2d82f7a..3c2f8611 100644
--- a/src/invoke_training/ui/gradio_blocks/pipeline_tab.py
+++ b/src/invoke_training/ui/gradio_blocks/pipeline_tab.py
@@ -140,11 +140,13 @@ def on_generate_config_button_click(self, data: dict):
             # (in case some values were rounded or otherwise modified
             # in the process).
             update_dict = self.pipeline_config_group.update_ui_components_with_config_data(self._current_config)
-            update_dict.update({
-                self._config_yaml: yaml.safe_dump(
-                    self._current_config.model_dump(), default_flow_style=False, sort_keys=False
-                )
-            })
+            update_dict.update(
+                {
+                    self._config_yaml: yaml.safe_dump(
+                        self._current_config.model_dump(), default_flow_style=False, sort_keys=False
+                    )
+                }
+            )
             return update_dict
         except Exception as e:
             print(f"Error generating config: {e}")