From b880a31039afe98cdcfe3df5a44b6beccfb07aa5 Mon Sep 17 00:00:00 2001
From: psychedelicious <4822129+psychedelicious@users.noreply.github.com>
Date: Fri, 1 Mar 2024 13:03:32 +1100
Subject: [PATCH] refactor(mm): remove `ztsnr_training` field on `_MainConfig`

This is used to determine the CFG Rescale Multiplier setting. We'll handle this in the UI as a default setting.
---
 invokeai/app/api/routers/model_manager.py                 | 1 -
 invokeai/app/services/model_install/model_install_base.py | 2 +-
 invokeai/backend/model_manager/config.py                  | 1 -
 3 files changed, 1 insertion(+), 3 deletions(-)

diff --git a/invokeai/app/api/routers/model_manager.py b/invokeai/app/api/routers/model_manager.py
index 58950d6692..8712ba232d 100644
--- a/invokeai/app/api/routers/model_manager.py
+++ b/invokeai/app/api/routers/model_manager.py
@@ -79,7 +79,6 @@ example_model_config = {
     "prediction_type": "epsilon",
     "repo_variant": "fp16",
     "upcast_attention": False,
-    "ztsnr_training": False,
 }
 
 example_model_input = {
diff --git a/invokeai/app/services/model_install/model_install_base.py b/invokeai/app/services/model_install/model_install_base.py
index 4f2cdaed8e..0dd963a988 100644
--- a/invokeai/app/services/model_install/model_install_base.py
+++ b/invokeai/app/services/model_install/model_install_base.py
@@ -392,7 +392,7 @@ class ModelInstallServiceBase(ABC):
          will override corresponding autoassigned probe fields in the
          model's config record. Use it to override
          `name`, `description`, `base_type`, `model_type`, `format`,
-         `prediction_type`, `image_size`, and/or `ztsnr_training`.
+         `prediction_type`, and/or `image_size`.
 
         This will download the model located at `source`,
         probe it, and install it into the models directory.
diff --git a/invokeai/backend/model_manager/config.py b/invokeai/backend/model_manager/config.py
index 5aa07f44ee..2b2ceed42b 100644
--- a/invokeai/backend/model_manager/config.py
+++ b/invokeai/backend/model_manager/config.py
@@ -263,7 +263,6 @@ class _MainConfig(ModelConfigBase):
     variant: ModelVariantType = ModelVariantType.Normal
     prediction_type: SchedulerPredictionType = SchedulerPredictionType.Epsilon
     upcast_attention: bool = False
-    ztsnr_training: bool = False
 
 
 class MainCheckpointConfig(_CheckpointConfig, _MainConfig):