class FieldDescriptions: denoising_start = "When to start denoising, expressed a percentage of total steps" denoising_end = "When to stop denoising, expressed a percentage of total steps" cfg_scale = "Classifier-Free Guidance scale" scheduler = "Scheduler to use during inference" positive_cond = "Positive conditioning tensor" negative_cond = "Negative conditioning tensor" noise = "Noise tensor" clip = "CLIP (tokenizer, text encoder, LoRAs) and skipped layer count" unet = "UNet (scheduler, LoRAs)" vae = "VAE" cond = "Conditioning tensor" controlnet_model = "ControlNet model to load" vae_model = "VAE model to load" lora_model = "LoRA model to load" main_model = "Main model (UNet, VAE, CLIP) to load" sdxl_main_model = "SDXL Main model (UNet, VAE, CLIP1, CLIP2) to load" sdxl_refiner_model = "SDXL Refiner Main Modde (UNet, VAE, CLIP2) to load" onnx_main_model = "ONNX Main model (UNet, VAE, CLIP) to load" lora_weight = "The weight at which the LoRA is applied to each model" compel_prompt = "Prompt to be parsed by Compel to create a conditioning tensor" raw_prompt = "Raw prompt text (no parsing)" sdxl_aesthetic = "The aesthetic score to apply to the conditioning tensor" skipped_layers = "Number of layers to skip in text encoder" seed = "Seed for random number generation" steps = "Number of steps to run" width = "Width of output (px)" height = "Height of output (px)" control = "ControlNet(s) to apply" ip_adapter = "IP-Adapter to apply" t2i_adapter = "T2I-Adapter(s) to apply" denoised_latents = "Denoised latents tensor" latents = "Latents tensor" strength = "Strength of denoising (proportional to steps)" metadata = "Optional metadata to be saved with the image" metadata_collection = "Collection of Metadata" metadata_item_polymorphic = "A single metadata item or collection of metadata items" metadata_item_label = "Label for this metadata item" metadata_item_value = "The value for this metadata item (may be any type)" workflow = "Optional workflow to be saved with the image" interp_mode = "Interpolation mode" torch_antialias = "Whether or not to apply antialiasing (bilinear or bicubic only)" fp32 = "Whether or not to use full float32 precision" precision = "Precision to use" tiled = "Processing using overlapping tiles (reduce memory consumption)" detect_res = "Pixel resolution for detection" image_res = "Pixel resolution for output image" safe_mode = "Whether or not to use safe mode" scribble_mode = "Whether or not to use scribble mode" scale_factor = "The factor by which to scale" blend_alpha = ( "Blending factor. 0.0 = use input A only, 1.0 = use input B only, 0.5 = 50% mix of input A and input B." ) num_1 = "The first number" num_2 = "The second number" mask = "The mask to use for the operation" board = "The board to save the image to" image = "The image to process" tile_size = "Tile size" inclusive_low = "The inclusive low value" exclusive_high = "The exclusive high value" decimal_places = "The number of decimal places to round to" freeu_s1 = 'Scaling factor for stage 1 to attenuate the contributions of the skip features. This is done to mitigate the "oversmoothing effect" in the enhanced denoising process.' freeu_s2 = 'Scaling factor for stage 2 to attenuate the contributions of the skip features. This is done to mitigate the "oversmoothing effect" in the enhanced denoising process.' freeu_b1 = "Scaling factor for stage 1 to amplify the contributions of backbone features." freeu_b2 = "Scaling factor for stage 2 to amplify the contributions of backbone features."