pipeKSamplerAdvanced v1 (Legacy)

Documentation

• Class name: ttN pipeKSamplerAdvanced
• Category: 🌏 tinyterra/legacy
• Output node: True

This node is designed for advanced sampling in generative models, incorporating various techniques such as LoRA adjustments, noise control, and optional model components to refine and generate high-quality samples. It supports complex workflows including image upscaling, embedding workflows, and handling of optional inputs for enhanced flexibility and customization in sample generation.

Input types

Required

• pipe
  • unknown
  • Comfy dtype: PIPE_LINE
  • Python dtype: unknown
• lora_name
  • Specifies the name of the LoRA model to be used for adjustments, enhancing the control over the sampling process.
  • Comfy dtype: COMBO[STRING]
  • Python dtype: str
• lora_model_strength
  • Determines the strength of the LoRA model adjustments, allowing for fine-tuning of the model's behavior during sampling.
  • Comfy dtype: FLOAT
  • Python dtype: float
• lora_clip_strength
  • Specifies the strength of the LoRA clip adjustments, impacting the final visual quality of the samples.
  • Comfy dtype: FLOAT
  • Python dtype: float
• upscale_method
  • Specifies the method used for upscaling the generated samples, affecting the resolution and clarity.
  • Comfy dtype: COMBO[STRING]
  • Python dtype: str
• factor
  • The factor by which the image is upscaled, directly influencing the output image size.
  • Comfy dtype: FLOAT
  • Python dtype: float
• crop
  • Determines if and how the output images are cropped, affecting the final composition and aspect ratio.
  • Comfy dtype: COMBO[STRING]
  • Python dtype: str
• sampler_state
  • Represents the state of the sampler, including configurations and parameters for the sampling process.
  • Comfy dtype: COMBO[STRING]
  • Python dtype: str
• add_noise
  • Controls whether noise is added to the sampling process, with options to enable or disable noise, affecting the texture and details of the generated samples.
  • Comfy dtype: COMBO[STRING]
  • Python dtype: str
• steps
  • Defines the number of steps to perform in the sampling process, directly impacting the quality and characteristics of the generated samples.
  • Comfy dtype: INT
  • Python dtype: int
• cfg
  • Configuration setting for the sampling process, providing a means to customize various aspects of sample generation.
  • Comfy dtype: FLOAT
  • Python dtype: float
• sampler_name
  • Identifies the specific sampler to be used, allowing for selection among multiple sampling strategies.
  • Comfy dtype: COMBO[STRING]
  • Python dtype: str
• scheduler
  • Specifies the scheduler for controlling the sampling process, aiding in the management of sampling steps and their execution.
  • Comfy dtype: COMBO[STRING]
  • Python dtype: str
• start_at_step
  • unknown
  • Comfy dtype: INT
  • Python dtype: unknown
• end_at_step
  • unknown
  • Comfy dtype: INT
  • Python dtype: unknown
• return_with_leftover_noise
  • Controls whether the final output includes leftover noise, affecting the visual texture of the samples.
  • Comfy dtype: COMBO[STRING]
  • Python dtype: str
• image_output
  • Determines how the output images are handled, including options for hiding or saving the generated samples.
  • Comfy dtype: COMBO[STRING]
  • Python dtype: str
• save_prefix
  • Prefix for saving the generated samples, facilitating organization and retrieval of output files.
  • Comfy dtype: STRING
  • Python dtype: str

Optional

• noise_seed
  • The seed used for generating noise, ensuring reproducibility and consistency in the noise added to the samples.
  • Comfy dtype: INT
  • Python dtype: int
• optional_model
  • Specifies an optional model to be used in the sampling process, allowing for customization and experimentation.
  • Comfy dtype: MODEL
  • Python dtype: str
• optional_positive
  • Optional positive conditioning to guide the sampling towards desired attributes.
  • Comfy dtype: CONDITIONING
  • Python dtype: str
• optional_negative
  • Optional negative conditioning to steer the sampling away from undesired attributes.
  • Comfy dtype: CONDITIONING
  • Python dtype: str
• optional_latent
  • Specifies an optional latent input for the sampling process, providing a starting point or influence.
  • Comfy dtype: LATENT
  • Python dtype: str
• optional_vae
  • Specifies an optional VAE model to be used, affecting the encoding and decoding of samples.
  • Comfy dtype: VAE
  • Python dtype: str
• optional_clip
  • Specifies an optional CLIP model for additional guidance or conditioning in the sampling process.
  • Comfy dtype: CLIP
  • Python dtype: str
• xyPlot
  • Optional XY plot data for visualization or analysis purposes during the sampling process.
  • Comfy dtype: XYPLOT
  • Python dtype: str

Output types

• pipe
  • Comfy dtype: PIPE_LINE
  • The pipeline configuration used for the sampling process.
  • Python dtype: str
• model
  • Comfy dtype: MODEL
  • The model used in the sampling process.
  • Python dtype: str
• positive
  • Comfy dtype: CONDITIONING
  • Positive conditioning data used to guide the sampling process.
  • Python dtype: str
• negative
  • Comfy dtype: CONDITIONING
  • Negative conditioning data used to steer the sampling away from undesired attributes.
  • Python dtype: str
• latent
  • Comfy dtype: LATENT
  • The latent representation of the sample.
  • Python dtype: str
• vae
  • Comfy dtype: VAE
  • The VAE model used in the sampling process, if applicable.
  • Python dtype: str
• clip
  • Comfy dtype: CLIP
  • The CLIP model used for additional guidance or conditioning, if applicable.
  • Python dtype: str
• image
  • Comfy dtype: IMAGE
  • The final image output from the sampling process.
  • Python dtype: str
• seed
  • Comfy dtype: INT
  • The seed value used for reproducibility in the sampling process.
  • Python dtype: int
• ui
  • Provides a user interface component for visualizing the generated samples, enhancing the interaction and presentation of results.

Usage tips

• Infra type: GPU
• Common nodes: unknown

Source code

class ttN_pipeKSamplerAdvanced:
    version = '1.0.5'
    upscale_methods = ["None", "nearest-exact", "bilinear", "area", "bicubic", "lanczos", "bislerp"]
    crop_methods = ["disabled", "center"]

    def __init__(self):
        pass

    @classmethod
    def INPUT_TYPES(cls):
        return {"required":
                {"pipe": ("PIPE_LINE",),

                "lora_name": (["None"] + folder_paths.get_filename_list("loras"),),
                "lora_model_strength": ("FLOAT", {"default": 1.0, "min": -10.0, "max": 10.0, "step": 0.01}),
                "lora_clip_strength": ("FLOAT", {"default": 1.0, "min": -10.0, "max": 10.0, "step": 0.01}),

                "upscale_method": (cls.upscale_methods,),
                "factor": ("FLOAT", {"default": 2, "min": 0.0, "max": 10.0, "step": 0.25}),
                "crop": (cls.crop_methods,),
                "sampler_state": (["Sample", "Hold"], ),

                "add_noise": (["enable", "disable"], ),

                "steps": ("INT", {"default": 20, "min": 1, "max": 10000}),
                "cfg": ("FLOAT", {"default": 8.0, "min": 0.0, "max": 100.0}),
                "sampler_name": (comfy.samplers.KSampler.SAMPLERS,),
                "scheduler": (comfy.samplers.KSampler.SCHEDULERS,),

                "start_at_step": ("INT", {"default": 0, "min": 0, "max": 10000}),
                "end_at_step": ("INT", {"default": 10000, "min": 0, "max": 10000}),
                "return_with_leftover_noise": (["disable", "enable"], ),

                "image_output": (["Hide", "Preview", "Save", "Hide/Save"],),
                "save_prefix": ("STRING", {"default": "ComfyUI"})
                },
                "optional": 
                {"noise_seed": ("INT", {"default": 0, "min": 0, "max": 0xffffffffffffffff}),
                 "optional_model": ("MODEL",),
                 "optional_positive": ("CONDITIONING",),
                 "optional_negative": ("CONDITIONING",),
                 "optional_latent": ("LATENT",),
                 "optional_vae": ("VAE",),
                 "optional_clip": ("CLIP",),
                 "xyPlot": ("XYPLOT",),
                },
                "hidden":
                {"prompt": "PROMPT", "extra_pnginfo": "EXTRA_PNGINFO", "my_unique_id": "UNIQUE_ID",
                 "embeddingsList": (folder_paths.get_filename_list("embeddings"),),
                 "ttNnodeVersion": ttN_pipeKSamplerAdvanced.version},
        }

    RETURN_TYPES = ("PIPE_LINE", "MODEL", "CONDITIONING", "CONDITIONING", "LATENT", "VAE", "CLIP", "IMAGE", "INT",)
    RETURN_NAMES = ("pipe", "model", "positive", "negative", "latent","vae", "clip", "image", "seed", )
    OUTPUT_NODE = True
    FUNCTION = "sample"
    CATEGORY = "🌏 tinyterra/legacy"

    def sample(self, pipe,
               lora_name, lora_model_strength, lora_clip_strength,
               sampler_state, add_noise, steps, cfg, sampler_name, scheduler, image_output, save_prefix, denoise=1.0, 
               noise_seed=None, optional_model=None, optional_positive=None, optional_negative=None, optional_latent=None, optional_vae=None, optional_clip=None, xyPlot=None, upscale_method=None, factor=None, crop=None, prompt=None, extra_pnginfo=None, my_unique_id=None, start_at_step=None, end_at_step=None, return_with_leftover_noise=False):

        force_full_denoise = True
        if return_with_leftover_noise == "enable":
            force_full_denoise = False

        disable_noise = False
        if add_noise == "disable":
            disable_noise = True

        out = ttN_TSC_pipeKSampler.sample(self, pipe, lora_name, lora_model_strength, lora_clip_strength, sampler_state, steps, cfg, sampler_name, scheduler, image_output, save_prefix, denoise, 
               optional_model, optional_positive, optional_negative, optional_latent, optional_vae, optional_clip, noise_seed, xyPlot, upscale_method, factor, crop, prompt, extra_pnginfo, my_unique_id, start_at_step, end_at_step, force_full_denoise, disable_noise)

        return out