Float To Sigmas

Documentation

• Class name: FloatToSigmas
• Category: KJNodes/noise
• Output node: False

Transforms a list of float values into a tensor of sigmas, facilitating the conversion of numerical data into a format suitable for noise generation and manipulation within neural networks.

Input types

Required

• float_list
  • A list of float values to be converted into a sigmas tensor. This input is crucial for defining the specific noise levels to be applied in the neural network's processing.
  • Comfy dtype: FLOAT
  • Python dtype: List[float]

Output types

• SIGMAS
  • Comfy dtype: SIGMAS
  • A tensor of sigmas derived from the input list of float values, used for noise generation and manipulation in neural network operations.
  • Python dtype: torch.Tensor

Usage tips

• Infra type: GPU
• Common nodes: unknown

Source code

class FloatToSigmas:
    @classmethod
    def INPUT_TYPES(s):
        return {"required":
                    {
                     "float_list": ("FLOAT", {"default": 0.0, "forceInput": True}),
                     }
                }
    RETURN_TYPES = ("SIGMAS",)
    RETURN_NAMES = ("SIGMAS",)
    CATEGORY = "KJNodes/noise"
    FUNCTION = "customsigmas"
    DESCRIPTION = """
Creates a sigmas tensor from list of float values.  

"""
    def customsigmas(self, float_list):
        return torch.tensor(float_list, dtype=torch.float32),