peal.explainers.counterfactual_explainer.TIMEConfig¶

class peal.explainers.counterfactual_explainer.TIMEConfig[source]¶

Bases: ExplainerConfig

This class defines the config of a ACEConfig.

Methods

Attributes

`adam_beta1`
`adam_beta2`
`adam_epsilon`
`base_prompt`
`chunk`
`chunks`
`class_custom_token`
`custom_obj_token`
`custom_tokens_context`
`custom_tokens_init`
`data_config`
`editing_type`
`enable_xformers_memory_efficient_attention`
`exp_name`
`explainer_type`	The type of explanation that shall be used.
`generator`
`generic_custom_tokens`
`gpu`
`guidance_scale_denoising`
`guidance_scale_invertion`
`image_size`
`inference_batch_size`
`iterations`
`l2`
`label_query`
`label_target`
`learn_dataset_embedding`
`lr`
`max_attacks`
`max_epoch`
`merge_chunks`
`mini_batch_size`
`num_inference_steps`
`num_samples`
`p`
`predictor_image_size`
`predictor_path`
`prompt_connector`
`recover`
`sd_image_size`
`sd_model`
`total_num_inference_steps`
`train_batch_size`
`use_fp16`
`use_lora`
`use_negative_guidance_denoise`
`use_negative_guidance_inverse`
`weight_decay`
`y_target_goal_confidence`

explainer_type: str = 'TIME'¶: The type of explanation that shall be used. Options: [‘counterfactual’, ‘lrp’]

predictor_path: str | None = None¶

generator: None | GeneratorConfig = None¶

data_config: None | DataConfig = None¶

editing_type: str = 'ddpm_inversion'¶

sd_model: str = 'CompVis/stable-diffusion-v1-4'¶

use_negative_guidance_denoise: bool = True¶

use_negative_guidance_inverse: bool = True¶

guidance_scale_denoising: list = [12]¶

guidance_scale_invertion: list = [8]¶

num_inference_steps: list = [50]¶

exp_name: str = 'time'¶

label_target: int = -1¶

label_query: int = 31¶

class_custom_token: list = ['|<A*01>| |<A*02>| |<A*03>|', '|<A*11>| |<A*12>| |<A*13>|']¶

base_prompt: str = ''¶

prompt_connector: str = ''¶

chunks: int = 1¶

chunk: int = 0¶

enable_xformers_memory_efficient_attention: bool = True¶

use_fp16: bool = False¶

sd_image_size: int = 128¶

custom_obj_token: str = '|<C*>|'¶

p: float = 0.93¶

l2: float = 0.0¶

inference_batch_size: int = 1¶

predictor_image_size: int = 128¶

recover: bool = False¶

num_samples: int = 9999999999999999¶

merge_chunks: bool = False¶

generic_custom_tokens: list = ['|<C*1>|', '|<C*2>|', '|<C*3>|']¶

total_num_inference_steps: int = 50¶

custom_tokens_context: list = ['|<C*1>|', '|<C*2>|', '|<C*3>|']¶

custom_tokens_init: list = ['<|endoftext|>', '<|endoftext|>', '<|endoftext|>']¶

mini_batch_size: int = 1¶

gpu: str = '0'¶

lr: float = 0.0001¶

adam_beta1: float = 0.9¶

adam_beta2: float = 0.999¶

adam_epsilon: float = 1e-09¶

weight_decay: float = 0.0001¶

iterations: int = 100¶

max_epoch: int = 30¶

train_batch_size: int = 64¶

image_size: int = 128¶

y_target_goal_confidence: float = 0.9¶

max_attacks: int = 1¶

use_lora: bool = True¶

learn_dataset_embedding: bool = False¶