trainer:
  devices: '1'
  num_nodes: 1
model:
  inference_params:
    class_path: t2v_enhanced.model.pl_module_params_controlnet.InferenceParams
    init_args:
      num_inference_steps: 50  # number of inference steps
      frame_rate: 8
      eta: 1.0   # eta used for DDIM sampler
      guidance_scale: 7.5     # classifier free guidance scale
      conditioning_type: fixed
      start_from_real_input: false
      n_autoregressive_generations: 6  # how many autoregressive generations
      scheduler_cls: '' # we can load other models
  unet_params:
    class_path: t2v_enhanced.model.pl_module_params_controlnet.UNetParams
    init_args:
      use_standard_attention_processor: False
  opt_params:
    class_path: t2v_enhanced.model.pl_module_params_controlnet.OptimizerParams
    init_args:
      noise_generator:
        class_path: t2v_enhanced.model.video_noise_generator.NoiseGenerator
        init_args:
          mode: vanilla # can be 'vanilla','mixed_noise', 'consistI2V' or 'mixed_noise_consistI2V'
          alpha: 1.0
          shared_noise_across_chunks: True  # if true, shared noise between all chunks of a video
          forward_steps: 850 # number of DDPM forward steps
          radius: [2,2,2]  # radius for time, width and height
n_predictions: 300
data:
  class_path: t2v_enhanced.model.datasets.prompt_reader.PromptReader
  init_args:
    prompt_cfg: 
      type: file
      content: /home/roberto.henschel/T2V-Enhanced/repo/training_code/t2v_enhanced/evaluation_prompts/prompts_long_eval.txt