code: def __init__(
      self,
      hh_size=4,
      recent_size=512,
      k_seq_dim=2,
      v_seq_dim=2,
  ):
      print(f"H2OKVCache-LayerWise: {hh_size}, {recent_size}")
      self.hh_size = hh_size
      self.recent_size = recent_size
      self.cache_size = hh_size + recent_size
      self.k_seq_dim = k_seq_dim
      self.v_seq_dim = v_seq_dim
      self.hh_score = None
  
imports: import math
  from typing import Optional, Tuple
  import pdb
  import torch
  from torch import nn
  import torch.utils.checkpoint
  import torch.nn.functional
  from transformers.models.llama.modeling_llama import LlamaAttention, rotate_half, apply_rotary_pos_emb, LlamaRotaryEmbedding, apply_rotary_pos_emb, LlamaForCausalLM
  import types
  from transformers.configuration_utils import PretrainedConfig
label_desc: Use image node_id 1 to create a new H2OKVCache_LayerWise object  with example: obj = H2OKVCache_LayerWise(hh_size, recent_size, k_seq_dim, v_seq_dim)