code: def make_config(args):
      config = ExLlamaConfig(args.config)
      config.model_path = args.model
  
      config.max_seq_len = args.length
      config.compress_pos_emb = args.compress_pos_emb
      config.set_auto_map(args.gpu_split)
      config.gpu_peer_fix = args.gpu_peer_fix
      config.alpha_value = args.alpha
      config.calculate_rotary_embedding_base()
  
      if args.flash_attn:
          config.use_flash_attn_2 = True
          try:
              config.max_input_len = int(args.flash_attn)
          except ValueError:
              pass
  
      config.matmul_recons_thd = args.matmul_recons_thd
      config.fused_mlp_thd = args.fused_mlp_thd
      config.sdp_thd = args.sdp_thd
      config.matmul_fused_remap = args.matmul_fused_remap
      config.fused_attn = not args.no_fused_attn
  
      config.rmsnorm_no_half2 = args.rmsnorm_no_half2
      config.rope_no_half2 = args.rope_no_half2
      config.matmul_no_half2 = args.matmul_no_half2
      config.silu_no_half2 = args.silu_no_half2
      config.concurrent_streams = args.concurrent_streams
  
      if args.theta:
          config.rotary_embedding_base = args.theta
  
      return config
  
file_path: exllama/model_init.py
imports: from model import ExLlama, ExLlamaCache, ExLlamaConfig
  from tokenizer import ExLlamaTokenizer
  import argparse, sys, os, glob
  from torch import version
  from globals import set_affinity_str
label_desc: Use image node_id 6 for calling a global function with example usage: make_config(args) and returns: config