text: import subprocess
  import sys
  
  
  # dataset = sys.argv[2]
  # u_size = sys.argv[3]
  # v_size = sys.argv[4]
  # problem = sys.argv[1]
  # mode = sys.argv[5]
  mode = "output"
  problems = ["e-obm"]
  g_sizes = [(100, 100)]
  datasets = ["gmission", "gmission-var"]
  
  
  def get_models(model, u, v, dataset, problem, p, mode):
      if dataset == "er":
          weight_dist = "uniform"
          m, var = 0, 1
      else:
          weight_dist = dataset
          m, var = -1, -1
  
      if mode == "logs":
          subprocess.run(
              f"scp -r alomrani@cedar.computecanada.ca:~/projects/def-khalile2/alomrani/{mode}_{problem}_{dataset}_{u}by{v}_p={p}_{weight_dist}_m={m}_v={var}_a=3/{model} \
          {mode}/{mode}_{problem}_{dataset}_{u}by{v}_p={p}_{dataset}_m={m}_v={var}_a=3",
              shell=True,
          )
      else:
          subprocess.run(
              f"scp -r alomrani@cedar.computecanada.ca:~/projects/def-khalile2/alomrani/{mode}_{problem}_{dataset}_{u}by{v}_p={p}_{weight_dist}_m={m}_v={var}_a=3/{model} \
          {mode}s/{mode}_{problem}_{dataset}_{u}by{v}_p={p}_{dataset}_m={m}_v={var}_a=3",
              shell=True,
          )
  
  
  models = ["inv-ff", "ff", "ff-hist", "ff-supervised", "inv-ff-hist"]
  
  for problem in problems:
      for dataset in datasets:
          for u_size, v_size in g_sizes:
              g_params = [-1] if dataset != "er" else [0.05, 0.1, 0.15, 0.2]
              for m in models:
                  for p in g_params:
                      get_models(m, u_size, v_size, dataset, problem, p, mode)
  