class_docstr: Solver for raw tensorflow model.
class_docstr_tok: ["Solver","for","raw","tensorflow","model","."]
docstr: Set the experimental environment.
docstr_tok: ["Set","the","experimental","environment","."]
code: def set_experimental_environment(self):
      """Set the experimental environment."""
      # Set configuration
      session_conf = get_session_conf(self.config)
  
      task_config = self.config["data"]["task"]
      batch_size = task_config["batch_size"]
      num_epochs = task_config["epochs"]
  
      saver_conf = self.config["solver"]["saver"]
      smax_to_keep = saver_conf["max_to_keep"]
      save_checkpoint_steps = saver_conf["save_checkpoint_steps"]
      resume_model_path = saver_conf.get("resume_model_path", None)
      print_every = saver_conf["print_every"]
  
      return (
          session_conf,
          smax_to_keep,
          batch_size,
          num_epochs,
          save_checkpoint_steps,
          resume_model_path,
          print_every,
      )
  
imports: import re
  import math
  import numpy
  import delta.compat
  from absl import logging
  from delta.utils.solver.base_solver import Solver
  from delta import utils
  from delta.utils.register import registers
  from delta.utils.solver.utils.solver_utils import get_checkpoint_dir
  from delta.utils.solver.utils.solver_utils import get_ckpt_state
  from delta.utils.solver.utils.solver_utils import get_session_conf
  from delta.utils.solver.utils.solver_utils import to_saved_model
  from delta.utils.solver.utils.solver_utils import run_metrics
label_desc: Use image node_id 5 for calling the RawSolver obj's underlying member method code with example usage: obj.set_experimental_environment() and returns: session_conf,  smax_to_keep,  batch_size,  num_epochs,  save_checkpoint_steps,  resume_model_path,  print_every