text: import datetime
  
  import ray
  import torch
  from ray import tune
  from torch.utils.tensorboard import SummaryWriter
  
  from anfis.consequent_layer import ConsequentLayerType
  from anfis.hyperparameter_search import main
  from anfis.joint_membership import JointTrapMembership
  from anfis.joint_membership_optimized import JointDiffSigmoidMembershipV2
  from anfis.loader import load_training_data
  from anfis.trainer import make_joint_anfis, train_anfis, load_anfis
  from anfis.utils import test_anfis, save_fuzzy_membership_functions
  
  
  def load_and_test(train_data, checkpoint_file, rules_type=ConsequentLayerType.PLAIN):
      x_joint_definitons = [
          ('distance', JointTrapMembership(*[0, .25, .1, .1], constant_center=True)),
          ('theta_far', JointTrapMembership(*[0, .25, .1, .1], constant_center=True)),
          ('theta_near', JointTrapMembership(*[0, .25, .1, .1], constant_center=True)),
      ]
  
      outputs = ['angular_velocity']
  
  
      load_anfis(model, checkpoint_file)
  
      save_fuzzy_membership_functions(model)
  
      test_anfis(model, train_data, show_plots=True)
  
      print(model)
  
  
  def make_robot_anfis(data, rules_type=ConsequentLayerType.PLAIN, epochs=1000):
      x_joint_definitons = [
          # ('distance', JointTrapMembership(*[0, .25, 2, 2], constant_center=True)),
          # ('theta_far', JointTrapMembership(*[0, .25, 2, 2], constant_center=True)),
          # ('theta_near', JointTrapMembership(*[0, .25, 2, 2], constant_center=True)),
  
          # ('distance', JointDiffSigmoidMembership(*[0, 10, 4, 4], constant_center=True)),
          # ('theta_far', JointDiffSigmoidMembership(*[0, 10, 4, 4], constant_center=True)),
          # ('theta_near', JointDiffSigmoidMembership(*[0, 10, 4, 4], constant_center=True)),
  
          ('distance', JointDiffSigmoidMembershipV2(*[0, 10, 4, 4], constant_center=True)),
          ('theta_far', JointDiffSigmoidMembershipV2(*[0, 10, 4, 4], constant_center=True)),
          ('theta_near', JointDiffSigmoidMembershipV2(*[0, 10, 4, 4], constant_center=True)),
      ]
  
      outputs = ['angular_velocity']
  
      model = make_joint_anfis(x_joint_definitons, outputs, rules_type=rules_type)
  
      summary = SummaryWriter(log_dir=f'runs/ANFIS {datetime.datetime.now().strftime("%Y-%m-%d-%H-%M-%S")}')
  
      train_anfis(model, data, epochs=epochs, summary=summary)
  
  
  def hyper_paramerter_tuner(train_data):
      ray.init(log_to_driver=False, include_dashboard=False)
  
      criterion = torch.nn.MSELoss(reduction='sum')
  
      config = {
          "lr": tune.loguniform(1e-5, 1e0),
          # 'h': tune.choice([False]),
          # 'm': tune.choice([.99, 0.8]),
          'm': tune.uniform(.75, 1),
          # 'd': 0,
          # 'wd': tune.choice([0]),
          's': tune.uniform(0.1, 5),
          'w1': tune.uniform(-0.4, 3),
          'w2': tune.uniform(-0.4, 3),
          'b': tune.choice([32, 64, 128, 256, 512, 1024]),
      }
  
      # folder_name = f'ANFIS Search {datetime.datetime.now().strftime("%Y-%m-%d-%H-%M")}'
      # folder_name = f'ANFIS Search {datetime.datetime.now().strftime("%Y-%m-%d-%H-%M")}'
      folder_name = f'ANFIS Search 2021-07-23-00-27'
  
      # folder_name = f'ANFIS Search'
  
      def create_model(config):
          x_joint_definitons = [
              ('distance', JointTrapMembership(*[0, config['s'], config['w1'], config['w2']], constant_center=True)),
              ('theta_far', JointTrapMembership(*[0, config['s'], config['w1'], config['w2']], constant_center=True)),
              ('theta_near', JointTrapMembership(*[0, config['s'], config['w1'], config['w2']], constant_center=True)),
          ]
  
          outputs = ['angular_velocity']
  
          model = make_joint_anfis(x_joint_definitons, outputs, rules_type=config['h'])
          return model
  
      def create_dataset(config):
          return load_training_data('test1', batch_size=config['b'], num_workers=0,
                                    data_folder=r'C:\Users\mariu\Documents\GitHub\ANFIS\data')
  
      main(create_dataset, config, create_model, criterion, num_samples=50, folder_name=folder_name, max_num_epochs=1000,
           grace_period=50, num_checkpoints=10)
  
  
  def make_hyp_robot_anfis(dataset, hparams, epochs=1000):
      hparams.setdefault('h', ConsequentLayerType.PLAIN)
      hparams.setdefault('n', False)
      hparams.setdefault('m', 0.99)
      hparams.setdefault('wd', 0)
      hparams.setdefault('d', 0)
  
      x_joint_definitons = [
          ('distance', JointTrapMembership(*[0, hparams['s'], hparams['w1'], hparams['w2']], constant_center=True)),
          ('theta_far', JointTrapMembership(*[0, hparams['s'], hparams['w1'], hparams['w2']], constant_center=True)),
          ('theta_near', JointTrapMembership(*[0, hparams['s'], hparams['w1'], hparams['w2']], constant_center=True)),
      ]
  
      outputs = ['angular_velocity']
  
      model = make_joint_anfis(x_joint_definitons, outputs, rules_type=hparams['h'])
  
      summary = SummaryWriter(log_dir=f'runs/ANFIS {datetime.datetime.now().strftime("%Y-%m-%d-%H-%M-%S")}')
  
      train_anfis(model, dataset, epochs=epochs, summary=summary, lr=hparams['lr'], momentum=hparams['m'],
                  dampening=hparams['d'], weight_decay=hparams['wd'], nesterov=hparams['n'])
  
  
  if __name__ == '__main__':
      dataset = load_training_data('test1', num_workers=2, dtype=torch.float64)
      # num_data, i, o = training_data_selection("offline_training_v2/1inputs100.csv", "offline_training_v2/1outputs100.csv")
      # num_inputs = 3
      #
      # outputs = output_csv(o, num_data)
      # dataset = input_data(i, outputs, num_data, num_inputs)
  
      # load_and_test(dataset, 'runs/ANFIS 2021-07-22-22-28-48/checkpoint.pth')
      # make_robot_anfis(dataset, False, epochs=1000)
      make_robot_anfis(dataset, rules_type=ConsequentLayerType.PLAIN, epochs=1000)
  
      # hyper_paramerter_tuner(dataset)
  
      hparams = {
          "b": 32,
          "lr": 8.226783314915011e-05,
          "m": 0.9933396281384579,
          "s": 3.281225890798252,
          "w1": 0.1031245552184179,
          "w2": -0.24263594010904674
      }
      # dataset = load_training_data('test1', num_workers=0, batch_size=hparams['b'])
  
      # load_and_test(dataset, 'runs/ANFIS 2021-07-23-11-09-21/checkpoint.pth')
      # make_hyp_robot_anfis(dataset, hparams)
  