'''Main file for running experiments.

'''


import logging

from cortex._lib import (config, data, exp, optimizer, setup_cortex,
                         setup_experiment, train)
from cortex._lib.utils import print_section

import torch

__author__ = 'R Devon Hjelm'
__author_email__ = 'erroneus@gmail.com'


logger = logging.getLogger('cortex')
viz_process = None


def run(model=None):
    '''Main function.

    '''
    # Parse the command-line arguments

    try:
        args = setup_cortex(model=model)

        if args.command == 'setup':
            # Performs setup only.
            config.setup()
            exit(0)
        else:
            config.set_config()
            print_section('EXPERIMENT')
            model = setup_experiment(args, model=model)

            print_section('DATA')
            data.setup(**exp.ARGS['data'])

            print_section('NETWORKS')
            if args.reload and not args.load_models:
                pass
            else:
                model.build()
                if args.load_models:
                    d = torch.load(args.load_models, map_location='cpu')
                    for k in args.reloads:
                        model.nets[k].load_state_dict(d['nets'][k].state_dict())

            print_section('OPTIMIZER')
            optimizer.setup(model, **exp.ARGS['optimizer'])

    except KeyboardInterrupt:
        print('Cancelled')
        exit(0)

    train.main_loop(model, **exp.ARGS['train'])

'''Main file for running experiments.

'''


import logging

from cortex._lib import (config, data, exp, optimizer, setup_cortex,
                         setup_experiment, train)
from cortex._lib.utils import print_section

import torch

__author__ = 'R Devon Hjelm'
__author_email__ = 'erroneus@gmail.com'


logger = logging.getLogger('cortex')
viz_process = None


def run(model=None):
    '''Main function.

    '''
    # Parse the command-line arguments

    try:
        args = setup_cortex(model=model)

        if args.command == 'setup':
            # Performs setup only.
            config.setup()
            exit(0)
        else:
            config.set_config()
            print_section('EXPERIMENT')
            model = setup_experiment(args, model=model)

            print_section('DATA')
            data.setup(**exp.ARGS['data'])

            print_section('NETWORKS')
            if args.reload and not args.load_models:
                pass
            else:
                model.build()
                if args.load_models:
                    d = torch.load(args.load_models, map_location='cpu')
                    for k in args.reloads:
                        model.nets[k].load_state_dict(d['nets'][k].state_dict())

            print_section('OPTIMIZER')
            optimizer.setup(model, **exp.ARGS['optimizer'])

    except KeyboardInterrupt:
        print('Cancelled')
        exit(0)

    train.main_loop(model, **exp.ARGS['train'])
    viz_process.terminate()

Terminate viz process at end of experiment.
Terminate viz process at end of experiment.

  '''Main file for running experiments.
  
  '''
  
  
  import logging
  
  from cortex._lib import (config, data, exp, optimizer, setup_cortex,
                           setup_experiment, train)
  from cortex._lib.utils import print_section
  
  import torch
  
  __author__ = 'R Devon Hjelm'
  __author_email__ = 'erroneus@gmail.com'
  
  
  logger = logging.getLogger('cortex')
  viz_process = None
  
  
  def run(model=None):
      '''Main function.
  
      '''
      # Parse the command-line arguments
  
      try:
          args = setup_cortex(model=model)
  
          if args.command == 'setup':
              # Performs setup only.
              config.setup()
              exit(0)
          else:
              config.set_config()
              print_section('EXPERIMENT')
              model = setup_experiment(args, model=model)
  
              print_section('DATA')
              data.setup(**exp.ARGS['data'])
  
              print_section('NETWORKS')
              if args.reload and not args.load_models:
                  pass
              else:
                  model.build()
                  if args.load_models:
                      d = torch.load(args.load_models, map_location='cpu')
                      for k in args.reloads:
                          model.nets[k].load_state_dict(d['nets'][k].state_dict())
  
              print_section('OPTIMIZER')
              optimizer.setup(model, **exp.ARGS['optimizer'])
  
      except KeyboardInterrupt:
          print('Cancelled')
          exit(0)
  
      train.main_loop(model, **exp.ARGS['train'])
+     viz_process.terminate()
  
Terminate viz process at end of experiment.
## Code Before:
'''Main file for running experiments.

'''


import logging

from cortex._lib import (config, data, exp, optimizer, setup_cortex,
                         setup_experiment, train)
from cortex._lib.utils import print_section

import torch

__author__ = 'R Devon Hjelm'
__author_email__ = 'erroneus@gmail.com'


logger = logging.getLogger('cortex')
viz_process = None


def run(model=None):
    '''Main function.

    '''
    # Parse the command-line arguments

    try:
        args = setup_cortex(model=model)

        if args.command == 'setup':
            # Performs setup only.
            config.setup()
            exit(0)
        else:
            config.set_config()
            print_section('EXPERIMENT')
            model = setup_experiment(args, model=model)

            print_section('DATA')
            data.setup(**exp.ARGS['data'])

            print_section('NETWORKS')
            if args.reload and not args.load_models:
                pass
            else:
                model.build()
                if args.load_models:
                    d = torch.load(args.load_models, map_location='cpu')
                    for k in args.reloads:
                        model.nets[k].load_state_dict(d['nets'][k].state_dict())

            print_section('OPTIMIZER')
            optimizer.setup(model, **exp.ARGS['optimizer'])

    except KeyboardInterrupt:
        print('Cancelled')
        exit(0)

    train.main_loop(model, **exp.ARGS['train'])

## Instruction:
Terminate viz process at end of experiment.
## Code After:
'''Main file for running experiments.

'''


import logging

from cortex._lib import (config, data, exp, optimizer, setup_cortex,
                         setup_experiment, train)
from cortex._lib.utils import print_section

import torch

__author__ = 'R Devon Hjelm'
__author_email__ = 'erroneus@gmail.com'


logger = logging.getLogger('cortex')
viz_process = None


def run(model=None):
    '''Main function.

    '''
    # Parse the command-line arguments

    try:
        args = setup_cortex(model=model)

        if args.command == 'setup':
            # Performs setup only.
            config.setup()
            exit(0)
        else:
            config.set_config()
            print_section('EXPERIMENT')
            model = setup_experiment(args, model=model)

            print_section('DATA')
            data.setup(**exp.ARGS['data'])

            print_section('NETWORKS')
            if args.reload and not args.load_models:
                pass
            else:
                model.build()
                if args.load_models:
                    d = torch.load(args.load_models, map_location='cpu')
                    for k in args.reloads:
                        model.nets[k].load_state_dict(d['nets'][k].state_dict())

            print_section('OPTIMIZER')
            optimizer.setup(model, **exp.ARGS['optimizer'])

    except KeyboardInterrupt:
        print('Cancelled')
        exit(0)

    train.main_loop(model, **exp.ARGS['train'])
    viz_process.terminate()
