def parse()

in container-serving/resources/FairMOT/config.py [0:0]

• 33 lines of code
• 15 McCabe index (conditional complexity)

  def parse(self, args=''):
    #self.gpus='0'
    self.gpus_str = self.gpus
    self.gpus = [int(gpu) for gpu in self.gpus.split(',')]
    self.gpus = [i for i in range(len(self.gpus))] if self.gpus[0] >=0 else [-1]
    self.lr_step = [int(i) for i in self.lr_step.split(',')]

    self.fix_res = not self.keep_res
    print('Fix size testing.' if self.fix_res else 'Keep resolution testing.')
    self.reg_offset = not self.not_reg_offset

    if self.head_conv == -1: # init default head_conv
      self.head_conv = 256 if 'dla' in self.arch else 256
    self.pad = 31
    self.num_stacks = 1

    if self.trainval:
      self.val_intervals = 100000000

    if self.master_batch_size == -1:
      self.master_batch_size = self.batch_size // len(self.gpus)
    rest_batch_size = (self.batch_size - self.master_batch_size)
    self.chunk_sizes = [self.master_batch_size]
    for i in range(len(self.gpus) - 1):
      slave_chunk_size = rest_batch_size // (len(self.gpus) - 1)
      if i < rest_batch_size % (len(self.gpus) - 1):
        slave_chunk_size += 1
      self.chunk_sizes.append(slave_chunk_size)
    print('training chunk_sizes:', self.chunk_sizes)

    self.root_dir = os.path.join(os.path.dirname(__file__), '..', '..')
    self.exp_dir = os.path.join(self.root_dir, 'exp', self.task)
    self.save_dir = os.path.join(self.exp_dir, self.exp_id)
    self.debug_dir = os.path.join(self.save_dir, 'debug')
    print('The output will be saved to ', self.save_dir)
    
    if self.resume and self.load_model == '':
      model_path = self.save_dir[:-4] if self.save_dir.endswith('TEST') \
                  else self.save_dir
      self.load_model = os.path.join(model_path, 'model_last.pth')