nn/basicNetwork.py
def make_ckdir(self, ckdir, patch_size, par_dir=None):
        """
        Made checkpoint directory for the neural network
        :param ckdir: base directory of the ckpt
        :param patch_size: size of the input patch, could be a single number of tuple
        :param par_dir: if not None, the ckpt will be stored in ckdir/par_dir
        :return:
        """
        if type(patch_size) is list:
            patch_size = patch_size[0]
        # make unique directory for save
        dir_name = '{}_PS{}_BS{}_EP{}_LR{}_DS{}_DR{}'.\
            format(self.model_name, patch_size, self.bs, self.epochs, self.lr, self.ds, self.dr)
        if par_dir is None:
            self.ckdir = os.path.join(ckdir, dir_name)
        else:
            self.ckdir = os.path.join(ckdir, par_dir, dir_name)

        Made checkpoint directory for the neural network
        :param ckdir: base directory of the ckpt
        :param patch_size: size of the input patch, could be a single number of tuple
        :param par_dir: if not None, the ckpt will be stored in ckdir/par_dir
        :return:
        
Made checkpoint directory for the neural network
Made checkpoint directory for the neural network
def make_ckdir(self, ckdir, patch_size, par_dir=None):
        if type(patch_size) is list:
            patch_size = patch_size[0]
        dir_name = '{}_PS{}_BS{}_EP{}_LR{}_DS{}_DR{}'.\
            format(self.model_name, patch_size, self.bs, self.epochs, self.lr, self.ds, self.dr)
        if par_dir is None:
            self.ckdir = os.path.join(ckdir, dir_name)
        else:
            self.ckdir = os.path.join(ckdir, par_dir, dir_name)
def make_ckdir ( self , ckdir , patch_size , par_dir = None ) : if type ( patch_size ) is list : patch_size = patch_size [ 0 ] dir_name = '{}_PS{}_BS{}_EP{}_LR{}_DS{}_DR{}' . format ( self . model_name , patch_size , self . bs , self . epochs , self . lr , self . ds , self . dr ) if par_dir is None : self . ckdir = os . path . join ( ckdir , dir_name ) else : self . ckdir = os . path . join ( ckdir , par_dir , dir_name )
Made checkpoint directory for the neural network
Made checkpoint directory for the neural network
"""
        Made checkpoint directory for the neural network
        :param ckdir: base directory of the ckpt
        :param patch_size: size of the input patch, could be a single number of tuple
        :param par_dir: if not None, the ckpt will be stored in ckdir/par_dir
        :return:
        """ # make unique directory for save
None
self
ckdir
base directory of the ckpt
base directory of the ckpt
patch_size
size of the input patch, could be a single number of tuple
size of the input patch could be a single number of tuple
par_dir
if not None, the ckpt will be stored in ckdir/par_dir
if not None the ckpt will be stored in ckdir / par_dir