def save_data(self): if not self.debug_mode: BasicFunctions_szz.save_pr( self.program_info['path_save'], self.program_info['save_name'], [self.tensor_data, self.tensor_info, self.update_info], ['tensor_data', 'tensor_info', 'update_info'])
def save_data(self): if not self.debug_mode: BasicFunctions_szz.save_pr( self.program_info['path_save'], self.program_info['save_name'], [ self.weight, self.tensor_info, self.update_info, self.tensor_shape, self.para ], [ 'weight', 'tensor_info', 'update_info', 'tensor_shape', 'para' ])
def __init__(self, device='cuda', dtype=torch.float64, debug_mode=False): self.debug_mode = debug_mode self.program_info = dict() self.device_type = device self.device = BasicFunctions_szz.get_best_gpu(device=device) self.dtype = dtype self.calculate_program_info_time(mode='start')
def load_weight(self): load_path = self.program_info['path_save'] + self.program_info[ 'save_name'] if os.path.isfile(load_path): self.weight, self.tensor_info, self.update_info, self.tensor_shape = \ BasicFunctions_szz.load_pr(load_path, ['weight', 'tensor_info', 'update_info', 'tensor_shape']) self.weight.data = self.weight.data.to(self.device)
def print_program_info(self, mode='start'): if mode == 'start': print('This program starts at ' + time.strftime("%Y-%m-%d %H:%M:%S", time.localtime())) print(BasicFunctions_szz.sort_dict(self.para)) elif mode == 'end': print('This program ends at ' + time.strftime("%Y-%m-%d %H:%M:%S", time.localtime())) print( 'This program consumes ' + str(self.program_info['end_time']['time'] - self.program_info['start_time']['time']) + ' seconds of wall time.')
def save_data(self): BasicFunctions_szz.save_pr(self.program_info['path_save'], self.program_info['save_name'], [self.accuracy, self.test_info], ['accuracy', 'test_info'])
def load_accuracy(self): load_path = self.program_info['path_save'] + self.program_info[ 'save_name'] if os.path.isfile(load_path): self.accuracy, self.test_info = BasicFunctions_szz.load_pr( load_path, ['accuracy', 'test_info'])
def load_gtn(self): load_path = self.program_info['path_save'] + self.program_info[ 'save_name'] if os.path.isfile(load_path): self.tensor_data, self.tensor_info, self.update_info = \ BasicFunctions_szz.load_pr(load_path, ['tensor_data', 'tensor_info', 'update_info'])
def integrate_codebook(self): BasicFunctions_szz.integrate_codebook( self.program_info['path_save'], self.program_info['program_name'])
def name_md5_generate(self): self.program_info['save_name'] = BasicFunctions_szz.name_generator_md5( self.program_info['path_save'], self.program_info['program_name'], self.para, rough_mode=self.para['rough_mode'])
def name_md5_generate(self): if not self.debug_mode: self.program_info[ 'save_name'] = BasicFunctions_szz.name_generator_md5( self.program_info['path_save'], self.program_info['program_name'], self.para)