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)