def __init__(self, op, load_dic):
ConvNet.__init__(self, op, load_dic)
self.summary_dir = self.save_file + '_summary'
if not os.path.exists(self.summary_dir):
os.makedirs(self.summary_dir)
''' here, (train,test,pred) corresponds to (train,validation,testing)'''
self.write_features = [self.write_features_train, self.write_features_test, self.write_features_pred]
def __init__(self, op, load_dic):
ConvNet.__init__(self, op, load_dic)
self.summary_dir = self.save_file + '_summary'
if not os.path.exists(self.summary_dir):
os.makedirs(self.summary_dir)
''' here, (train,test,pred) corresponds to (train,validation,testing)'''
self.write_features = [
self.write_features_train, self.write_features_test,
self.write_features_pred
]
def __init__(self, model_path, data_processor, gpu, layers):
op = ConvNetPredict.get_options_parser()
op.set_value('load_file', model_path)
op.set_value('gpu', str(gpu))
load_dic = IGPUModel.load_checkpoint(model_path)
old_op = load_dic["op"]
old_op.merge_from(op)
op = old_op
op.eval_expr_defaults()
ConvNet.__init__(self, op, load_dic)
self.dp = data_processor
self.ftr_layer_idx = map(self.get_layer_idx, layers)
def __init__(self, op, load_dic):
ConvNet.__init__(self, op, load_dic)
def __init__(self, op, load_dic):
ConvNet.__init__(self, op, load_dic)
self.op.set_value('data_path', '/home/komet/software/cuda-convnet/data/cifar-10-py-colmajor')
def __init__(self, op, load_dic):
ConvNet.__init__(self, op, load_dic)
self.op.set_value(
'data_path',
'/home/komet/software/cuda-convnet/data/cifar-10-py-colmajor')
def __init__(self, op, load_dict):
ConvNet.__init__(self, op, load_dic)
self.statistics = dict()
self.temp_data = dict()
def __init__(self, op, load_dic, dp_params):
ConvNet.__init__(self, op, load_dic, dp_params)
def __init__(self, op, load_dict):
ConvNet.__init__(self, op, load_dic)
self.statistics = dict()
self.temp_data = dict()
self.cropper_dict = {'faceubd': IFaceUbdCropImage}
def __init__(self, op, load_dic):
ConvNet.__init__(self, op, load_dic)
print self.save_figure
def __init__(self, op, load_dict):
ConvNet.__init__(self, op, load_dic)
self.statistics = dict()
self.temp_data = dict()
def __init__(self, op, load_dic):
ConvNet.__init__(self, op, load_dic)
print self.save_figure
def __init__(self, op, load_dic, dp_params={}):
filename_options = []
self.regular_test_outputs = []
ConvNet.__init__(self, op, load_dic, dp_params=dp_params)
self.model_state['regular_test_outputs'] = self.regular_test_outputs
def __init__(self, op, load_dict):
ConvNet.__init__(self, op, load_dic)
self.statistics = dict()
self.temp_data = dict()
self.cropper_dict = {'faceubd':IFaceUbdCropImage}
