def _init_node_parm(self, key):
"""
Init parameter from workflow_data_frame
:return:
"""
wf_net_conf = WorkFlowNetConfWdnn(key)
self.wf_state_id = wf_net_conf.get_state_id(key).pk
netconfig = wf_net_conf.get_view_obj(key)
self.model_path = wf_net_conf.model_path
self.hidden_layers = wf_net_conf.hidden_layers
self.activation_function = wf_net_conf.activation_function
self.batch_size = wf_net_conf.batch_size
self.epoch = wf_net_conf.epoch
self.model_type = wf_net_conf.model_type
#Todo 어떻게 꺼내는지 승우씨한테 물어볼것
_wf_data_conf = wf_data_conf(key.split('_')[0]+'_'+key.split('_')[1]+'_'+'dataconf_node')
self.data_conf = _wf_data_conf.conf
self.label = _wf_data_conf.label
self.cell_feature = _wf_data_conf.cell_feature
self.cross_cell = _wf_data_conf.cross_cell
self.extend_cell_feature = _wf_data_conf.extend_cell_feature
self.label_values = _wf_data_conf.label_values
if 'test' in self.get_prev_node()[0].node_name:
_wf_data_node = wf_data_node(key.split('_')[0] + '_' + key.split('_')[1] + '_' + 'data_node')
self.multi_read_flag = _wf_data_node.multi_node_flag
else:
_wf_data_node = wf_data_node(key.split('_')[0] + '_' + key.split('_')[1] + '_' + 'data_node')
self.multi_read_flag = _wf_data_node.multi_node_flag
def _init_node_parm(self, key):
"""
Init parameter from workflow_data_frame
:return:
"""
wf_net_conf = WorkFlowNetConfWdnn(key)
self.wf_state_id = wf_net_conf.get_state_id(key).pk
netconfig = wf_net_conf.get_view_obj(key)
self.model_path = wf_net_conf.model_path
self.hidden_layers = wf_net_conf.hidden_layers
self.activation_function = wf_net_conf.activation_function
self.batch_size = wf_net_conf.batch_size
self.epoch = wf_net_conf.epoch
self.model_type = wf_net_conf.model_type
#Todo 어떻게 꺼내는지 승우씨한테 물어볼것
_wf_data_conf = wf_data_conf(
key.split('_')[0] + '_' + key.split('_')[1] + '_' +
'dataconf_node')
self.data_conf = _wf_data_conf.conf
self.label = _wf_data_conf.label
self.cell_feature = _wf_data_conf.cell_feature
self.cross_cell = _wf_data_conf.cross_cell
self.extend_cell_feature = _wf_data_conf.extend_cell_feature
self.label_values = _wf_data_conf.label_values
if 'test' in self.get_prev_node()[0].node_name:
_wf_data_node = wf_data_node(
key.split('_')[0] + '_' + key.split('_')[1] + '_' +
'data_node')
self.multi_read_flag = _wf_data_node.multi_node_flag
else:
_wf_data_node = wf_data_node(
key.split('_')[0] + '_' + key.split('_')[1] + '_' +
'data_node')
self.multi_read_flag = _wf_data_node.multi_node_flag
def _init_node_parm(self, key):
"""
Init parameter from workflow_data_frame
:return:
"""
wf_net_conf = WorkFlowNetConfWdnn(key)
self.model_path = wf_net_conf.model_path
self.hidden_layers = wf_net_conf.hidden_layers
self.activation_function = wf_net_conf.activation_function
self.batch_size = wf_net_conf.batch_size
self.epoch = wf_net_conf.epoch
self.model_type = wf_net_conf.model_type
self.train = wf_net_conf.train
self.auto_demension = wf_net_conf.auto_demension
#Todo 어떻게 꺼내는지 승우씨한테 물어볼것
_wf_data_conf = wf_data_conf(
key.split('_')[0] + '_' + key.split('_')[1] + '_' +
'dataconf_node')
self.data_conf = _wf_data_conf.conf
self.label = _wf_data_conf.label
self.cell_feature = _wf_data_conf.cell_feature
self.cross_cell = _wf_data_conf.cross_cell
self.extend_cell_feature = _wf_data_conf.extend_cell_feature
self.label_values = _wf_data_conf.label_values
_wf_data_node = wf_data_node(
key.split('_')[0] + '_' + key.split('_')[1] + '_' + 'data_node')
self.multi_read_flag = _wf_data_node.multi_node_flag
self.predict_path = _wf_data_node.predict_path
def _init_node_parm(self, key):
"""
Init parameter from workflow_data_frame
:return:
"""
#key = conf_data.
wf_net_conf = WorkFlowNetConfWdnn(key)
#self.model_path = utils.get_model_path(nnid, ver, netconf_node)
self.model_path = wf_net_conf.model_path
self.hidden_layers = wf_net_conf.hidden_layers
self.activation_function = wf_net_conf.activation_function
self.batch_size = wf_net_conf.batch_size
self.epoch = wf_net_conf.epoch
self.model_type = wf_net_conf.model_type
self.train = wf_net_conf.train
self.auto_demension = wf_net_conf.auto_demension
self.optimizer_type = wf_net_conf.optimizer_type
self.learning_rates = wf_net_conf.learning_rates
#Todo 어떻게 꺼내는지 승우씨한테 물어볼것
_wf_data_conf = wf_data_conf(key.split('_')[0]+'_'+key.split('_')[1]+'_'+'dataconf_node')
self.data_conf = _wf_data_conf.conf
self.label = _wf_data_conf.label
self.cell_feature = _wf_data_conf.cell_feature
self.cross_cell = _wf_data_conf.cross_cell
self.extend_cell_feature = _wf_data_conf.extend_cell_feature
self.label_values = _wf_data_conf.label_values
_wf_data_node = wf_data_node(key.split('_')[0] + '_' + key.split('_')[1] + '_' + 'data_node')
self.multi_read_flag = _wf_data_node.multi_node_flag
self.predict_path = _wf_data_node.predict_path
def _init_node_parm(self, key):
"""
Init parameter from workflow_data_frame
:return:
"""
wf_net_conf = WorkFlowNetConfML(key)
self.model_path = wf_net_conf.model_path
self.ml_class = wf_net_conf.ml_class
self.config = wf_net_conf.config
self.batch_size = 10000
self.model_type = wf_net_conf.model_type
#Todo 어떻게 꺼내는지 승우씨한테 물어볼것
_wf_data_conf = wf_data_conf(
key.split('_')[0] + '_' + key.split('_')[1] + '_' +
'dataconf_node')
self.data_conf = _wf_data_conf.conf
self.label = _wf_data_conf.label
self.cell_feature = _wf_data_conf.cell_feature
self.cross_cell = _wf_data_conf.cross_cell
self.extend_cell_feature = _wf_data_conf.extend_cell_feature
self.label_values = _wf_data_conf.label_values
_wf_data_node = wf_data_node(
key.split('_')[0] + '_' + key.split('_')[1] + '_' + 'data_node')
self.multi_read_flag = _wf_data_node.multi_node_flag
self.predict_path = _wf_data_node.predict_path
def _init_node_parm(self, key):
"""
Init parameter from workflow_data_frame
:return:
"""
wf_net_conf = WorkFlowNetConfML(key)
self.model_path = wf_net_conf.model_path
self.ml_class = wf_net_conf.ml_class
self.config = wf_net_conf.config
self.batch_size = 10000
self.model_type = wf_net_conf.model_type
#Todo 어떻게 꺼내는지 승우씨한테 물어볼것
_wf_data_conf = wf_data_conf(key.split('_')[0]+'_'+key.split('_')[1]+'_'+'dataconf_node')
self.data_conf = _wf_data_conf.conf
self.label = _wf_data_conf.label
self.cell_feature = _wf_data_conf.cell_feature
self.cross_cell = _wf_data_conf.cross_cell
self.extend_cell_feature = _wf_data_conf.extend_cell_feature
self.label_values = _wf_data_conf.label_values
_wf_data_node = wf_data_node(key.split('_')[0] + '_' + key.split('_')[1] + '_' + 'data_node')
self.multi_read_flag = _wf_data_node.multi_node_flag
self.predict_path = _wf_data_node.predict_path