def set_exp_run_conf(value): r"""Set experimental configuration for job Args: value ([type]): [description] """ assert type(func_desc, value) is dict pb_util.PythonDict2PbMessage(value, func_desc.job_config_proto.exp_run_conf)
def set_indexed_slices_optimizer_conf(func_desc, value): r"""Set indexed slices configuration of optimizer Args: func_desc ([type]): [description] value ([type]): [description] """ assert type(value) is dict pb_msg = func_desc.job_config_proto.indexed_slices_optimizer_conf pb_util.PythonDict2PbMessage(value, pb_msg)
def set_default_initializer_conf(func_desc, value): r"""Set default initial configuration for job Args: func_desc ([type]): [description] value ([type]): [description] """ assert type(value) is dict pb_util.PythonDict2PbMessage( value, func_desc.job_config_proto.default_initializer_conf)
def set_model_update_conf(func_desc, value): r"""Set up optimizer and update method of learning rate for job Args: func_desc ([type]): [description] value ([type]): [description] """ print( """WARNING: func_config.train.* has been deprecated. Please replace it by the new optimizer api. """) print(traceback.format_stack()[-3]) assert type(value) is dict pb_msg = func_desc.job_config_proto.train_conf.model_update_conf pb_util.PythonDict2PbMessage(value, pb_msg)