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.PythonDict2CFG(value, func_desc.job_config_proto.mutable_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.mutable_indexed_slices_optimizer_conf() pb_util.PythonDict2CFG(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.PythonDict2CFG( value, func_desc.job_config_proto.mutable_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.mutable_train_conf().mutable_model_update_conf() pb_util.PythonDict2CFG(value, pb_msg)