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)
