def api_gpu_device_num(val: int) -> None: """Set number of GPUs on each machine to run oneflow on. Args: val (int): number of GPUs. It is identical on every machine. In other words, you can't specify different number of GPUs you would like to use on each machine. """ if oneflow._oneflow_internal.flags.with_cuda(): return enable_if.unique([gpu_device_num, do_nothing])(val) else: print( "INFO: for CPU-only OneFlow, oneflow.config.gpu_device_num is equivalent to oneflow.config.cpu_device_num" ) print(traceback.format_stack()[-2]) return enable_if.unique([cpu_device_num, do_nothing])(val)
def api_env_init() -> bool: """Init environment for job Returns: bool: [description] """ return enable_if.unique([env_init, do_nothing])()
def api_enable_eager_execution(val: bool = True) -> None: """If True, job will execute in eager mode, else use lazy mode(static graph). Args: val (bool, optional): Whether eager execution or not. Defaults to True. """ return enable_if.unique([enable_eager_environment])(val)
def api_logtostderr(val: int) -> None: """Set whether log messages go to stderr instead of logfiles Args: val (int): [description] """ return enable_if.unique([logtostderr, do_nothing])(val)
def api_log_dir(val: str) -> None: """Specify a dir to store OneFlow's logging files. If not specified, it is `./log` by default. Args: val (str): string , log file path """ return enable_if.unique([log_dir, do_nothing])(val)
def api_cpu_device_num(val: int) -> None: """Set number of CPUs on each machine to run oneflow on. Usually you don't need to set this. Args: val (int): number of CPUs. It is identical on every machine. """ return enable_if.unique([cpu_device_num, do_nothing])(val)
def api_enable_fusion(val: bool = True) -> None: """Whether or not allow fusion the operators Args: val (bool, optional): True or False. Defaults to True. """ return enable_if.unique([enable_fusion, do_nothing])(val=val)
def api_reserved_device_mem_mbyte(val: int) -> None: """Set up the memory size of reserved device Args: val (int): memory size, e.g. 1024(mb) """ return enable_if.unique([reserved_device_mem_mbyte, do_nothing])(val)
def api_compute_thread_pool_size(val: int) -> None: """Set up the size of compute thread pool Args: val (int): size of thread pool """ return enable_if.unique([compute_thread_pool_size, do_nothing])(val)
def api_enable_mem_chain_merge(val: bool = True) -> None: """Whether or not to enable MemChain merge. Args: val (bool, optional): True or False. Defaults to True. """ return enable_if.unique([enable_mem_chain_merge, do_nothing])(val=val)
def api_ctrl_port(val: int) -> None: """Set port number used to control the execution across multiple machines. Same on every machine. Args: val: a port number accessible to peer machines """ return enable_if.unique([ctrl_port, do_nothing])(val)
def api_enable_model_io_v2(val): """Whether or not use version2 of model input/output function. Args: val ([type]): True or False """ return enable_if.unique([enable_model_io_v2, do_nothing])(val)
def api_data_port(val: int) -> None: """Set port number used to data transfer among multiple machines. Same on every machine. Args: val: a port number accessible to peer machines """ return enable_if.unique([data_port, do_nothing])(val)
def api_enable_legacy_model_io(val: bool = True): """Whether or not use legacy model io. Args: val ([type]): True or False """ return enable_if.unique([enable_legacy_model_io, do_nothing])(val)
def api_nccl_num_streams(val: int) -> None: """Set up the number of nccl parallel streams while use boxing Args: val (int): number of streams """ return enable_if.unique([nccl_num_streams, do_nothing])(val)
def api_nccl_enable_mixed_fusion(val: bool) -> None: """Whether or not use nccl mixed fusion Args: val (bool): True or False """ return enable_if.unique([nccl_enable_mixed_fusion, do_nothing])(val)
def api_nccl_fusion_threshold_mb(val: int) -> None: """Set up threshold for oprators fusion Args: val (int): int number, e.g. 10(mb) """ return enable_if.unique([nccl_fusion_threshold_mb, do_nothing])(val)
def api_load_library_now(val: str) -> None: """Load necessary library for job now Args: val (str): path to shared object file """ return enable_if.unique([load_library_now, do_nothing])(val)
def api_nccl_enable_all_to_all(val: bool) -> None: """Whether or not use nccl all2all during s2s boxing Args: val (bool): True or False """ return enable_if.unique([nccl_enable_all_to_all, do_nothing])(val)
def api_nccl_fusion_broadcast(val: bool) -> None: """Whether or not use nccl fusion during broadcast progress Args: val (bool): True or False """ return enable_if.unique([nccl_fusion_broadcast, do_nothing])(val)
def api_nccl_fusion_max_ops(val: int) -> None: """Maximum number of ops for nccl fusion. Args: val (int): Maximum number of ops """ return enable_if.unique([nccl_fusion_max_ops, do_nothing])(val)
def api_enable_debug_mode(val: bool) -> None: """Whether use debug mode or not. Args: val (bool): True or False """ return enable_if.unique([enable_debug_mode, do_nothing])(val)
def api_nccl_fusion_all_gather(val: bool) -> None: """Whether or not use nccl fusion during all gather progress Args: val (bool): True or False """ return enable_if.unique([nccl_fusion_all_gather, do_nothing])(val)
def api_machine_num(val: int) -> None: """Set available number of machine/node for running job . Args: val (int): available number of machines """ return enable_if.unique([machine_num, do_nothing])(val)
def api_max_mdsave_worker_num(val: int) -> None: """Set up max number of workers for mdsave process. Args: val (int): max number of workers """ return enable_if.unique([max_mdsave_worker_num, do_nothing])(val)
def api_nccl_fusion_all_reduce_use_buffer(val: bool) -> None: """Whether or not use buffer during nccl fusion progress Args: val (bool): True or False """ return enable_if.unique([nccl_fusion_all_reduce_use_buffer, do_nothing])(val)
def api_enable_tensor_float_32_compute(val: bool = True) -> None: """Whether or not to enable Tensor-float-32 on supported GPUs Args: val (bool, optional): True or False. Defaults to True. """ return enable_if.unique([enable_tensor_float_32_compute, do_nothing])(val=val)
def api_num_callback_threads(val: int) -> None: """Set up number of callback threads for boxing process. Boxing is used to convert between different parallel properties of logical tensor Args: val (int): number of callback threads """ return enable_if.unique([num_callback_threads, do_nothing])(val)
def api_comm_net_worker_num(val: int) -> None: """Set up the workers number in epoll mode network, If use RDMA mode network, then doesn't need. Args: val (int): number of workers """ return enable_if.unique([comm_net_worker_num, do_nothing])(val)
def api_enable_cudnn_fused_normalization_add_relu(val: bool) -> None: """Whether enable cudnn_fused_normalization_add_relu. Args: val (bool): whether enable or not """ return enable_if.unique( [enable_cudnn_fused_normalization_add_relu, do_nothing])(val)