关于bind一个csv格式的数据提交任务后报错

[ShaoYULi12]

您好 bind table和upload table在使用上有什么不同吗？ 我通过v1/table/bind这个接口绑定了一个csv格式的文件 然后通过

dsl:

{
    "components":{
        "featurescale_2":{
            "output":{
                "data":[
                    "data"
                ],
                "model":[
                    "model"
                ]
            },
            "input":{
                "data":{
                    "data":[
                        "datatransform_1.data"
                    ]
                }
            },
            "module":"FeatureScale"
        },
        "reader_0":{
            "output":{
                "data":[
                    "data"
                ]
            },
            "input":{},
            "module":"Reader"
        },
        "datatransform_1":{
            "output":{
                "data":[
                    "data"
                ],
                "model":[
                    "model"
                ]
            },
            "input":{
                "data":{
                    "data":[
                        "reader_0.data"
                    ]
                }
            },
            "module":"DataTransform"
        },
        "homolr_3":{
            "output":{
                "data":[
                    "data"
                ],
                "model":[
                    "model"
                ]
            },
            "input":{
                "data":{
                    "train_data":[
                        "featurescale_2.data"
                    ]
                }
            },
            "module":"HomoLR"
        }
    }
}

conf:

{
        "dsl_version": 2,
        "initiator": {
            "role": "guest",
            "party_id": "10000"
        },
        "role": {
            "guest": [
                "10000"
            ],
            "arbiter": [
                "10000"
            ],
            "host": [
                "9999"
            ]
        },
        "component_parameters": {
            "common": {
                "datatransform_1": {
                    "with_label": true,
                    "output_format": "dense"
                },
                "featurescale_2": {
                    "method": "min_max_scale"
                },
                "homolr_3": {
                    "alpha": 0.01,
                    "optimizer": "sgd",
                    "batch_size": 320,
                    "learning_rate": 0.15,
                    "max_iter": 3,
                    "decay": 1.0,
                    "decay_sqrt": true
                }
            },
            "role": {
                "guest": {
                    "0": {
                        "reader_0": {
                            "table": {
                                "name": "breast_homo_guest",
                                "namespace": "experiment"
                            }
                        }
                    }
                },
                "host": {
                    "0": {
                        "reader_0": {
                            "table": {
                                "name": "breast_homo_host",
                                "namespace": "experiment"
                            }
                        }
                    }
                }
            }
        }
    }

提交训练任务 但是在datatransform模块报错：

[ERROR] [2024-04-17 14:13:28,198] [202404171401157397360] [28618:139967649003264] - [job_saver.update_task] [line:93]: role host party id 9999 task 202404171401157397360_datatransform_1 error report: Traceback (most recent call last):
  File "xxx/fate_flow/worker/task_executor.py", line 210, in _run_
    cpn_output = run_object.run(cpn_input)
  File "xxx/federatedml/model_base.py", line 239, in run
    self._run(cpn_input=cpn_input)
  File "xxx/federatedml/model_base.py", line 315, in _run
    this_data_output = func(*real_param)
  File "xxx/federatedml/util/data_transform.py", line 1052, in fit
    data_inst = self.transformer.read_data(data, "fit")
  File "xxx/federatedml/util/data_transform.py", line 137, in read_data
    abnormal_detection.empty_table_detection(input_data)
  File "xxx/federatedml/util/abnormal_detection.py", line 29, in empty_table_detection
    raise ValueError(f"Count of data_instance is 0: {data_instances}")
ValueError: Count of data_instance is 0: <fate_arch.computing.non_distributed.LocalData object at 0x7f9ddc04de20>

这种csv的数据是必须要通过upload的方式才可以在联邦学习里使用吗

[mgqa34]

bind绑定一个本地路径，是用的时候透传这个路径给到相应的算法组件，需要算法组件本身可以处理这种情况，当前应该只有homo_nn可以 upload是将本地数据转化成分布式的表，fate的所有算法组件都支持这个模式