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‎.gitignore‎

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# Created by .ignore support plugin (hsz.mobi)
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### Go template
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# Binaries for programs and plugins
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*.exe
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*.exe~
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*.dll
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*.so
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*.dylib
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# Test binary, build with `go test -c`
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*.test
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# Output of the go coverage tool, specifically when used with LiteIDE
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*.out
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### Example user template template
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### Example user template
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# IntelliJ project files
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.idea
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# VsCode project files
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.vscode/*
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*.log
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*.zip
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log/*
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*.swp
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*.swo
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venv
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pandas
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site

‎README.md‎

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# 依赖
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python3.9
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# 安装/升级
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待正式对外发布
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# 配置
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1. 鉴权通过OAuth2.0, 所以这里要先申请用户的`appid`、`api_key`、`secret_key`
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2. 配置方式一：直接通过制定参数的方式实例化api_client， 参考快速开始部分
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3. 配置方式二: yaml配置文件， 配置的默认路径为`~./.config/deepwisdom/dwconfig.yaml`, 配置内容如下
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```yaml
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api_key: "xx"
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secret_key: "xxx"
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appid: 3
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domain: "xxx"
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```
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# 快速开始
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以表格二分类为例
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```python
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import deepwisdom as dw
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if __name__ == "__main__":
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api_client = dw.Client(appid="your appid", api_key="your api key", secret_key="your secret key")
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dw.set_client(client=api_client)
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train_dataset = dw.Dataset.create(file_path="path to train", stage="train")
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automl = dw.AutoML.create(dataset=train_dataset, name="sdk-demo", label_col="k", time_col="g")
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automl.train()
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test_dataset = dw.Dataset.create(file_path="path to test", stage="test")
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eval_res = automl.evaluate(test_dataset)
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service = dw.Deployment.create(project=automl, name="sdk-demo")
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ret = service.call_service()
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```
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# 特性
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1. 数据集管理。 包括数据集的增删改查、数据集模糊搜索等
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2. 项目管理。 项目的增删改查、训练管理、离线预测、高级设置更新、方案/部署模型列表等
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3. 实验管理。 实验详情数据查询，包括耗时、性能和效果指标等
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4. 最佳方案。 实验的方案列表及对应的部署模型信息等
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5. 离线预测。 获取离线预测列表，进行离线预测等
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6. 推理部署。推理服务创建，获取列表，修改常驻状态，修改推理服务名称，调用服务等
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# 详细文档
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1. API Reference。
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2. tutorials
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‎deepwisdom/__init__.py‎

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# flake8: noqa
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from ._version import __version__
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from .client import Client, set_client
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from .errors import AppPlatformError
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from .models import (
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Dataset,
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OfflinePrediction,
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Deployment,
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Project,
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AdvanceSetting,
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TrainSetting,
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SearchSpace,
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CreateDeploymentRequest
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)
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from .models import Project as AutoML

‎deepwisdom/_compat.py‎

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"""
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This module contains compatibility fixes to allow usage of both 1.x and 2.x Trafaret versions
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"""
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try:
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from trafaret import ToInt as Int
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except ImportError:
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from trafaret import Int # noqa
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try:
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from trafaret import AnyString as String
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except ImportError:
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from trafaret import String # noqa
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try:
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from trafaret import Any as Any
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except ImportError:
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from trafaret import Any

‎deepwisdom/_version.py‎

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__version__ = "0.2.4"

‎deepwisdom/client.py‎

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import os
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import yaml
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from ._version import __version__
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from .rest import DeepWisdomClientConfig, RESTClientObject
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from deepwisdom.enums import API_DOMAIN
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__all__ = ("Client", "get_client", "set_client")
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_global_client = None
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def Client(
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api_key=None,
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secret_key=None,
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appid=None,
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domain=None,
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admin_domain=API_DOMAIN.ADMIN
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):
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"""
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api请求客户端
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Args:
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admin_domain (str):
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api_key:
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secret_key:
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appid:
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domain:
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Returns:
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"""
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global _global_client
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if api_key and appid and secret_key:
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dwconfig = DeepWisdomClientConfig(
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appid=appid,
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api_key=api_key,
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secret_key=secret_key,
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domain=domain,
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admin_domain=admin_domain
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)
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else:
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config_path = _get_default_config_file()
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if config_path is None:
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raise ValueError("Config No Found.")
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dwconfig = _config_from_file(config_path)
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if dwconfig.domain is None:
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dwconfig.domain = API_DOMAIN.API
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_global_client = RESTClientObject.from_config(dwconfig)
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return _global_client
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def _get_client_version():
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return __version__
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def get_client():
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return _global_client or Client()
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class staticproperty(property):
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def __get__(self, instance, owner):
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return self.fget()
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def set_client(client):
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"""
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Set the global HTTP client for sdk.
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Returns previous client.
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"""
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global _global_client
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previous = _global_client
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_global_client = client
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return previous
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def _get_config_dir():
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return os.path.expanduser(os.path.join("~", ".config", "deepwisdom"))
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def _get_default_config_file():
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first_choice_config_path = os.path.join(_get_config_dir(), "dwconfig.yaml")
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if _file_exists(first_choice_config_path):
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return first_choice_config_path
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else:
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return None
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_file_exists = os.path.isfile
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def _config_from_file(config_path):
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"""
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Create and return a DeepWisdomClientConfig from a config path. The file must be
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a yaml formatted file
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Parameters
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----------
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config_path : str
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Path to the configuration file
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Returns
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-------
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config : DeepWisdomClientConfig
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"""
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with open(config_path, "rb") as f:
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data = yaml.load(f, Loader=yaml.SafeLoader)
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return DeepWisdomClientConfig.from_data(data)
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‎deepwisdom/enums.py‎

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import json
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def enum(*vals, **enums):
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"""
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Enum without third party libs and compatible with py2 and py3 versions.
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"""
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enums.update(dict(zip(vals, vals)))
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return type("Enum", (), enums)
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PROJECT_DEFAULT_ADVANCE_SETTING = json.loads('{"search_space":[{"hp_subspace":"feature_engineering","hp_values":{"KeyTimeBinSecond":{"hp_type":"bool","hp_values":[true,false]},"KeyTimeBinMsecond":{"hp_type":"bool","hp_values":[true,false]},"KeyTimeWeekday":{"hp_type":"bool","hp_values":[true,false]},"KeyTimeHour":{"hp_type":"bool","hp_values":[true,false]},"KeyTimeDay":{"hp_type":"bool","hp_values":[true,false]},"KeyTimeMonth":{"hp_type":"bool","hp_values":[true,false]},"KeyTimeYear":{"hp_type":"bool","hp_values":[true,false]},"KeyNumDiff":{"hp_type":"bool","hp_values":[true,false]},"KeyTimeDiff_BW_Window_1":{"hp_type":"bool","hp_values":[true,false]},"KeyTimeDiff_FW_Window_10":{"hp_type":"bool","hp_values":[true,false]},"McCatRank":{"hp_type":"bool","hp_values":[true,false]},"McMcInnerLen":{"hp_type":"bool","hp_values":[true,false]},"GroupCntDivNunique":{"hp_type":"bool","hp_values":[true,false]},"CatCnt":{"hp_type":"bool","hp_values":[true,false]},"GroupMean":{"hp_type":"bool","hp_values":[true,false]},"GroupMax":{"hp_type":"bool","hp_values":[true,false]},"GroupMin":{"hp_type":"bool","hp_values":[true,false]},"GroupStd":{"hp_type":"bool","hp_values":[true,false]},"GroupMeanMinusSelf":{"hp_type":"bool","hp_values":[true,false]},"GroupMaxMinusSelf":{"hp_type":"bool","hp_values":[true,false]},"GroupMinMinusSelf":{"hp_type":"bool","hp_values":[true,false]},"CatSegCtrOrigin":{"hp_type":"bool","hp_values":[true,false]}}},{"hp_subspace":"modeling","hp_values":{"model":{"hp_type":"choice","hp_values":[{"hp_name":"LIGHTGBM","learning_rate":{"hp_type":"loguniform","hp_values":[0.005,0.2]},"feature_fraction":{"hp_type":"uniform","hp_values":[0.75,1]},"min_data_in_leaf":{"hp_type":"randint","hp_values":[2,30]},"num_leaves":{"hp_type":"randint","hp_values":[16,96]}},{"hp_name":"RANDOMFOREST","n_estimators":{"hp_type":"randint","hp_values":[30,200]},"max_features":{"hp_type":"uniform","hp_values":[0,0.5]}},{"hp_name":"GBTREE","learning_rate":{"hp_type":"loguniform","hp_values":[0.01,1]},"n_estimators":{"hp_type":"randint","hp_values":[30,200]},"subsample":{"hp_type":"uniform","hp_values":[0.5,1]}},{"hp_name":"CATBOOST","depth":{"hp_type":"randint","hp_values":[5,8]},"l2_leaf_reg":{"hp_type":"uniform","hp_values":[1,5]}},{"hp_name":"LOGISTIC_REGRESSION","C":{"hp_type":"loguniform","hp_values":[0.1,10]},"fit_intercept":{"hp_type":"choice","hp_values":[true,false]}},{"hp_name":"RIDGE","alpha":{"hp_type":"uniform","hp_values":[0.1,5]}},{"hp_name":"DECISIONTREE","max_features":{"hp_type":"uniform","hp_values":[0.3,1]},"max_depth":{"hp_type":"randint","hp_values":[3,9]}},{"hp_name":"TABNET","max_epochs":{"hp_type":"randint","hp_values":[3,20]},"gamma":{"hp_type":"uniform","hp_values":[1.1,1.5]}}]}}}],"target_train":{"train_data_ratio":80,"training_program":"指标优先","call_limit":[5,20],"instance_num":2,"call_delay":50,"gpu_mem":0,"memory_limit":20,"program_num":5,"max_trials":30,"trial_concurrency":3,"random_seed":1647}}')
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DEFAULT_DOMAIN = ""
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DEFAULT_ADMIN_DOMAIN = ""
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# default time out values in seconds for waiting response from client
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DEFAULT_TIMEOUT = enum(
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CONNECT=6.05, # time in seconds for the connection to server to be established
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SOCKET=60,
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READ=60, # time in seconds after which to conclude the server isn't responding anymore
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UPLOAD=600, # time in seconds after which to conclude that project dataset cannot be uploaded
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)
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API_DOMAIN = enum(
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ACCESS_TOKEN="",
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API="",
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ADMIN=""
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)
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SVR_STATUS = enum(
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CREATE=1,
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SCHEDULE=2,
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SCHEDULE_SUCC=3,
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RUNNING=4,
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FAIL=5,
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HANDUP=6,
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CANCEL=7,
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DELETING=8,
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DELETED=9,
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)
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MODAL_TYPE = enum(
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CSV=0,
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VIDEO=1,
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IMAGE=2,
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SPEECH=3,
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TEXT=4
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)
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# 0二分类/分类,1多分类/检测/意图识别/匹配,2回归/定位/语音分离/序列,3时序/分隔
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TASK_TYPE = enum(
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)
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API_URL = enum(
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AUTH="appmng/token",
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DATASET_PREPARE="sdk/datasetprepare",
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FILE_UPLOAD="sdk/fileupload",
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DATASET_UPLOAD="sdk/datasetupload",
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DATASET_QUERY="sdksvr/querydataset", # 获取数据集id和状态
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DATASET_INFO="sdk/datasetinfo",
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DATASET_DELETE="sdk/datasetdelete", # 数据集删除 /datawarehouse/datasets DELETE
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DATASET_LIST="sdk/datasetlist", # 数据集搜索 /datawarehouse/datasets GET
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DATASET_MODIFY="sdk/datasetmodify", # 数据集修改 /datawarehouse/dataset Patch
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DATASET_SUMMIT="sdk/connectionsummit", # 从数据源导入生成数据集 /connection/submit POST
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DATASET_EDA="sdk/dataseteda", # 获取数据集的EDA /dataset/eda GET PATCH
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PROJECT_CREATE="sdk/createproj",
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PROJECT_DELETE="sdk/deleteproj", # 批量删除项目 /projects DELETE
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PROJECT_ADVANCESETTING_UPDATE="sdk/projsetting", # 高级设置修改 /project/advance_settings PATCH
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PROJECT_TRAIN="sdk/projtrain",
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PROJECT_TERMINATE_TRAIN="sdk/terminatetrain", # 终止训练 /project/terminate/train
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PROJECT_INFO="sdk/projinfo",
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PROJECT_DATASET_LIST="sdk/projdatasets", # 项目下的数据集列表 /project/dataset
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PROJECT_TRAIN_RESULT="/sdk/trainresult",
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PROJECT_EFFECT="sdk/projeffect", #迭代效果，实验列表： /project/iterative/effect
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PROJECT_SCHEME="sdk/projscheme", #有最终方案的实验/solution： /project/trial/scheme
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PROJECT_MODEL_LIST="sdk/modellist", #项目的模型列表：/project/models
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PROJECT_MODEL="sdk/model", #模型详情： /project/model
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PROJECT_MODEL_SELECT="sdk/modelselect", #需要部署的模型信息： /project/model/select
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PROJECT_MODEL_SS="/basic/searchspace/modal/task/ss", #搜索空间详情： 请求admin /basic/searchspace/modal/task/ss
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MODEL_DOWNLOAD="sdk/modeldownload", #模型文件下载： /project/model/download
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DATASET_PREDICT_UPLOAD="sdk/predictupload", #离线预测数据集上传： /predict/dataset/upload
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DATASET_PREDICT_LIST="sdk/predictlist", # 离线预测数据集列表 /predict/datasets
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PREDICTION_DETAIL="sdk/projeval/detail",
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PREDICTION_PREDICT="sdk/projeval/predict",
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PREDICTION_LIST="sdk/projeval/list",
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PREDICTION_DELETE="sdk/projeval/delete",
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PREDICTION_DATASET_DOWNLOAD="sdk/projeval/dataset_download",
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PREDICTION_RESULT_DOWNLOAD="sdk/projeval/result_download",
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DEPLOY_CREATE_SERVICE='sdk/deploy/create',
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DEPLOY_GET_SERVICE_DETAIL='sdk/deploy/detail',
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DEPLOY_LIST_DEPLOYMENTS='sdk/deploy/list',
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DEPLOY_RESIDENT_DEPLOYMENT='sdk/deploy/resident', # 推理服务常驻
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DEPLOY_RENAME_DEPLOYMENT='sdk/deploy/rename',
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DEPLOY_DELETE_DEPLOYMENT='sdk/deploy/delete',
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DEPLOY_GET_DEPLOYMENT_LOG='sdk/deploy/logs',
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DEPLOY_GET_SERVICE_API='sdk/deploy/get_api',
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# DATASET_DOWNLOAD_HOST="http://192.168.50.24:5000/proxy/static/"
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)
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