| Package | Description |
|---|---|
| com.tencentcloudapi.tione.v20211111.models |
| Modifier and Type | Method and Description |
|---|---|
Filter[] |
DescribeTrainingModelsRequest.getFilters()
Get 过滤器
Filter.Name: 枚举值:
keyword (模型名称)
TrainingModelId (模型ID)
ModelVersionType (模型版本类型) 其值Filter.Values支持: NORMAL(通用) ACCELERATE (加速)
TrainingModelSource (模型来源) 其值Filter.Values支持: JOB/COS/AUTO_ML
AlgorithmFramework (算法框架) 其值Filter.Values支持:TENSORFLOW/PYTORCH/DETECTRON2
ModelFormat(模型格式)其值Filter.Values支持:
TORCH_SCRIPT/PYTORCH/DETECTRON2/SAVED_MODEL/FROZEN_GRAPH/PMML
Filter.Values: 当长度为1时,支持模糊查询; 不为1时,精确查询
每次请求的Filters的上限为10,Filter.Values的上限为100
Filter.Fuzzy取值:true/false,是否支持模糊匹配
|
Filter[] |
DescribeDatasetsRequest.getFilters()
Get 数据集查询过滤条件,多个Filter之间的关系为逻辑与(AND)关系,过滤字段Filter.Name,类型为String
DatasetName,数据集名称
DatasetScope,数据集范围,SCOPE_DATASET_PRIVATE或SCOPE_DATASET_PUBLIC
|
Filter[] |
DescribeTrainingModelVersionsRequest.getFilters()
Get 过滤条件
Filter.Name: 枚举值:
TrainingModelVersionId (模型版本ID)
ModelVersionType (模型版本类型) 其值支持: NORMAL(通用) ACCELERATE (加速)
ModelFormat(模型格式)其值Filter.Values支持:
TORCH_SCRIPT/PYTORCH/DETECTRON2/SAVED_MODEL/FROZEN_GRAPH/PMML
AlgorithmFramework (算法框架) 其值Filter.Values支持:TENSORFLOW/PYTORCH/DETECTRON2
Filter.Values: 当长度为1时,支持模糊查询; 不为1时,精确查询
每次请求的Filters的上限为10,Filter.Values的上限为100
|
Filter[] |
DescribeLogsRequest.getFilters()
Get 过滤条件
注意:
1.
|
Filter[] |
DescribeTrainingTasksRequest.getFilters()
Get 过滤器,eg:[{ "Name": "Id", "Values": ["train-23091792777383936"] }]
取值范围:
Name(名称):task1
Id(task ID):train-23091792777383936
Status(状态):STARTING / RUNNING / STOPPING / STOPPED / FAILED / SUCCEED / SUBMIT_FAILED
ChargeType(计费类型):PREPAID(预付费)/ POSTPAID_BY_HOUR(后付费)
CHARGE_STATUS(计费状态):NOT_BILLING(未开始计费)/ BILLING(计费中)/ ARREARS_STOP(欠费停止)
|
Filter[] |
DescribeBillingResourceGroupsRequest.getFilters()
Get Filter.Name: 枚举值: ResourceGroupId (资源组id列表)
ResourceGroupName (资源组名称列表)
Filter.Values: 长度为1且Filter.Fuzzy=true时,支持模糊查询; 不为1时,精确查询
每次请求的Filters的上限为5,Filter.Values的上限为100
|
| Modifier and Type | Method and Description |
|---|---|
void |
DescribeTrainingModelsRequest.setFilters(Filter[] Filters)
Set 过滤器
Filter.Name: 枚举值:
keyword (模型名称)
TrainingModelId (模型ID)
ModelVersionType (模型版本类型) 其值Filter.Values支持: NORMAL(通用) ACCELERATE (加速)
TrainingModelSource (模型来源) 其值Filter.Values支持: JOB/COS/AUTO_ML
AlgorithmFramework (算法框架) 其值Filter.Values支持:TENSORFLOW/PYTORCH/DETECTRON2
ModelFormat(模型格式)其值Filter.Values支持:
TORCH_SCRIPT/PYTORCH/DETECTRON2/SAVED_MODEL/FROZEN_GRAPH/PMML
Filter.Values: 当长度为1时,支持模糊查询; 不为1时,精确查询
每次请求的Filters的上限为10,Filter.Values的上限为100
Filter.Fuzzy取值:true/false,是否支持模糊匹配
|
void |
DescribeDatasetsRequest.setFilters(Filter[] Filters)
Set 数据集查询过滤条件,多个Filter之间的关系为逻辑与(AND)关系,过滤字段Filter.Name,类型为String
DatasetName,数据集名称
DatasetScope,数据集范围,SCOPE_DATASET_PRIVATE或SCOPE_DATASET_PUBLIC
|
void |
DescribeTrainingModelVersionsRequest.setFilters(Filter[] Filters)
Set 过滤条件
Filter.Name: 枚举值:
TrainingModelVersionId (模型版本ID)
ModelVersionType (模型版本类型) 其值支持: NORMAL(通用) ACCELERATE (加速)
ModelFormat(模型格式)其值Filter.Values支持:
TORCH_SCRIPT/PYTORCH/DETECTRON2/SAVED_MODEL/FROZEN_GRAPH/PMML
AlgorithmFramework (算法框架) 其值Filter.Values支持:TENSORFLOW/PYTORCH/DETECTRON2
Filter.Values: 当长度为1时,支持模糊查询; 不为1时,精确查询
每次请求的Filters的上限为10,Filter.Values的上限为100
|
void |
DescribeLogsRequest.setFilters(Filter[] Filters)
Set 过滤条件
注意:
1.
|
void |
DescribeTrainingTasksRequest.setFilters(Filter[] Filters)
Set 过滤器,eg:[{ "Name": "Id", "Values": ["train-23091792777383936"] }]
取值范围:
Name(名称):task1
Id(task ID):train-23091792777383936
Status(状态):STARTING / RUNNING / STOPPING / STOPPED / FAILED / SUCCEED / SUBMIT_FAILED
ChargeType(计费类型):PREPAID(预付费)/ POSTPAID_BY_HOUR(后付费)
CHARGE_STATUS(计费状态):NOT_BILLING(未开始计费)/ BILLING(计费中)/ ARREARS_STOP(欠费停止)
|
void |
DescribeBillingResourceGroupsRequest.setFilters(Filter[] Filters)
Set Filter.Name: 枚举值: ResourceGroupId (资源组id列表)
ResourceGroupName (资源组名称列表)
Filter.Values: 长度为1且Filter.Fuzzy=true时,支持模糊查询; 不为1时,精确查询
每次请求的Filters的上限为5,Filter.Values的上限为100
|
| Constructor and Description |
|---|
Filter(Filter source)
NOTE: Any ambiguous key set via .set("AnyKey", "value") will be a shallow copy,
and any explicit key, i.e Foo, set via .setFoo("value") will be a deep copy.
|
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