REST APIs for /platform/rest/deeplearning/v1

Access

Methods

[ Jump to Models ]

Table of Contents

Configuration

Datasets

ElasticDistributedInference

Execute

Frameworks

HyperSearch

Inferences

ModelTemplates

ModelTrainings

ModelTunings

ModelValidations

Models

Scheduler

Configuration

Up
get /conf
Retrieves all dlpd configuration parameters (getDeepLearningConf)
Returns all properties that are defined in $EGO_CONFDIR/../../dli/conf/dlpd/dlpd.conf.

Consumes

This API call consumes the following media types via the Content-Type request header:

Return type

StringMap

Example data

Content-Type: application/json
{
  "example_key" : "example_key"
}

Produces

This API call produces the following media types according to the Accept request header; the media type will be conveyed by the Content-Type response header.

Responses

200

Successful response that contains a dictionary of key-value string pairs that is defined in the dlpd.conf file. StringMap

401

Authentication error. The request was denied.

403

Forbidden. The request was denied.

500

An unexpected error occurred.

Datasets

Up
post /datasets
Creates a new deep learning dataset (addDataset)
A dataset can be created in the following ways - 1) Import the existing LMDB, TFRecords, or Other dataset; 2) Create a LMDB or TFRecords dataset from existing image files for image classification; 3) Import images for object detection; 4) Import a CVS dataset; 5) Import images for vector output; 6) Import plugin dataset including customized plugins and the ready-made NLP plugin; 7) Raw data.

Consumes

This API call consumes the following media types via the Content-Type request header:

Request body

datasetInfo DatasetCreateParam (required)
Body Parameter — The information that specifies the details to create a new dataset.

Produces

This API call produces the following media types according to the Accept request header; the media type will be conveyed by the Content-Type response header.

Responses

201

The deep learning dataset created successfully.

400

Bad request. The request was not formatted correctly.

401

Authentication error. The request was denied.

403

Forbidden. The request was denied.

500

An unexpected error occurred.

Up
get /datasets/{datasetname}/csvs
Retrieve required dataset CSV data (csvList)
Retrieve required dataset CSV data.

Path parameters

datasetname (required)
Path Parameter — The dataset name.

Consumes

This API call consumes the following media types via the Content-Type request header:

Query parameters

type (required)
Query Parameter — The type of CSV data to review, for example - validation, test or training.
start (optional)
Query Parameter — You can request a specific range of results by specifying the start index of the data and the length of the data.
length (optional)
Query Parameter — You can request a specific range of results by specifying the start index of the data and the length of the data.

Return type

csvDetail

Example data

Content-Type: application/json
{
  "data" : [ "", "" ],
  "columns" : [ "columns", "columns" ],
  "index" : [ "index", "index" ],
  "JSONString" : "JSONString"
}

Produces

This API call produces the following media types according to the Accept request header; the media type will be conveyed by the Content-Type response header.

Responses

200

Successful response that contains the subset of the CSV dataset either for training, testing or validation. csvDetail

400

Bad request. The request was not formatted correctly.

401

Authentication error. The request was denied.

403

Forbidden. The request was denied.

404

The requested resource was not found.

500

An unexpected error occurred.

Up
delete /datasets/{datasetname}
Deletes a deep learning dataset (deleteDatasetInfo)
Deletes a deep learning dataset.

Path parameters

datasetname (required)
Path Parameter — The deep learning dataset name.

Consumes

This API call consumes the following media types via the Content-Type request header:

Produces

This API call produces the following media types according to the Accept request header; the media type will be conveyed by the Content-Type response header.

Responses

200

Successfully deleted the deep learning dataset.

400

The request format is invalid.

401

Authentication error. The request was denied.

403

Forbidden. The request was denied.

404

The requested resource is not found.

409

Conflict. The requested resource cannot be deleted because it is in use.

500

An unexpected error occurred.

Up
get /datasets/{datasetname}
Retrieves a deep learning dataset by its name (getDatasetInfo)
Retrieves a deep learning dataset by its name.

Path parameters

datasetname (required)
Path Parameter — The deep learning dataset name.

Consumes

This API call consumes the following media types via the Content-Type request header:

Return type

DatasetDetail

Example data

Content-Type: application/json
{
  "testlabels" : [ "", "" ],
  "datasourcetype" : "LMDB",
  "byclass" : true,
  "signame" : "signame",
  "testpath" : "testpath",
  "meanfilepath" : "meanfilepath",
  "sigid" : "sigid",
  "dbbackend" : "LMDB",
  "runduration" : 0.8008281904610115,
  "valpath" : "valpath",
  "vallabels" : [ "", "" ],
  "shards" : 7,
  "submittedtime" : "submittedtime",
  "driverid" : "driverid",
  "size" : 2.3021358869347655,
  "plugin" : "plugin",
  "masterUrl" : "masterUrl",
  "imagedetail" : {
    "trainimagepath" : "trainimagepath",
    "testpercentage" : 5,
    "imagetype" : "imagetype",
    "testimagepath" : "testimagepath",
    "valtextpath" : "valtextpath",
    "valimagepath" : "valimagepath",
    "resizetransformation" : "resizetransformation",
    "valpercentage" : 5,
    "labeltextpath" : "labeltextpath",
    "testtextpath" : "testtextpath",
    "width" : 1,
    "isusingtext" : true,
    "traintextpath" : "traintextpath",
    "splitalgorithm" : "hold-out",
    "height" : 6
  },
  "sparkappid" : "sparkappid",
  "name" : "name",
  "trainpath" : "trainpath",
  "createUser" : "createUser",
  "trainlabels" : [ "", "" ],
  "status" : "status"
}

Produces

This API call produces the following media types according to the Accept request header; the media type will be conveyed by the Content-Type response header.

Responses

200

Successful response that contains the resulting deep learning dataset. DatasetDetail

400

Bad request. The request was not formatted correctly.

401

Authentication error. The request was denied.

403

Forbidden. The request was denied.

404

The requested resource was not found.

500

An unexpected error occurred.

Up
get /datasets
Retrieves all deep learning datasets (getFullDatasetDetails)
Returns full listing of all the datasets defined in the system.

Consumes

This API call consumes the following media types via the Content-Type request header:

Return type

array[DatasetDetail]

Example data

Content-Type: application/json
[ {
  "testlabels" : [ "", "" ],
  "datasourcetype" : "LMDB",
  "byclass" : true,
  "signame" : "signame",
  "testpath" : "testpath",
  "meanfilepath" : "meanfilepath",
  "sigid" : "sigid",
  "dbbackend" : "LMDB",
  "runduration" : 0.8008281904610115,
  "valpath" : "valpath",
  "vallabels" : [ "", "" ],
  "shards" : 7,
  "submittedtime" : "submittedtime",
  "driverid" : "driverid",
  "size" : 2.3021358869347655,
  "plugin" : "plugin",
  "masterUrl" : "masterUrl",
  "imagedetail" : {
    "trainimagepath" : "trainimagepath",
    "testpercentage" : 5,
    "imagetype" : "imagetype",
    "testimagepath" : "testimagepath",
    "valtextpath" : "valtextpath",
    "valimagepath" : "valimagepath",
    "resizetransformation" : "resizetransformation",
    "valpercentage" : 5,
    "labeltextpath" : "labeltextpath",
    "testtextpath" : "testtextpath",
    "width" : 1,
    "isusingtext" : true,
    "traintextpath" : "traintextpath",
    "splitalgorithm" : "hold-out",
    "height" : 6
  },
  "sparkappid" : "sparkappid",
  "name" : "name",
  "trainpath" : "trainpath",
  "createUser" : "createUser",
  "trainlabels" : [ "", "" ],
  "status" : "status"
}, {
  "testlabels" : [ "", "" ],
  "datasourcetype" : "LMDB",
  "byclass" : true,
  "signame" : "signame",
  "testpath" : "testpath",
  "meanfilepath" : "meanfilepath",
  "sigid" : "sigid",
  "dbbackend" : "LMDB",
  "runduration" : 0.8008281904610115,
  "valpath" : "valpath",
  "vallabels" : [ "", "" ],
  "shards" : 7,
  "submittedtime" : "submittedtime",
  "driverid" : "driverid",
  "size" : 2.3021358869347655,
  "plugin" : "plugin",
  "masterUrl" : "masterUrl",
  "imagedetail" : {
    "trainimagepath" : "trainimagepath",
    "testpercentage" : 5,
    "imagetype" : "imagetype",
    "testimagepath" : "testimagepath",
    "valtextpath" : "valtextpath",
    "valimagepath" : "valimagepath",
    "resizetransformation" : "resizetransformation",
    "valpercentage" : 5,
    "labeltextpath" : "labeltextpath",
    "testtextpath" : "testtextpath",
    "width" : 1,
    "isusingtext" : true,
    "traintextpath" : "traintextpath",
    "splitalgorithm" : "hold-out",
    "height" : 6
  },
  "sparkappid" : "sparkappid",
  "name" : "name",
  "trainpath" : "trainpath",
  "createUser" : "createUser",
  "trainlabels" : [ "", "" ],
  "status" : "status"
} ]

Produces

This API call produces the following media types according to the Accept request header; the media type will be conveyed by the Content-Type response header.

Responses

200

Successful response that contains the resulting deep learning datasets.

400

Bad request. The request was not formatted correctly.

401

Authentication error. The request was denied.

403

Forbidden. The request was denied.

500

An unexpected error occurred.

Up
get /datasets/{datasetname}/objectimages
Retrieves required object images (objectimageList)
Retrieves required object images.

Path parameters

datasetname (required)
Path Parameter — The dataset name.

Consumes

This API call consumes the following media types via the Content-Type request header:

Query parameters

type (required)
Query Parameter — The type of image data to review, for example - validation, test or training.
start (optional)
Query Parameter — You can request a specific range of results by specifying the start index of the data and the length of the data.
length (optional)
Query Parameter — You can request a specific range of results by specifying the start index of the data and the length of the data.

Return type

array[Pictures]

Example data

Content-Type: application/json
[ {
  "path" : "path",
  "name" : "name",
  "labels" : "labels"
}, {
  "path" : "path",
  "name" : "name",
  "labels" : "labels"
} ]

Produces

This API call produces the following media types according to the Accept request header; the media type will be conveyed by the Content-Type response header.

Responses

200

Successful response that contains the subset of the image dataset for training, testing or validation.

400

Bad request. The request was not formatted correctly.

401

Authentication error. The request was denied.

403

Forbidden. The request was denied.

404

The requested resource was not found.

500

An unexpected error occurred.

Up
put /datasets/{datasetname}/stop
Stops a dataset task (stopDataSet)
Stops a running dataset task.

Path parameters

datasetname (required)
Path Parameter — The dataset name.

Consumes

This API call consumes the following media types via the Content-Type request header:

Produces

This API call produces the following media types according to the Accept request header; the media type will be conveyed by the Content-Type response header.

Responses

200

Successfully stopped the running job.

400

Bad request. The request was not formatted correctly.

401

Authentication error. The request was denied.

403

Forbidden. The request was denied.

404

The requested resource was not found.

500

An unexpected error occurred.

ElasticDistributedInference

Up
delete /edimodels/{modelname}
Deletes an elastic distributed inference service (deleteEDIModel)
Deletes an elastic distributed inference service.

Path parameters

modelname (required)
Path Parameter — The elastic distributed inference model service.

Consumes

This API call consumes the following media types via the Content-Type request header:

Produces

This API call produces the following media types according to the Accept request header; the media type will be conveyed by the Content-Type response header.

Responses

200

Ok. Successfully deleted the elastic distributed inference service.

400

The request format is invalid.

401

Authentication error. The request was denied.

403

Forbidden. The request was denied.

404

The requested resource is not found.

409

Conflict. The requested resource cannot be deleted because it is in use.

500

An unexpected error occurred.

Up
post /edimodels/{modelname}/inference
Do inference using an elastic distributed inference service (doEDIInference)
Do inference using an elastic distributed inference service.

Path parameters

modelname (required)
Path Parameter — The elastic distributed inference service name.

Consumes

This API call consumes the following media types via the Content-Type request header:

Request body

IaSTestInputParameters IaSTestInputParam (required)
Body Parameter — Parameters required to update app profile of an elastic distributed inference service.

Return type

IaSTestResultParam

Example data

Content-Type: application/json
{
  "modelName" : "modelName",
  "other" : "other",
  "reslove" : true,
  "results" : [ {
    "classificationResults" : [ {
      "isImage" : true,
      "inputPath" : "inputPath",
      "sampleId" : "sampleId",
      "results" : [ {
        "prob" : 0.8008281904610115,
        "bbox" : "bbox",
        "label" : "label"
      }, {
        "prob" : 0.8008281904610115,
        "bbox" : "bbox",
        "label" : "label"
      } ]
    }, {
      "isImage" : true,
      "inputPath" : "inputPath",
      "sampleId" : "sampleId",
      "results" : [ {
        "prob" : 0.8008281904610115,
        "bbox" : "bbox",
        "label" : "label"
      }, {
        "prob" : 0.8008281904610115,
        "bbox" : "bbox",
        "label" : "label"
      } ]
    } ],
    "type" : "type",
    "comparisonResults" : [ {
      "isImage" : true,
      "inputPath" : "inputPath",
      "distance" : 6.027456183070403,
      "sampleId1" : "sampleId1",
      "sampleId2" : "sampleId2",
      "isSimilar" : true
    }, {
      "isImage" : true,
      "inputPath" : "inputPath",
      "distance" : 6.027456183070403,
      "sampleId1" : "sampleId1",
      "sampleId2" : "sampleId2",
      "isSimilar" : true
    } ],
    "detResults" : [ {
      "isImage" : true,
      "inputPath" : "inputPath",
      "sampleId" : "sampleId",
      "results" : [ {
        "prob" : 0.8008281904610115,
        "bbox" : "bbox",
        "label" : "label"
      }, {
        "prob" : 0.8008281904610115,
        "bbox" : "bbox",
        "label" : "label"
      } ]
    }, {
      "isImage" : true,
      "inputPath" : "inputPath",
      "sampleId" : "sampleId",
      "results" : [ {
        "prob" : 0.8008281904610115,
        "bbox" : "bbox",
        "label" : "label"
      }, {
        "prob" : 0.8008281904610115,
        "bbox" : "bbox",
        "label" : "label"
      } ]
    } ]
  }, {
    "classificationResults" : [ {
      "isImage" : true,
      "inputPath" : "inputPath",
      "sampleId" : "sampleId",
      "results" : [ {
        "prob" : 0.8008281904610115,
        "bbox" : "bbox",
        "label" : "label"
      }, {
        "prob" : 0.8008281904610115,
        "bbox" : "bbox",
        "label" : "label"
      } ]
    }, {
      "isImage" : true,
      "inputPath" : "inputPath",
      "sampleId" : "sampleId",
      "results" : [ {
        "prob" : 0.8008281904610115,
        "bbox" : "bbox",
        "label" : "label"
      }, {
        "prob" : 0.8008281904610115,
        "bbox" : "bbox",
        "label" : "label"
      } ]
    } ],
    "type" : "type",
    "comparisonResults" : [ {
      "isImage" : true,
      "inputPath" : "inputPath",
      "distance" : 6.027456183070403,
      "sampleId1" : "sampleId1",
      "sampleId2" : "sampleId2",
      "isSimilar" : true
    }, {
      "isImage" : true,
      "inputPath" : "inputPath",
      "distance" : 6.027456183070403,
      "sampleId1" : "sampleId1",
      "sampleId2" : "sampleId2",
      "isSimilar" : true
    } ],
    "detResults" : [ {
      "isImage" : true,
      "inputPath" : "inputPath",
      "sampleId" : "sampleId",
      "results" : [ {
        "prob" : 0.8008281904610115,
        "bbox" : "bbox",
        "label" : "label"
      }, {
        "prob" : 0.8008281904610115,
        "bbox" : "bbox",
        "label" : "label"
      } ]
    }, {
      "isImage" : true,
      "inputPath" : "inputPath",
      "sampleId" : "sampleId",
      "results" : [ {
        "prob" : 0.8008281904610115,
        "bbox" : "bbox",
        "label" : "label"
      }, {
        "prob" : 0.8008281904610115,
        "bbox" : "bbox",
        "label" : "label"
      } ]
    } ]
  } ]
}

Produces

This API call produces the following media types according to the Accept request header; the media type will be conveyed by the Content-Type response header.

Responses

200

Successful response that contains the result of inference. IaSTestResultParam

400

Bad request. The request was not formatted correctly.

401

Authentication error. The request was denied.

403

Forbidden. The request was denied.

404

The requested resource was not round.

500

An unexpected error occurred.

Up
get /edimodels/{modelname}
Retrieves detail for a elastic distributed inference service (getEDIModel)
Returns full details for a elastic distributed inference service.

Path parameters

modelname (required)
Path Parameter — The elastic distributed inference service name.

Consumes

This API call consumes the following media types via the Content-Type request header:

Return type

IaSModelDescription

Example data

Content-Type: application/json
{
  "creator" : "creator",
  "mk_environments" : [ {
    "name" : "name",
    "value" : "value"
  }, {
    "name" : "name",
    "value" : "value"
  } ],
  "create_time" : "create_time",
  "mk_instance_min" : 6,
  "runtime" : "runtime",
  "model_path" : "model_path",
  "schema_version" : "schema_version",
  "weight_path" : "weight_path",
  "last_update_time" : "last_update_time",
  "mk_resource_req" : "mk_resource_req",
  "size" : 0,
  "service_uri" : "service_uri",
  "mk_instance_max" : 1,
  "name" : "name",
  "attributes" : [ {
    "value" : "value",
    "key" : "key"
  }, {
    "value" : "value",
    "key" : "key"
  } ],
  "tag" : "tag",
  "mk_umask" : "mk_umask",
  "state" : "state",
  "kernel_path" : "kernel_path"
}

Produces

This API call produces the following media types according to the Accept request header; the media type will be conveyed by the Content-Type response header.

Responses

200

Successful response that contains the resulting elastic distributed inference service. IaSModelDescription

400

Bad request. The request was not formatted correctly.

401

Authentication error. The request was denied.

403

Forbidden. The request was denied.

500

An unexpected error occurred.

Up
get /edimodels/{modelname}/instance
Retrieves detail for instance of an elastic distributed inference service (getEDIModelInstance)
Returns full details for instance of an elastic distributed inference service.

Path parameters

modelname (required)
Path Parameter — The elastic distributed inference service name.

Consumes

This API call consumes the following media types via the Content-Type request header:

Return type

IaSInstanceParam

Example data

Content-Type: application/json
{
  "instance" : {
    "instances" : [ {
      "client_number" : 0,
      "isd_uid" : "isd_uid",
      "request_per_sec" : 1,
      "data_size_per_sec" : 5,
      "pending_number" : 6,
      "isd_container" : [ {
        "container_uid" : "container_uid",
        "running_task" : 2,
        "total_task" : 5,
        "container_status" : "container_status",
        "finish_task" : 7,
        "failed_task" : 9,
        "container_host" : "container_host"
      }, {
        "container_uid" : "container_uid",
        "running_task" : 2,
        "total_task" : 5,
        "container_status" : "container_status",
        "finish_task" : 7,
        "failed_task" : 9,
        "container_host" : "container_host"
      } ]
    }, {
      "client_number" : 0,
      "isd_uid" : "isd_uid",
      "request_per_sec" : 1,
      "data_size_per_sec" : 5,
      "pending_number" : 6,
      "isd_container" : [ {
        "container_uid" : "container_uid",
        "running_task" : 2,
        "total_task" : 5,
        "container_status" : "container_status",
        "finish_task" : 7,
        "failed_task" : 9,
        "container_host" : "container_host"
      }, {
        "container_uid" : "container_uid",
        "running_task" : 2,
        "total_task" : 5,
        "container_status" : "container_status",
        "finish_task" : 7,
        "failed_task" : 9,
        "container_host" : "container_host"
      } ]
    } ],
    "name" : "name",
    "state" : "state"
  },
  "name" : "name",
  "state" : "state"
}

Produces

This API call produces the following media types according to the Accept request header; the media type will be conveyed by the Content-Type response header.

Responses

200

Successful response that contains the resulting instance of elastic distributed inference service. IaSInstanceParam

400

Bad request. The request was not formatted correctly.

401

Authentication error. The request was denied.

403

Forbidden. The request was denied.

500

An unexpected error occurred.

Up
get /edimodels/{modelname}/appprofile
Retrieves detail for app profile of an elastic distributed inference service (getEDIModelPorfile)
Returns full details for app profile of an elastic distributed inference service.

Path parameters

modelname (required)
Path Parameter — The elastic distributed inference service name.

Consumes

This API call consumes the following media types via the Content-Type request header:

Return type

IaSProfileParam

Example data

Content-Type: application/json
{
  "schema_version" : "schema_version",
  "update_time" : "update_time",
  "create_time" : "create_time",
  "replica" : 0,
  "kernel" : {
    "log_directory" : "log_directory",
    "umask" : "umask",
    "envs" : {
      "name" : "name",
      "value" : "value"
    },
    "working_directory" : "working_directory",
    "run_as" : "run_as",
    "connection_timeout" : 3,
    "gpu" : "gpu"
  },
  "name" : "name",
  "resource_allocation" : {
    "service" : {
      "resource_group" : "resource_group",
      "resreq" : "resreq",
      "type" : "type",
      "consumer" : "consumer"
    },
    "kernel" : {
      "resource_group" : "resource_group",
      "resreq" : "resreq",
      "type" : "type",
      "consumer" : "consumer"
    }
  },
  "envs" : [ {
    "name" : "name",
    "value" : "value"
  }, {
    "name" : "name",
    "value" : "value"
  } ],
  "type" : "type",
  "policy" : {
    "task_execution_timeout" : 2,
    "task_batch_size" : 7,
    "stream_number_per_group" : 9,
    "stream_discard_slow_tasks" : true,
    "name" : "name",
    "kernel_delay_release_time" : 5,
    "schedule_intervel" : 6,
    "kernel_min" : 1,
    "kernel_max" : 5
  }
}

Produces

This API call produces the following media types according to the Accept request header; the media type will be conveyed by the Content-Type response header.

Responses

200

Successful response that contains the resulting app profile of elastic distributed inference service. IaSProfileParam

400

Bad request. The request was not formatted correctly.

401

Authentication error. The request was denied.

403

Forbidden. The request was denied.

500

An unexpected error occurred.

Up
get /edimodels/{modelname}/readme
Retrieves readme of an elastic distributed inference service (getEDIModelReadme)
Returns readme of an elastic distributed inference service.

Path parameters

modelname (required)
Path Parameter — The elastic distributed inference service name.

Consumes

This API call consumes the following media types via the Content-Type request header:

Return type

IaSReadmeParam

Example data

Content-Type: application/json
{
  "readme" : "readme"
}

Produces

This API call produces the following media types according to the Accept request header; the media type will be conveyed by the Content-Type response header.

Responses

200

Successful response that contains the resulting readme of elastic distributed inference service. IaSReadmeParam

400

Bad request. The request was not formatted correctly.

401

Authentication error. The request was denied.

403

Forbidden. The request was denied.

500

An unexpected error occurred.

Up
get /edimodels/{modelname}/streaming
Retrieves streaming uri for the elastic distributed inference service (getEDIModelStreaming)
Retrieves streaming uri for the elastic distributed inference service

Path parameters

modelname (required)
Path Parameter — The elastic distributed inference services name.

Consumes

This API call consumes the following media types via the Content-Type request header:

Return type

String

Example data

Content-Type: application/json
""

Produces

This API call produces the following media types according to the Accept request header; the media type will be conveyed by the Content-Type response header.

Responses

200

Successful response that contains the resulting of streaming uri. String

400

Bad request. The request was not formatted correctly.

401

Authentication error. The request was denied.

403

Forbidden. The request was denied.

500

An unexpected error occurred.

Up
get /edimodels
Retrieves all elastic distributed inference services defined in the system (getEDIModels)
Returns full listing of all the elastic distributed inference services defined in the system.

Consumes

This API call consumes the following media types via the Content-Type request header:

Return type

array[IaSModelDescription]

Example data

Content-Type: application/json
[ {
  "creator" : "creator",
  "mk_environments" : [ {
    "name" : "name",
    "value" : "value"
  }, {
    "name" : "name",
    "value" : "value"
  } ],
  "create_time" : "create_time",
  "mk_instance_min" : 6,
  "runtime" : "runtime",
  "model_path" : "model_path",
  "schema_version" : "schema_version",
  "weight_path" : "weight_path",
  "last_update_time" : "last_update_time",
  "mk_resource_req" : "mk_resource_req",
  "size" : 0,
  "service_uri" : "service_uri",
  "mk_instance_max" : 1,
  "name" : "name",
  "attributes" : [ {
    "value" : "value",
    "key" : "key"
  }, {
    "value" : "value",
    "key" : "key"
  } ],
  "tag" : "tag",
  "mk_umask" : "mk_umask",
  "state" : "state",
  "kernel_path" : "kernel_path"
}, {
  "creator" : "creator",
  "mk_environments" : [ {
    "name" : "name",
    "value" : "value"
  }, {
    "name" : "name",
    "value" : "value"
  } ],
  "create_time" : "create_time",
  "mk_instance_min" : 6,
  "runtime" : "runtime",
  "model_path" : "model_path",
  "schema_version" : "schema_version",
  "weight_path" : "weight_path",
  "last_update_time" : "last_update_time",
  "mk_resource_req" : "mk_resource_req",
  "size" : 0,
  "service_uri" : "service_uri",
  "mk_instance_max" : 1,
  "name" : "name",
  "attributes" : [ {
    "value" : "value",
    "key" : "key"
  }, {
    "value" : "value",
    "key" : "key"
  } ],
  "tag" : "tag",
  "mk_umask" : "mk_umask",
  "state" : "state",
  "kernel_path" : "kernel_path"
} ]

Produces

This API call produces the following media types according to the Accept request header; the media type will be conveyed by the Content-Type response header.

Responses

200

Successful response that contains the resulting elastic distributed inference services.

400

Bad request. The request was not formatted correctly.

401

Authentication error. The request was denied.

403

Forbidden. The request was denied.

500

An unexpected error occurred.

Up
post /edimodels/new
Create a new elastic distributed inference service. (newEDIModel)
Create a new elastic distributed inference service.

Consumes

This API call consumes the following media types via the Content-Type request header:

Request body

IaSParameters IaSParam (required)
Body Parameter — Parameters required to create a new elastic distributed inference service.

Produces

This API call produces the following media types according to the Accept request header; the media type will be conveyed by the Content-Type response header.

Responses

201

Successfully create elastic distributed inference service.

400

Bad request. The request was not formatted correctly.

401

Authentication error. The request was denied.

403

Forbidden. The request was denied.

404

The requested resource was not round.

500

An unexpected error occurred.

Up
post /edimodels/{modelname}
Publish a new elastic distributed inference service from the DLI inference model. (publishEDIModel)
Publish a new elastic distributed inference service from the DLI inference model.

Path parameters

modelname (required)
Path Parameter — The name of deep learning model, which will be published to Elastic Distributed Inference service.

Consumes

This API call consumes the following media types via the Content-Type request header:

Request body

IaSParameters IaSParam (required)
Body Parameter — Parameters required to publish a new elastic distributed inference service.

Produces

This API call produces the following media types according to the Accept request header; the media type will be conveyed by the Content-Type response header.

Responses

201

Successfully publish elastic distributed inference service.

400

Bad request. The request was not formatted correctly.

401

Authentication error. The request was denied.

403

Forbidden. The request was denied.

404

The requested resource was not round.

500

An unexpected error occurred.

Up
put /edimodels/{modelname}/operation/start
Start an elastic distributed inference service (startEDIModel)
Start an elastic distributed inference service.

Path parameters

modelname (required)
Path Parameter — The elastic distributed inference service name.

Consumes

This API call consumes the following media types via the Content-Type request header:

Produces

This API call produces the following media types according to the Accept request header; the media type will be conveyed by the Content-Type response header.

Responses

200

Ok. Successfully started the elastic distributed inference service.

400

Bad request. The request was not formatted correctly.

401

Authentication error. The request was denied.

403

Forbidden. The request was denied.

404

The requested resource was not found.

500

An unexpected error occurred.

Up
put /edimodels/{modelname}/operation/stop
Stop an elastic distributed inference service (stopEDIModel)
Stop an elastic distributed inference service.

Path parameters

modelname (required)
Path Parameter — The elastic distributed inference service name.

Consumes

This API call consumes the following media types via the Content-Type request header:

Produces

This API call produces the following media types according to the Accept request header; the media type will be conveyed by the Content-Type response header.

Responses

200

Ok. Successfully stopped the elastic distributed inference service.

400

Bad request. The request was not formatted correctly.

401

Authentication error. The request was denied.

403

Forbidden. The request was denied.

404

The requested resource was not found.

500

An unexpected error occurred.

Up
put /edimodels/{modelname}
Update elastic distributed inference service. (updateEDIModel)
Update elastic distributed inference service.

Path parameters

modelname (required)
Path Parameter — The elastic distributed inference service name.

Consumes

This API call consumes the following media types via the Content-Type request header:

Request body

IaSModelParameters IaSModelDescription (required)
Body Parameter — Parameters required to update app profile of an elastic distributed inference service.

Produces

This API call produces the following media types according to the Accept request header; the media type will be conveyed by the Content-Type response header.

Responses

201

Successfully update elastic distributed inference service.

400

Bad request. The request was not formatted correctly.

401

Authentication error. The request was denied.

403

Forbidden. The request was denied.

404

The requested resource was not round.

500

An unexpected error occurred.

Up
put /edimodels/{modelname}/appprofile
Update app profile of an elastic distributed inference service. (updateEDIModelPorfile)
Update app profile of an elastic distributed inference service.

Path parameters

modelname (required)
Path Parameter — The elastic distributed inference service name.

Consumes

This API call consumes the following media types via the Content-Type request header:

Request body

IaSProfileParameters IaSProfileParam (required)
Body Parameter — Parameters required to update app profile of an elastic distributed inference service.

Produces

This API call produces the following media types according to the Accept request header; the media type will be conveyed by the Content-Type response header.

Responses

201

Successfully update app profile of elastic distributed inference service.

400

Bad request. The request was not formatted correctly.

401

Authentication error. The request was denied.

403

Forbidden. The request was denied.

404

The requested resource was not round.

500

An unexpected error occurred.

Execute

Up
delete /execs
Deletes all tasks started by the current users. (execsDelete)
Delete all tasks

Consumes

This API call consumes the following media types via the Content-Type request header:

Produces

This API call produces the following media types according to the Accept request header; the media type will be conveyed by the Content-Type response header.

Responses

200

Ok. Successfully deleted all tasks.

401

Authentication error. The request was denied.

500

An unexpected error occurred.

Up
delete /execs/{execId}
Deletes a task started through Execute (execsExecIdDelete)
Deletes a task

Path parameters

execId (required)
Path Parameter — ID of task

Consumes

This API call consumes the following media types via the Content-Type request header:

Produces

This API call produces the following media types according to the Accept request header; the media type will be conveyed by the Content-Type response header.

Responses

200

Ok. Successfully deleted the task.

400

Cannot find task with given execId.

401

Authentication error. The request was denied.

500

An unexpected error occurred.

Up
get /execs/{execId}
Retrieves a task started through Execute (execsExecIdGet)
Retrieves a task started through Execute. The returned values 'sigId', 'submissionId' can be used to make other Conductor REST calls to get additional task details.

Path parameters

execId (required)
Path Parameter — ID of task

Consumes

This API call consumes the following media types via the Content-Type request header:

Return type

Batch

Example data

Content-Type: application/json
{
  "args" : "args",
  "submissionId" : "submissionId",
  "executionUserName" : "executionUserName",
  "sigName" : "sigName",
  "masterURL" : "masterURL",
  "appId" : "appId",
  "sigId" : "sigId",
  "id" : "id",
  "state" : "state",
  "userName" : "userName"
}

Produces

This API call produces the following media types according to the Accept request header; the media type will be conveyed by the Content-Type response header.

Responses

200

Successful response that contains the task. Batch

400

Cannot find task with given execId.

401

Authentication error. The request was denied.

500

An unexpected error occurred.

Up
get /execs/{execId}/log
Retrieve logs of the training task by execution ID. (execsExecIdLogGet)
Retrieve logs of the training task by execution ID.

Path parameters

execId (required)
Path Parameter — Execution ID of the training task.

Consumes

This API call consumes the following media types via the Content-Type request header:

Return type

String

Example data

Content-Type: application/json
""

Produces

This API call produces the following media types according to the Accept request header; the media type will be conveyed by the Content-Type response header.

Responses

200

Successful response that contains the logs of this training task. String

400

Cannot find task with the given execId.

401

Authentication error. The request was denied.

500

An unexpected error occurred.

Up
get /execs/{execId}/result
Retrieve the result of the training task using an execution ID. (execsExecIdResultGet)
Retrieve the result of the training task using an execution ID.

Path parameters

execId (required)
Path Parameter — Execution ID of the training task.

Consumes

This API call consumes the following media types via the Content-Type request header:

Return type

String

Example data

Content-Type: application/json
""

Produces

This API call produces the following media types according to the Accept request header; the media type will be conveyed by the Content-Type response header.

Responses

200

Successful response that contains the trained model of the training task. Returned as a zip file. String

400

Cannot find task with the given execId.

401

Authentication error. The request was denied.

500

An unexpected error occurred.

Up
post /execs/{execId}/stop
Stop the training task by execution ID. (execsExecIdStopPost)
Stop the training task by execution ID.

Path parameters

execId (required)
Path Parameter — Execution ID of the training task.

Consumes

This API call consumes the following media types via the Content-Type request header:

Produces

This API call produces the following media types according to the Accept request header; the media type will be conveyed by the Content-Type response header.

Responses

200

Successfully stopped the tasks.

400

Cannot find task with the given execId.

401

Authentication error. The request was denied.

500

An unexpected error occurred.

Up
get /execs/frameworks
Retrieves all deep learning framework plugins (execsFrameworksGet)
Retrieves all deep learning framework plugins

Consumes

This API call consumes the following media types via the Content-Type request header:

Return type

array[DLFramework]

Example data

Content-Type: application/json
[ {
  "distributeStrategy" : "MultiWorkerMirroredStrategy",
  "frameworkVersion" : "frameworkVersion",
  "name" : "name",
  "description" : "description",
  "numPs" : 0,
  "desc" : [ "desc", "desc" ]
}, {
  "distributeStrategy" : "MultiWorkerMirroredStrategy",
  "frameworkVersion" : "frameworkVersion",
  "name" : "name",
  "description" : "description",
  "numPs" : 0,
  "desc" : [ "desc", "desc" ]
} ]

Produces

This API call produces the following media types according to the Accept request header; the media type will be conveyed by the Content-Type response header.

Responses

200

Successful response that contains all deep learning framework plugins. Framework plugin names are used to start a task.

401

Authentication error. The request was denied.

500

An unexpected error occurred.

Up
get /execs
Retrieves all tasks started through Execute (execsGet)
Retrieves all tasks started through Execute

Consumes

This API call consumes the following media types via the Content-Type request header:

Return type

array[Batch]

Example data

Content-Type: application/json
[ {
  "args" : "args",
  "submissionId" : "submissionId",
  "executionUserName" : "executionUserName",
  "sigName" : "sigName",
  "masterURL" : "masterURL",
  "appId" : "appId",
  "sigId" : "sigId",
  "id" : "id",
  "state" : "state",
  "userName" : "userName"
}, {
  "args" : "args",
  "submissionId" : "submissionId",
  "executionUserName" : "executionUserName",
  "sigName" : "sigName",
  "masterURL" : "masterURL",
  "appId" : "appId",
  "sigId" : "sigId",
  "id" : "id",
  "state" : "state",
  "userName" : "userName"
} ]

Produces

This API call produces the following media types according to the Accept request header; the media type will be conveyed by the Content-Type response header.

Responses

200

Successful response that contains the tasks.

401

Authentication error. The request was denied.

500

An unexpected error occurred.

Up
post /execs
Starts a task through Execute (execsPost)
Starts a task through Execute

Consumes

This API call consumes the following media types via the Content-Type request header:

Query parameters

sigName (required)
Query Parameter — The Spark instance group in which to start the task
args (required)
Query Parameter — Arguments to the task. These arguments can be found in the command line interface. They can be model specific arguments. Examples are "--exec-start tensorflow --model-main TF_mnist.py", "--exec-start PyTorch --model-main PyTorch_mnist.py --batch-size 200"

Form parameters

file (required)
Form Parameter — If the model consists of one file then specify that file. If the model consists of a directory, then it's the tar of the directory with suffix ".modelDir.tar"

Produces

This API call produces the following media types according to the Accept request header; the media type will be conveyed by the Content-Type response header.

Responses

200

Successful task creation

401

Authentication error. The request was denied.

500

An unexpected error occurred.

Frameworks

Up
get /frameworks/all
Retrieves training engine name for all defined frameworks (getAllDeepLearningFrameworks)
Returns training engine name for all deep learning framework.

Consumes

This API call consumes the following media types via the Content-Type request header:

Return type

array[String]

Example data

Content-Type: application/json
[ "", "" ]

Produces

This API call produces the following media types according to the Accept request header; the media type will be conveyed by the Content-Type response header.

Responses

200

Successful response that contains the resulting framework information.

400

Bad request. The request was not formatted correctly.

401

Authentication error. The request was denied.

403

Forbidden. The request was denied.

404

The requested resource was not found.

500

An unexpected error occurred.

Up
get /frameworks
Retrieves details for all defined frameworks (getDeepLearningFrameworks)
Returns the configuration information for all deep learning framework or a specified deep learning framework.

Consumes

This API call consumes the following media types via the Content-Type request header:

Query parameters

backend (optional)
Query Parameter — Filter deep learning frameworks by the backend framework name.

Return type

array[FrameworkDetail]

Example data

Content-Type: application/json
[ {
  "accelerator" : "Native",
  "name" : "TensorFlow",
  "commIPNetwork" : "commIPNetwork",
  "backend" : "TensorFlow",
  "psNum" : "psNum",
  "home" : "home"
}, {
  "accelerator" : "Native",
  "name" : "TensorFlow",
  "commIPNetwork" : "commIPNetwork",
  "backend" : "TensorFlow",
  "psNum" : "psNum",
  "home" : "home"
} ]

Produces

This API call produces the following media types according to the Accept request header; the media type will be conveyed by the Content-Type response header.

Responses

200

Successful response that contains the resulting framework information.

400

Bad request. The request was not formatted correctly.

401

Authentication error. The request was denied.

403

Forbidden. The request was denied.

404

The requested resource was not found.

500

An unexpected error occurred.

HyperSearch

Up
delete /hypersearch
Delete all hpo tasks (deleteAllHPO)
Delete all hpo tasks.

Consumes

This API call consumes the following media types via the Content-Type request header:

Produces

This API call produces the following media types according to the Accept request header; the media type will be conveyed by the Content-Type response header.

Responses

200

Successfully deleted all the hpo tasks.

400

The request format is invalid.

401

Authentication error. The request was denied.

403

Forbidden. The request was denied.

404

The requested resource is not found.

409

Conflict. The requested resource cannot be deleted because it is in use.

500

An unexpected error occurred.

Up
delete /hypersearch/{hpoName}
Delete a hpo task (deleteOneHPO)
Delete a hpo task.

Path parameters

hpoName (required)
Path Parameter — The hpo task name.

Consumes

This API call consumes the following media types via the Content-Type request header:

Produces

This API call produces the following media types according to the Accept request header; the media type will be conveyed by the Content-Type response header.

Responses

200

Successfully deleted the hpo task.

400

The request format is invalid.

401

Authentication error. The request was denied.

403

Forbidden. The request was denied.

404

The requested resource is not found.

409

Conflict. The requested resource cannot be deleted because it is in use.

500

An unexpected error occurred.

Up
delete /hypersearch/algorithm/{algoName}
Delete a hpo plugin algorithm (deleteOneHPOALGORITHM)
Delete a hpo plugin algorithm.

Path parameters

algoName (required)
Path Parameter — The hpo plugin algorithm name.

Consumes

This API call consumes the following media types via the Content-Type request header:

Produces

This API call produces the following media types according to the Accept request header; the media type will be conveyed by the Content-Type response header.

Responses

200

Successfully deleted the hpo plugin algorithm.

400

The request format is invalid.

401

Authentication error. The request was denied.

403

Forbidden. The request was denied.

404

The requested resource is not found.

500

An unexpected error occurred.

Up
get /hypersearch
Retrieve all hpo tasks. (getAllHPO)
Get all the hpo tasks that the login user can access.

Consumes

This API call consumes the following media types via the Content-Type request header:

Return type

array[HpoTaskState]

Example data

Content-Type: application/json
[ {
  "duration" : "duration",
  "creator" : "creator",
  "createtime" : "createtime",
  "hpoName" : "hpoName",
  "experiments" : [ {
    "maxiteration" : 6,
    "driverId" : "driverId",
    "appId" : "appId",
    "metricVal" : 1.4894159098541704,
    "startTime" : "startTime",
    "id" : 1,
    "state" : "state",
    "endTime" : "endTime",
    "hyperParams" : {
      "maxIntVal" : 5,
      "fixedVal" : "fixedVal",
      "minIntVal" : 1,
      "dataType" : "int",
      "userDefined" : true,
      "discreateStrVal" : [ "discreateStrVal", "discreateStrVal" ],
      "type" : "range",
      "discreteIntVal" : [ 2, 2 ],
      "maxDbVal" : 6.027456183070403,
      "name" : "name",
      "step" : "step",
      "power" : "power",
      "discreteDbVal" : [ 5.637376656633329, 5.637376656633329 ],
      "minDbVal" : 0.8008281904610115
    }
  }, {
    "maxiteration" : 6,
    "driverId" : "driverId",
    "appId" : "appId",
    "metricVal" : 1.4894159098541704,
    "startTime" : "startTime",
    "id" : 1,
    "state" : "state",
    "endTime" : "endTime",
    "hyperParams" : {
      "maxIntVal" : 5,
      "fixedVal" : "fixedVal",
      "minIntVal" : 1,
      "dataType" : "int",
      "userDefined" : true,
      "discreateStrVal" : [ "discreateStrVal", "discreateStrVal" ],
      "type" : "range",
      "discreteIntVal" : [ 2, 2 ],
      "maxDbVal" : 6.027456183070403,
      "name" : "name",
      "step" : "step",
      "power" : "power",
      "discreteDbVal" : [ 5.637376656633329, 5.637376656633329 ],
      "minDbVal" : 0.8008281904610115
    }
  } ],
  "progress" : "progress",
  "best" : {
    "maxiteration" : 6,
    "driverId" : "driverId",
    "appId" : "appId",
    "metricVal" : 1.4894159098541704,
    "startTime" : "startTime",
    "id" : 1,
    "state" : "state",
    "endTime" : "endTime",
    "hyperParams" : {
      "maxIntVal" : 5,
      "fixedVal" : "fixedVal",
      "minIntVal" : 1,
      "dataType" : "int",
      "userDefined" : true,
      "discreateStrVal" : [ "discreateStrVal", "discreateStrVal" ],
      "type" : "range",
      "discreteIntVal" : [ 2, 2 ],
      "maxDbVal" : 6.027456183070403,
      "name" : "name",
      "step" : "step",
      "power" : "power",
      "discreteDbVal" : [ 5.637376656633329, 5.637376656633329 ],
      "minDbVal" : 0.8008281904610115
    }
  },
  "state" : "state"
}, {
  "duration" : "duration",
  "creator" : "creator",
  "createtime" : "createtime",
  "hpoName" : "hpoName",
  "experiments" : [ {
    "maxiteration" : 6,
    "driverId" : "driverId",
    "appId" : "appId",
    "metricVal" : 1.4894159098541704,
    "startTime" : "startTime",
    "id" : 1,
    "state" : "state",
    "endTime" : "endTime",
    "hyperParams" : {
      "maxIntVal" : 5,
      "fixedVal" : "fixedVal",
      "minIntVal" : 1,
      "dataType" : "int",
      "userDefined" : true,
      "discreateStrVal" : [ "discreateStrVal", "discreateStrVal" ],
      "type" : "range",
      "discreteIntVal" : [ 2, 2 ],
      "maxDbVal" : 6.027456183070403,
      "name" : "name",
      "step" : "step",
      "power" : "power",
      "discreteDbVal" : [ 5.637376656633329, 5.637376656633329 ],
      "minDbVal" : 0.8008281904610115
    }
  }, {
    "maxiteration" : 6,
    "driverId" : "driverId",
    "appId" : "appId",
    "metricVal" : 1.4894159098541704,
    "startTime" : "startTime",
    "id" : 1,
    "state" : "state",
    "endTime" : "endTime",
    "hyperParams" : {
      "maxIntVal" : 5,
      "fixedVal" : "fixedVal",
      "minIntVal" : 1,
      "dataType" : "int",
      "userDefined" : true,
      "discreateStrVal" : [ "discreateStrVal", "discreateStrVal" ],
      "type" : "range",
      "discreteIntVal" : [ 2, 2 ],
      "maxDbVal" : 6.027456183070403,
      "name" : "name",
      "step" : "step",
      "power" : "power",
      "discreteDbVal" : [ 5.637376656633329, 5.637376656633329 ],
      "minDbVal" : 0.8008281904610115
    }
  } ],
  "progress" : "progress",
  "best" : {
    "maxiteration" : 6,
    "driverId" : "driverId",
    "appId" : "appId",
    "metricVal" : 1.4894159098541704,
    "startTime" : "startTime",
    "id" : 1,
    "state" : "state",
    "endTime" : "endTime",
    "hyperParams" : {
      "maxIntVal" : 5,
      "fixedVal" : "fixedVal",
      "minIntVal" : 1,
      "dataType" : "int",
      "userDefined" : true,
      "discreateStrVal" : [ "discreateStrVal", "discreateStrVal" ],
      "type" : "range",
      "discreteIntVal" : [ 2, 2 ],
      "maxDbVal" : 6.027456183070403,
      "name" : "name",
      "step" : "step",
      "power" : "power",
      "discreteDbVal" : [ 5.637376656633329, 5.637376656633329 ],
      "minDbVal" : 0.8008281904610115
    }
  },
  "state" : "state"
} ]

Produces

This API call produces the following media types according to the Accept request header; the media type will be conveyed by the Content-Type response header.

Responses

200

Successful response that contains the resulting hpo tasks.

400

Bad request. The request was not formatted correctly.

401

Authentication error. The request was denied.

403

Forbidden. The request was denied.

500

An unexpected error occurred.

Up
get /hypersearch/algorithm
Retrieve all hpo algorithm by algorithm type. (getAllHPOAlgorithm)
Get all the hpo tasks that the login user can access.

Consumes

This API call consumes the following media types via the Content-Type request header:

Query parameters

type (optional)
Query Parameter — The algorithm type, BUILD_IN or USER_PLUGIN, if not specified, it will query all algorithms

Return type

array[HpoAlgorithmDesc]

Example data

Content-Type: application/json
[ {
  "path" : "path",
  "createtime" : "createtime",
  "logLevel" : "logLevel",
  "condaEnv" : "condaEnv",
  "name" : "name",
  "condaHome" : "condaHome",
  "type" : "type",
  "remoteExec" : true
}, {
  "path" : "path",
  "createtime" : "createtime",
  "logLevel" : "logLevel",
  "condaEnv" : "condaEnv",
  "name" : "name",
  "condaHome" : "condaHome",
  "type" : "type",
  "remoteExec" : true
} ]

Produces

This API call produces the following media types according to the Accept request header; the media type will be conveyed by the Content-Type response header.

Responses

200

Successful response that contains the resulting hpo tasks.

400

Bad request. The request was not formatted correctly.

401

Authentication error. The request was denied.

403

Forbidden. The request was denied.

500

An unexpected error occurred.

Up
get /hypersearch/algorithm/{algoName}
Retrieve the hpo algorithm detail (getOneAlgorithm)
Retrieve the hpo algorithm detail with the specified name in URL.

Path parameters

algoName (required)
Path Parameter — The hpo algorithm name.

Consumes

This API call consumes the following media types via the Content-Type request header:

Return type

HpoAlgorithmDesc

Example data

Content-Type: application/json
{
  "path" : "path",
  "createtime" : "createtime",
  "logLevel" : "logLevel",
  "condaEnv" : "condaEnv",
  "name" : "name",
  "condaHome" : "condaHome",
  "type" : "type",
  "remoteExec" : true
}

Produces

This API call produces the following media types according to the Accept request header; the media type will be conveyed by the Content-Type response header.

Responses

200

Successful response that contains the resulting hpo algorithm. HpoAlgorithmDesc

400

Bad request. The request was not formatted correctly.

401

Authentication error. The request was denied.

403

Forbidden. The request was denied.

500

An unexpected error occurred.

Up
get /hypersearch/{hpoName}
Retrieve the hpo task detail (getOneHPO)
Retrieve the hpo task detail with the specified hpo task name in URL.

Path parameters

hpoName (required)
Path Parameter — The hpo task name.

Consumes

This API call consumes the following media types via the Content-Type request header:

Return type

HpoTaskState

Example data

Content-Type: application/json
{
  "duration" : "duration",
  "creator" : "creator",
  "createtime" : "createtime",
  "hpoName" : "hpoName",
  "experiments" : [ {
    "maxiteration" : 6,
    "driverId" : "driverId",
    "appId" : "appId",
    "metricVal" : 1.4894159098541704,
    "startTime" : "startTime",
    "id" : 1,
    "state" : "state",
    "endTime" : "endTime",
    "hyperParams" : {
      "maxIntVal" : 5,
      "fixedVal" : "fixedVal",
      "minIntVal" : 1,
      "dataType" : "int",
      "userDefined" : true,
      "discreateStrVal" : [ "discreateStrVal", "discreateStrVal" ],
      "type" : "range",
      "discreteIntVal" : [ 2, 2 ],
      "maxDbVal" : 6.027456183070403,
      "name" : "name",
      "step" : "step",
      "power" : "power",
      "discreteDbVal" : [ 5.637376656633329, 5.637376656633329 ],
      "minDbVal" : 0.8008281904610115
    }
  }, {
    "maxiteration" : 6,
    "driverId" : "driverId",
    "appId" : "appId",
    "metricVal" : 1.4894159098541704,
    "startTime" : "startTime",
    "id" : 1,
    "state" : "state",
    "endTime" : "endTime",
    "hyperParams" : {
      "maxIntVal" : 5,
      "fixedVal" : "fixedVal",
      "minIntVal" : 1,
      "dataType" : "int",
      "userDefined" : true,
      "discreateStrVal" : [ "discreateStrVal", "discreateStrVal" ],
      "type" : "range",
      "discreteIntVal" : [ 2, 2 ],
      "maxDbVal" : 6.027456183070403,
      "name" : "name",
      "step" : "step",
      "power" : "power",
      "discreteDbVal" : [ 5.637376656633329, 5.637376656633329 ],
      "minDbVal" : 0.8008281904610115
    }
  } ],
  "progress" : "progress",
  "best" : {
    "maxiteration" : 6,
    "driverId" : "driverId",
    "appId" : "appId",
    "metricVal" : 1.4894159098541704,
    "startTime" : "startTime",
    "id" : 1,
    "state" : "state",
    "endTime" : "endTime",
    "hyperParams" : {
      "maxIntVal" : 5,
      "fixedVal" : "fixedVal",
      "minIntVal" : 1,
      "dataType" : "int",
      "userDefined" : true,
      "discreateStrVal" : [ "discreateStrVal", "discreateStrVal" ],
      "type" : "range",
      "discreteIntVal" : [ 2, 2 ],
      "maxDbVal" : 6.027456183070403,
      "name" : "name",
      "step" : "step",
      "power" : "power",
      "discreteDbVal" : [ 5.637376656633329, 5.637376656633329 ],
      "minDbVal" : 0.8008281904610115
    }
  },
  "state" : "state"
}

Produces

This API call produces the following media types according to the Accept request header; the media type will be conveyed by the Content-Type response header.

Responses

200

Successful response that contains the resulting hpo task. HpoTaskState

400

Bad request. The request was not formatted correctly.

401

Authentication error. The request was denied.

403

Forbidden. The request was denied.

500

An unexpected error occurred.

Up
post /hypersearch/algorithm/install
Install a new hpo plugin algorithm (installHPOAlgorithm)

Install a new hpo plugin algorithm by providing algorithm scipts as well as other required parameters.

To install a new hpo plugin algorithm, we need string format of input parameters, which is python dict or json format as below:

data sepcification:

{
   'name': 'required, string, name/id for the plugin algorithm, should be unique.',
   'path': 'optional, string, the path for plugin algorithm scripts on server, required for local installation mode.',
   'condaHome': 'optional, string, the CONDA_HOME to run the algorithm scripts, it will use the DLI_CONDA_HOME if not specified.',
   'condaEnv': 'optional, string, the conda environment to run the algorithm scripts, it will use the DLI default conda environment if not specified.',
   'remoteExec': 'optional, boolean, whether to deploy algorithm execution remotely, the default value is false.',
   'logLevel': 'optional, string, the log level of the plugin algorithm, the default value is INFO.'
}

Consumes

This API call consumes the following media types via the Content-Type request header:

Form parameters

file (optional)
Form Parameter — tar the plugin algorithm directory with suffix ".tar", require if the using upload installation mode
data (required)
Form Parameter — Python dict or json format, convert to string when calling REST.

Produces

This API call produces the following media types according to the Accept request header; the media type will be conveyed by the Content-Type response header.

Responses

200

Successfully installed the hpo plugin algorithm.

400

The request format is invalid.

401

Authentication error. The request was denied.

403

Forbidden. The request was denied.

500

An unexpected error occurred.

Up
post /hypersearch
Start a new hpo task (startHPO)

Start a new hpo task by providing sample images as well as other required parameters.

To start a hpo task, we need string format of input parameters, which is python dict or json format as below:

data sepcification:

{
   'hpoName': 'optional, string, name/id for the hpo task, will generate one if none specified here.',
   'modelSpec': 
   {
       'sigName': 'required, string, same as BYOF training',
       'args': 'required, string, same as BYOF training'
   },
   'algoDef':
   { 
       'algorithm': 'required, string, it can be build in algorithms like Random, Bayesian, Tpe, Hyperband and ExperimentGridSearch, or user installed algorithms',
       'maxRunTime': 'optional, int, max running time of the hpo task in minutes, default -1(unlimited)',
       'maxJobNum': 'optional, int, max number of training job to submitted for hpo task, default -1(unlimited)',
       'maxParalleJob': 'optinal, int, max number of training job to run in parallel, default 1',
       'objectiveMetric': 'required, string, name of metric will be optimized, same one in the val_dict_list.json',
       'objective': 'required, string, optimize policy, one of minimize, maximize',
       'algoParams': 'optional, list like [{'name':'', value:''}], additional algorithm parameters and it could be different for each algorithm which will be covered in later part'
   },
   'hyperParams':
   [
       {
           'name': 'required, string, hyperparameter name, the same name will be used in the config.json so user model can load it',
           'type': 'required, string, one of Range, Discrete',
           'dataType': 'required, string, one of int, double, str',
           'minDbVal': 'double, required if type=Range and datatype=double',
           'maxDbVal': 'double, required if type=Range and datatype=double',
           'minIntVal': 'int, required if type=Range and datatype=int',
           'maxIntVal': 'int, required if type=Range and datatype=int',
           'discreteDbVal': 'double, list like [0.1, 0.2], required if type=Discrete and dataType=double',
           'discreteIntVal': 'int, list like [1, 2], required if type=Discrete and datatype=int',
           'discreateStrVal': 'string, list like ['1', '2'], required if type=Discrete and datatype=str',
           'power': 'a number value in string format, the base value for power calculation. ONLY valid when type is Range',
           'step': 'a number value in string format, step size to split the Range space. ONLY valid when type is Range'
       }
   ],
   'experiments':
   [
       {
          'id': 'required, int, hyperparameter experiment id',
          'hyperParams':
          [
              {
                  'name': 'required, string, hyperparameter name, the same name will be used in the config.json so user model can load it',
                  'dataType': 'required, string, one of int, double, str',
                  'fixedVal': 'required, the same type with datatype specified, if dataTye=double, need fixedVal type doulbe'
              }
          ]
       }
    ]
}

Each new hpo task request could only choose one from hyperParams and experiments, for search algorithm ExperimentGridSearch, only experiments is supported, for other algorithms, only hyperParams is supported:

For Random, algoParams can be provided as this:

'algoParams':
[
    {
        'name': 'RandomSeed',
        'value': 'Optional, string, the random seed used to propose hyperparameter combinations.'
    }
]

For Hyperband, algoParams can be provided as this:

'algoParams':
[
    {
        'name': 'RandomSeed',
        'value': 'Optional, string, the random seed used by Hyperband to propose hyperparameter combinations in the first rung of brackets.'
    },
    {
        'name': 'eta',
        'value': 'Optional, string, the reduction factor to control the proportion of configurations discarded in each Hyperband brackets. Default 3.'            
    },
    {
        'name': 'ResourceName',
        'value': 'Required, string, the parameter name that will be taken as resource in Hyperband, normally training epochs or iterations. User can get this parameter from config.json just like other hyper-parameters.'
    },
    {
        'name': 'ResourceValue',
        'value': 'Required, int value in string format, it is the corresponding upper limited value for the ResourceName.'
    }
]

For Tpe, algoParams can be provided as this:

'algoParams':
[
    {
        'name': 'RandomSeed',
        'value': 'Optional, string, the random seed used to propose the TPE initial warm up hyperparameter combinations.'
    },
    {
        'name': 'WarmUp',
        'value': 'Optional, string, the number of initial warm up hyperparameter combinations. It should be bigger than 2. If maxJobNum is smaller than this value, maxJobNum will be taken as the value. Default 20.'
    },
    {
        'name': 'EICandidate',
        'value': 'Optional, string, the number of hyperparameter combinations proposed each round as the candidates for Expected Improvement to propose the final one hyperparameter combination. It should be bigger than 1. Default 24.'
    },
    {
        'name': 'GoodRatio',
        'value': 'Optional, string, the fraction to use as good hyperparameter combinations from previous completed experiment training to build the good Gaussian Mixture Model. It should be bigger than 0. Default 0.25.'
    },
    {
        'name': 'GoodMax',
        'value': 'Optional, string, the max number of good hyperparameter combinations from previous completed experiment training to build the good Gaussian Mixture Model. It should be bigger than 1. Default 25.'
    }
]

For Bayesian, algoParams can be provided as this:

'algoParams':
[
    {
        'name': 'RandomSeed',
        'value': 'Optional, string, the random seed used by Bayesian. If not given, HPO will generate a random RandomSeed.'
    },
    {
        'name': 'InitPoints',
        'value': 'Optional, string, number of random search before approximating with Bayesian algorithm. Default 10.'
    },
    {
        'name': 'CubeSize',
        'value': 'Optional, string, the Bayesian candidate size. The value of CubeSize should not be smaller than the max maxJobNum. If maxJobNum=-1, CubeSize is max(10000, CubeSize), otherwise the default cubSize is maxJobNum*100. '
    },
    {
        'name': 'Noiseless',
        'value': 'Optional, string, specify whether the bayesian sampling will disable noise or not. If your model is entirely deterministic (e.g. analytic), then specify it true to speed up the optimization. If your model is not deterministic (as expected for most Machine Learning or Deep Learning models), then specify it false. Default true (noiseless).'
    }
]

Consumes

This API call consumes the following media types via the Content-Type request header:

Form parameters

file (required)
Form Parameter — If the model consists of one file then specify that file. If the model consists of a directory, then it's the tar of the directory with suffix ".modelDir.tar"
data (required)
Form Parameter — Python dict or json format, convert to string when calling REST.

Produces

This API call produces the following media types according to the Accept request header; the media type will be conveyed by the Content-Type response header.

Responses

200

Successfully started hpo task.

400

The request format is invalid.

401

Authentication error. The request was denied.

403

Forbidden. The request was denied.

409

Conflict. The requested resource already exists.

500

An unexpected error occurred.

Up
put /hypersearch/{hpoName}
Stops a hpo task (stopOneHPO)
Stops a running hpo task.

Path parameters

hpoName (required)
Path Parameter — The HPO task name.

Consumes

This API call consumes the following media types via the Content-Type request header:

Produces

This API call produces the following media types according to the Accept request header; the media type will be conveyed by the Content-Type response header.

Responses

200

Successfully stopped the hpo task.

400

Bad request. The request was not formatted correctly.

401

Authentication error. The request was denied.

403

Forbidden. The request was denied.

404

The requested resource was not found.

500

An unexpected error occurred.

Up
put /hypersearch/{hpoName}/force
Stop a hpo task forcely (stopOneHPOForce)
Stop a running hpo task forcely.

Path parameters

hpoName (required)
Path Parameter — The hpo task name.

Consumes

This API call consumes the following media types via the Content-Type request header:

Produces

This API call produces the following media types according to the Accept request header; the media type will be conveyed by the Content-Type response header.

Responses

200

Successfully stopped the hpo task forcely.

400

Bad request. The request was not formatted correctly.

401

Authentication error. The request was denied.

403

Forbidden. The request was denied.

404

The requested resource was not found.

500

An unexpected error occurred.

Inferences

Up
post /inferences
Create a new inference from the model training. (createModelTrainInference)
Create a new inference from the model training.

Consumes

This API call consumes the following media types via the Content-Type request header:

Request body

InferenceCreateParameters InferenceCreateParam (required)
Body Parameter — Parameters required to create a new inference instance.

Produces

This API call produces the following media types according to the Accept request header; the media type will be conveyed by the Content-Type response header.

Responses

201

Successfully created model inference.

400

Bad request. The request was not formatted correctly.

401

Authentication error. The request was denied.

403

Forbidden. The request was denied.

404

The requested resource was not round.

500

An unexpected error occurred.

Up
delete /inferences/{predictName}
Deletes a prediction (deletePredict)
Deletes a prediction.

Path parameters

predictName (required)
Path Parameter — The prediction name.

Consumes

This API call consumes the following media types via the Content-Type request header:

Produces

This API call produces the following media types according to the Accept request header; the media type will be conveyed by the Content-Type response header.

Responses

200

Successfully deleted the prediction.

400

The request format is invalid.

401

Authentication error. The request was denied.

403

Forbidden. The request was denied.

404

The requested resource is not found.

409

Conflict. The requested resource cannot be deleted because it is in use.

500

An unexpected error occurred.

Up
get /inferences
Get all inference instances for a model (getAllPredictsByModelName)
Get all inference instances for a model.

Consumes

This API call consumes the following media types via the Content-Type request header:

Query parameters

modelname (required)
Query Parameter — The deep learning model name.
flag (required)
Query Parameter — Save results to a file? Currently, saving results is NOT supported, and the flag must be set to "false". default: false

Return type

array[InferenceDetail]

Example data

Content-Type: application/json
[ {
  "signame" : "signame",
  "inputpath" : "inputpath",
  "modelname" : "modelname",
  "predictname" : "predictname",
  "inputfiles" : "inputfiles",
  "sigid" : "sigid",
  "threshold" : "threshold",
  "appURL" : "appURL",
  "resultfile" : "resultfile",
  "output" : "output",
  "result" : {
    "predictResults" : {
      "proba" : 0.8008282,
      "name" : "name",
      "index" : "index"
    },
    "predictItem" : "predictItem"
  },
  "driverid" : "driverid",
  "masterUrl" : "masterUrl",
  "createTime" : "createTime",
  "appid" : "appid",
  "historyServerUrl" : "historyServerUrl",
  "user" : "user",
  "status" : "status"
}, {
  "signame" : "signame",
  "inputpath" : "inputpath",
  "modelname" : "modelname",
  "predictname" : "predictname",
  "inputfiles" : "inputfiles",
  "sigid" : "sigid",
  "threshold" : "threshold",
  "appURL" : "appURL",
  "resultfile" : "resultfile",
  "output" : "output",
  "result" : {
    "predictResults" : {
      "proba" : 0.8008282,
      "name" : "name",
      "index" : "index"
    },
    "predictItem" : "predictItem"
  },
  "driverid" : "driverid",
  "masterUrl" : "masterUrl",
  "createTime" : "createTime",
  "appid" : "appid",
  "historyServerUrl" : "historyServerUrl",
  "user" : "user",
  "status" : "status"
} ]

Produces

This API call produces the following media types according to the Accept request header; the media type will be conveyed by the Content-Type response header.

Responses

200

Successful response containing all inference instances for a model.

400

Bad request. The request was not formatted correctly.

401

Authentication error. The request was denied.

403

Forbidden. The request was denied.

404

The requested resource was not found.

500

An unexpected error occurred.

Up
get /inferences/{predictName}
Get the inference instance details (getPredictByPredictName)
Retrieves the details for one model inference instance.

Path parameters

predictName (required)
Path Parameter — The prediction name.

Consumes

This API call consumes the following media types via the Content-Type request header:

Return type

InferenceDetail

Example data

Content-Type: application/json
{
  "signame" : "signame",
  "inputpath" : "inputpath",
  "modelname" : "modelname",
  "predictname" : "predictname",
  "inputfiles" : "inputfiles",
  "sigid" : "sigid",
  "threshold" : "threshold",
  "appURL" : "appURL",
  "resultfile" : "resultfile",
  "output" : "output",
  "result" : {
    "predictResults" : {
      "proba" : 0.8008282,
      "name" : "name",
      "index" : "index"
    },
    "predictItem" : "predictItem"
  },
  "driverid" : "driverid",
  "masterUrl" : "masterUrl",
  "createTime" : "createTime",
  "appid" : "appid",
  "historyServerUrl" : "historyServerUrl",
  "user" : "user",
  "status" : "status"
}

Produces

This API call produces the following media types according to the Accept request header; the media type will be conveyed by the Content-Type response header.

Responses

200

Successful response containing inference detail for the specified prediction. InferenceDetail

400

The modification request is either missing required values or contains invalid values.

401

Authentication error. The request was denied.

404

The requested resource was not found.

409

The modification request cannot be completed. The deep learning model is not in a valid state for modification.

500

An unexpected error.

Up
get /inferences/{predictName}/predicts
Get the prediction results for an inference (getPredictResults)
Retrieves full prediction results for one inference instance.

Path parameters

predictName (required)
Path Parameter — The prediction name.

Consumes

This API call consumes the following media types via the Content-Type request header:

Return type

PredictResult

Example data

Content-Type: application/json
{
  "classificationResults" : [ {
    "isImage" : true,
    "inputPath" : "inputPath",
    "sampleId" : "sampleId",
    "results" : [ {
      "prob" : 0.8008281904610115,
      "bbox" : "bbox",
      "label" : "label"
    }, {
      "prob" : 0.8008281904610115,
      "bbox" : "bbox",
      "label" : "label"
    } ]
  }, {
    "isImage" : true,
    "inputPath" : "inputPath",
    "sampleId" : "sampleId",
    "results" : [ {
      "prob" : 0.8008281904610115,
      "bbox" : "bbox",
      "label" : "label"
    }, {
      "prob" : 0.8008281904610115,
      "bbox" : "bbox",
      "label" : "label"
    } ]
  } ],
  "type" : "type",
  "comparisonResults" : [ {
    "isImage" : true,
    "inputPath" : "inputPath",
    "distance" : 6.027456183070403,
    "sampleId1" : "sampleId1",
    "sampleId2" : "sampleId2",
    "isSimilar" : true
  }, {
    "isImage" : true,
    "inputPath" : "inputPath",
    "distance" : 6.027456183070403,
    "sampleId1" : "sampleId1",
    "sampleId2" : "sampleId2",
    "isSimilar" : true
  } ],
  "detResults" : [ {
    "isImage" : true,
    "inputPath" : "inputPath",
    "sampleId" : "sampleId",
    "results" : [ {
      "prob" : 0.8008281904610115,
      "bbox" : "bbox",
      "label" : "label"
    }, {
      "prob" : 0.8008281904610115,
      "bbox" : "bbox",
      "label" : "label"
    } ]
  }, {
    "isImage" : true,
    "inputPath" : "inputPath",
    "sampleId" : "sampleId",
    "results" : [ {
      "prob" : 0.8008281904610115,
      "bbox" : "bbox",
      "label" : "label"
    }, {
      "prob" : 0.8008281904610115,
      "bbox" : "bbox",
      "label" : "label"
    } ]
  } ]
}

Produces

This API call produces the following media types according to the Accept request header; the media type will be conveyed by the Content-Type response header.

Responses

200

Successful response containing prediction details. PredictResult

400

The modification request is either missing required values or contains invalid values.

401

Authentication error. The request was denied.

404

The requested resource was not found.

409

The modification request cannot be completed. The deep learning model is not in a valid state for modification.

500

An unexpected error.

Up
post /inferences/startpredict
Start predicting an inference model (startPredict)

Start predicting an inference model by providing sample images as well as other required parameters.

NOTE

You can provide arbitrary number of image files as an input to start a prediction. Here, we only require two files, as an example.

Consumes

This API call consumes the following media types via the Content-Type request header:

Form parameters

image0 (required)
Form Parameter — First image file for testing the prediction
image1 (required)
Form Parameter — Second image file for testing the prediction
modelname (required)
Form Parameter — The model name.
threshold (required)
Form Parameter — The probability threshold for the classification.
masterUrl (optional)
Form Parameter — The Spark instance group master URL.
sigid (optional)
Form Parameter — The Spark instance group ID.
signame (optional)
Form Parameter — The Spark instance group name.
predictname (required)
Form Parameter — The prediction name. Must be unique.

Produces

This API call produces the following media types according to the Accept request header; the media type will be conveyed by the Content-Type response header.

Responses

200

Successfully started prediction.

400

The request format is invalid.

401

Authentication error. The request was denied.

403

Forbidden. The request was denied.

409

Conflict. The requested resource already exists.

500

An unexpected error occurred.

Up
put /inferences/{predictName}/stop
Stops a prediction (stopInference)
Stops a running prediction task.

Path parameters

predictName (required)
Path Parameter — The prediction name.

Consumes

This API call consumes the following media types via the Content-Type request header:

Produces

This API call produces the following media types according to the Accept request header; the media type will be conveyed by the Content-Type response header.

Responses

200

Successfully stopped the prediction job.

400

Bad request. The request was not formatted correctly.

401

Authentication error. The request was denied.

403

Forbidden. The request was denied.

404

The requested resource was not found.

500

An unexpected error occurred.

ModelTemplates

Up
post /modeltemplates
Creates a new deep learning model template (addModelTemplate)
Creates a new deep learning model template.

Consumes

This API call consumes the following media types via the Content-Type request header:

Request body

modeltemplate ModelTemplateCreateParam (required)
Body Parameter — The information that specifies the details of a model template to create.

Produces

This API call produces the following media types according to the Accept request header; the media type will be conveyed by the Content-Type response header.

Responses

201

The deep learning model template is created successfully.

400

The request format is invalid.

401

Authentication error. The request was denied.

403

Forbidden. The request was denied.

409

Conflict. The requested resource already exists.

500

An unexpected error occurred.

Up
delete /modeltemplates/{modeltemplatename}
Deletes a model template (deleteModelTemplate)
Deletes a deep learning model template.

Path parameters

modeltemplatename (required)
Path Parameter — The deep learning model template name.

Consumes

This API call consumes the following media types via the Content-Type request header:

Produces

This API call produces the following media types according to the Accept request header; the media type will be conveyed by the Content-Type response header.

Responses

200

Ok. Successfully deleted the deep learning model template.

400

The request format is invalid.

401

Authentication error. The request was denied.

403

Forbidden. The request was denied.

404

The requested resource is not found.

409

Conflict. The requested resource cannot be deleted because it is in use.

500

An unexpected error occurred.

Up
get /modeltemplates/{modeltemplatename}
Retrieves model template details (getModelTemplateByName)
Returns full details for the specified model template.

Path parameters

modeltemplatename (required)
Path Parameter — The deep learning model template name.

Consumes

This API call consumes the following media types via the Content-Type request header:

Return type

ModelTemplateDetail

Example data

Content-Type: application/json
{
  "inferenceprototxtpath" : "inferenceprototxtpath",
  "tfmainpath" : "tfmainpath",
  "description" : "description",
  "solverContent" : "solverContent",
  "inferenceContent" : "inferenceContent",
  "traintestprototxtpath" : "traintestprototxtpath",
  "hyperparameter" : {
    "learningrate" : 0.8008282,
    "l2_regularization" : 6.84685269835264,
    "maxiteration" : 2,
    "lambd" : 6.683562403749608,
    "centered" : true,
    "threshold_mode" : "threshold_mode",
    "epoch" : 7,
    "lrpolicy" : "multistep",
    "nesterov" : true,
    "threshold" : 6.778324963048013,
    "lr_power" : 4.965218492984954,
    "cycle" : true,
    "dampening" : 6.438423552598547,
    "epsilon" : 1.2315135367772556,
    "mode" : "mode",
    "l1_regularization" : 1.4894159098541704,
    "solvertype" : "AdaDelta",
    "lr_decay" : 9.369310271410669,
    "amsgrad" : true,
    "beta1" : 7.457744773683766,
    "beta2" : 1.1730742509559433,
    "t_max" : 3,
    "alpha" : 8.762042012749001,
    "stepvalues" : "2000,4000,6000",
    "optdecay" : 7.386281948385884,
    "patience" : 2,
    "cooldown" : 6,
    "hiddenstatesize" : 4,
    "power" : 2.027123023002322,
    "weightdecay" : 1.4658129,
    "factor" : 1.284659006116532,
    "staircase" : "staircase",
    "decayrate" : 5.962134,
    "decaysteps" : 5.63737665663332876420099637471139430999755859375,
    "eps" : 5.944895607614016,
    "eta_min" : 6.965117697638846,
    "momentum" : 6.0274563,
    "end_learning_rate" : 5.025004791520295,
    "rho" : 9.965781217890562,
    "accumulator" : 1.0246457001441578,
    "t0" : 9.018348186070783,
    "stepsize" : 9,
    "gamma" : 3.616076749251911
  },
  "path" : "path",
  "solverprototxtpath" : "solverprototxtpath",
  "framework" : "TensorFlow",
  "tfmainContent" : "tfmainContent",
  "frameworkVersion" : "frameworkVersion",
  "name" : "name",
  "trainTestContent" : "trainTestContent"
}

Produces

This API call produces the following media types according to the Accept request header; the media type will be conveyed by the Content-Type response header.

Responses

200

Successful response that contains the resulting deep learning model template. ModelTemplateDetail

400

Bad request. The request was not formatted correctly.

401

Authentication error. The request was denied.

403

Forbidden. The request was denied.

404

The requested resource was not found.

500

An unexpected error occurred.

Up
get /modeltemplates
Retrieves all deep learning model templates (getModelTemplateDetails)
Retrieves all deep learning model templates.

Consumes

This API call consumes the following media types via the Content-Type request header:

Query parameters

framework (optional)
Query Parameter — The deep learning framework name.

Return type

array[ModelTemplateDetail]

Example data

Content-Type: application/json
[ {
  "inferenceprototxtpath" : "inferenceprototxtpath",
  "tfmainpath" : "tfmainpath",
  "description" : "description",
  "solverContent" : "solverContent",
  "inferenceContent" : "inferenceContent",
  "traintestprototxtpath" : "traintestprototxtpath",
  "hyperparameter" : {
    "learningrate" : 0.8008282,
    "l2_regularization" : 6.84685269835264,
    "maxiteration" : 2,
    "lambd" : 6.683562403749608,
    "centered" : true,
    "threshold_mode" : "threshold_mode",
    "epoch" : 7,
    "lrpolicy" : "multistep",
    "nesterov" : true,
    "threshold" : 6.778324963048013,
    "lr_power" : 4.965218492984954,
    "cycle" : true,
    "dampening" : 6.438423552598547,
    "epsilon" : 1.2315135367772556,
    "mode" : "mode",
    "l1_regularization" : 1.4894159098541704,
    "solvertype" : "AdaDelta",
    "lr_decay" : 9.369310271410669,
    "amsgrad" : true,
    "beta1" : 7.457744773683766,
    "beta2" : 1.1730742509559433,
    "t_max" : 3,
    "alpha" : 8.762042012749001,
    "stepvalues" : "2000,4000,6000",
    "optdecay" : 7.386281948385884,
    "patience" : 2,
    "cooldown" : 6,
    "hiddenstatesize" : 4,
    "power" : 2.027123023002322,
    "weightdecay" : 1.4658129,
    "factor" : 1.284659006116532,
    "staircase" : "staircase",
    "decayrate" : 5.962134,
    "decaysteps" : 5.63737665663332876420099637471139430999755859375,
    "eps" : 5.944895607614016,
    "eta_min" : 6.965117697638846,
    "momentum" : 6.0274563,
    "end_learning_rate" : 5.025004791520295,
    "rho" : 9.965781217890562,
    "accumulator" : 1.0246457001441578,
    "t0" : 9.018348186070783,
    "stepsize" : 9,
    "gamma" : 3.616076749251911
  },
  "path" : "path",
  "solverprototxtpath" : "solverprototxtpath",
  "framework" : "TensorFlow",
  "tfmainContent" : "tfmainContent",
  "frameworkVersion" : "frameworkVersion",
  "name" : "name",
  "trainTestContent" : "trainTestContent"
}, {
  "inferenceprototxtpath" : "inferenceprototxtpath",
  "tfmainpath" : "tfmainpath",
  "description" : "description",
  "solverContent" : "solverContent",
  "inferenceContent" : "inferenceContent",
  "traintestprototxtpath" : "traintestprototxtpath",
  "hyperparameter" : {
    "learningrate" : 0.8008282,
    "l2_regularization" : 6.84685269835264,
    "maxiteration" : 2,
    "lambd" : 6.683562403749608,
    "centered" : true,
    "threshold_mode" : "threshold_mode",
    "epoch" : 7,
    "lrpolicy" : "multistep",
    "nesterov" : true,
    "threshold" : 6.778324963048013,
    "lr_power" : 4.965218492984954,
    "cycle" : true,
    "dampening" : 6.438423552598547,
    "epsilon" : 1.2315135367772556,
    "mode" : "mode",
    "l1_regularization" : 1.4894159098541704,
    "solvertype" : "AdaDelta",
    "lr_decay" : 9.369310271410669,
    "amsgrad" : true,
    "beta1" : 7.457744773683766,
    "beta2" : 1.1730742509559433,
    "t_max" : 3,
    "alpha" : 8.762042012749001,
    "stepvalues" : "2000,4000,6000",
    "optdecay" : 7.386281948385884,
    "patience" : 2,
    "cooldown" : 6,
    "hiddenstatesize" : 4,
    "power" : 2.027123023002322,
    "weightdecay" : 1.4658129,
    "factor" : 1.284659006116532,
    "staircase" : "staircase",
    "decayrate" : 5.962134,
    "decaysteps" : 5.63737665663332876420099637471139430999755859375,
    "eps" : 5.944895607614016,
    "eta_min" : 6.965117697638846,
    "momentum" : 6.0274563,
    "end_learning_rate" : 5.025004791520295,
    "rho" : 9.965781217890562,
    "accumulator" : 1.0246457001441578,
    "t0" : 9.018348186070783,
    "stepsize" : 9,
    "gamma" : 3.616076749251911
  },
  "path" : "path",
  "solverprototxtpath" : "solverprototxtpath",
  "framework" : "TensorFlow",
  "tfmainContent" : "tfmainContent",
  "frameworkVersion" : "frameworkVersion",
  "name" : "name",
  "trainTestContent" : "trainTestContent"
} ]

Produces

This API call produces the following media types according to the Accept request header; the media type will be conveyed by the Content-Type response header.

Responses

200

Successful response that contains the resulting deep learning model templates.

400

Bad request. The request was not formatted correctly.

401

Authentication error. The request was denied.

403

Forbidden. The request was denied.

404

The requested resource was not found.

500

An unexpected error occurred.

Up
get /modeltemplates/files/{filename}
Retrieves the specified model template file contents (getModelTemplateFileContentByName)
Returns the contents of a specified model template file.

Path parameters

filename (required)
Path Parameter — The model template file name.

Consumes

This API call consumes the following media types via the Content-Type request header:

Return type

String

Example data

Content-Type: application/json
""

Produces

This API call produces the following media types according to the Accept request header; the media type will be conveyed by the Content-Type response header.

Responses

200

Successful response that contains the resulting contents of the specified model template file. String

400

Bad request. The request was not formatted correctly.

401

Authentication error. The request was denied.

403

Forbidden. The request was denied.

404

The requested resource was not found.

500

An unexpected error occurred.

Up
get /modeltemplates/{modeltemplatename}/files
Retrieves model template files (getModelTemplateFiles)
Returns full list of the files related with the specified model template.

Path parameters

modeltemplatename (required)
Path Parameter — The deep learning model template name.

Consumes

This API call consumes the following media types via the Content-Type request header:

Return type

String

Example data

Content-Type: application/json
""

Produces

This API call produces the following media types according to the Accept request header; the media type will be conveyed by the Content-Type response header.

Responses

200

Successful response that contains the resulting files related with the specified model template. String

400

Bad request. The request was not formatted correctly.

401

Authentication error. The request was denied.

403

Forbidden. The request was denied.

404

The requested resource was not found.

500

An unexpected error occurred.

Up
put /modeltemplates/{modeltemplatename}
Modifies a deep learning model template (updateModelTemplate)
Modifies a deep learning model template.

Path parameters

modeltemplatename (required)
Path Parameter — The deep learning model template name.

Consumes

This API call consumes the following media types via the Content-Type request header:

Request body

modeltemplate ModelTemplateDetail (required)
Body Parameter — The deep learning model template information.

Produces

This API call produces the following media types according to the Accept request header; the media type will be conveyed by the Content-Type response header.

Responses

200

The deep learning model template is modified on the server.

400

Bad request. The request was not formatted correctly.

401

Authentication error. The request was denied.

403

Forbidden. The request was denied.

404

The requested resource was not found.

500

An unexpected error occurred.

ModelTrainings

Up
delete /models/{modelname}/trainings/{trainingname}
Delete a model training (delModelTraining)
Deletes a single deep learning model training.

Path parameters

modelname (required)
Path Parameter — The deep learning model name.
trainingname (required)
Path Parameter — The deep learning training name.

Consumes

This API call consumes the following media types via the Content-Type request header:

Produces

This API call produces the following media types according to the Accept request header; the media type will be conveyed by the Content-Type response header.

Responses

200

Successfully deleted the deep learning model training.

400

The request format is invalid.

401

Authentication error. The request was denied.

403

Forbidden. The request was denied.

404

The requested resource is not found.

409

Conflict. The requested resource cannot be deleted because it is in use.

500

An unexpected error occurred.

Up
get /models/{modelname}/trainingnames
Get training names of all trainings for a specified model (getModelTrainingNames)
Get training names of all trainings for a specified model.

Path parameters

modelname (required)
Path Parameter — The deep learning model name.

Consumes

This API call consumes the following media types via the Content-Type request header:

Return type

array[String]

Example data

Content-Type: application/json
[ "", "" ]

Produces

This API call produces the following media types according to the Accept request header; the media type will be conveyed by the Content-Type response header.

Responses

200

Successful response containing a detailed list of all training names associated with a model.

400

Bad request. The request was not formatted correctly.

401

Authentication error. The request was denied.

403

Forbidden. The request was denied.

404

The requested resource was not found.

500

An unexpected error occurred.

Up
get /models/{modelname}/trainings/{trainingname}/weightfile
Get weight files for a model training (getModelTrainingWeightfiles)
Retrieves weight files for a deep learning model training.

Path parameters

modelname (required)
Path Parameter — The deep learning model name.
trainingname (required)
Path Parameter — The deep learning training name.

Consumes

This API call consumes the following media types via the Content-Type request header:

Return type

String

Example data

Content-Type: application/json
""

Produces

This API call produces the following media types according to the Accept request header; the media type will be conveyed by the Content-Type response header.

Responses

200

Successful response containing the weight file name. String

400

Bad request. The request was not formatted correctly.

401

Authentication error. The request was denied.

403

Forbidden. The request was denied.

404

The requested resource was not found.

500

An unexpected error occurred.

Up
get /models/{modelname}/trainings/{trainingname}
Get status of the specified training for a specified model (getModelTrainingbyName)
Get status of the specified training for a specified model.

Path parameters

modelname (required)
Path Parameter — The deep learning model name.
trainingname (required)
Path Parameter — The deep learning training name.

Consumes

This API call consumes the following media types via the Content-Type request header:

Return type

TrainDetail

Example data

Content-Type: application/json
{
  "model" : "model",
  "trainingParameters" : {
    "wfinit" : "wfinit",
    "testInterval" : 1,
    "testIteration" : 5,
    "dlFramework" : "TensorFlow",
    "sigId" : "sigId",
    "appURL" : "appURL",
    "sigMasterUrl" : "sigMasterUrl",
    "clusterSize" : 6,
    "wtURL" : "wtURL",
    "wtfolder" : "wtfolder",
    "driverid" : "driverid",
    "gpuRatio" : 0,
    "sigName" : "sigName",
    "createTime" : "createTime",
    "trainName" : "trainName",
    "appid" : "appid",
    "syncMode" : "SYNC",
    "progress" : 5,
    "cmd" : "cmd",
    "historyServerUrl" : "historyServerUrl",
    "user" : "user",
    "status" : "status"
  },
  "dataset" : "dataset"
}

Produces

This API call produces the following media types according to the Accept request header; the media type will be conveyed by the Content-Type response header.

Responses

200

Successful response containing a training with a specified training name associated with a model. TrainDetail

400

Bad request. The request was not formatted correctly.

401

Authentication error. The request was denied.

403

Forbidden. The request was denied.

404

The requested resource is not found.

500

An unexpected error occurred.

Up
get /models/{modelname}/trainings
Get status of all trainings for a specified model (getModelTrainings)
Get status of all trainings for a specified model.

Path parameters

modelname (required)
Path Parameter — The deep learning model name.

Consumes

This API call consumes the following media types via the Content-Type request header:

Return type

array[TrainDetail]

Example data

Content-Type: application/json
[ {
  "model" : "model",
  "trainingParameters" : {
    "wfinit" : "wfinit",
    "testInterval" : 1,
    "testIteration" : 5,
    "dlFramework" : "TensorFlow",
    "sigId" : "sigId",
    "appURL" : "appURL",
    "sigMasterUrl" : "sigMasterUrl",
    "clusterSize" : 6,
    "wtURL" : "wtURL",
    "wtfolder" : "wtfolder",
    "driverid" : "driverid",
    "gpuRatio" : 0,
    "sigName" : "sigName",
    "createTime" : "createTime",
    "trainName" : "trainName",
    "appid" : "appid",
    "syncMode" : "SYNC",
    "progress" : 5,
    "cmd" : "cmd",
    "historyServerUrl" : "historyServerUrl",
    "user" : "user",
    "status" : "status"
  },
  "dataset" : "dataset"
}, {
  "model" : "model",
  "trainingParameters" : {
    "wfinit" : "wfinit",
    "testInterval" : 1,
    "testIteration" : 5,
    "dlFramework" : "TensorFlow",
    "sigId" : "sigId",
    "appURL" : "appURL",
    "sigMasterUrl" : "sigMasterUrl",
    "clusterSize" : 6,
    "wtURL" : "wtURL",
    "wtfolder" : "wtfolder",
    "driverid" : "driverid",
    "gpuRatio" : 0,
    "sigName" : "sigName",
    "createTime" : "createTime",
    "trainName" : "trainName",
    "appid" : "appid",
    "syncMode" : "SYNC",
    "progress" : 5,
    "cmd" : "cmd",
    "historyServerUrl" : "historyServerUrl",
    "user" : "user",
    "status" : "status"
  },
  "dataset" : "dataset"
} ]

Produces

This API call produces the following media types according to the Accept request header; the media type will be conveyed by the Content-Type response header.

Responses

200

Successful response containing a detailed list of all trainings associated with a model.

400

Bad request. The request was not formatted correctly.

401

Authentication error. The request was denied.

403

Forbidden. The request was denied.

404

The requested resource was not found.

500

An unexpected error occurred.

Up
post /models/{modelname}/trainings
Start a new model training task (startModelTraining)
Start a new model training task.

Path parameters

modelname (required)
Path Parameter — The deep learning model name.

Consumes

This API call consumes the following media types via the Content-Type request header:

Request body

trainingParameters TrainingCreateParam (required)
Body Parameter — The training parameters.

Produces

This API call produces the following media types according to the Accept request header; the media type will be conveyed by the Content-Type response header.

Responses

200

Successfully started model training.

400

Bad request. The request was not formatted correctly.

401

Authentication error. The request was denied.

403

Forbidden. The request was denied.

404

The requested deep learning model name was not found.

500

An unexpected error occurred.

Up
put /models/{modelname}/trainings/{trainingname}/stop
Stops a model training task (stopModelTraining)
Stops a running deep learning model training task.

Path parameters

modelname (required)
Path Parameter — The deep learning model name.
trainingname (required)
Path Parameter — The deep learning training name.

Consumes

This API call consumes the following media types via the Content-Type request header:

Produces

This API call produces the following media types according to the Accept request header; the media type will be conveyed by the Content-Type response header.

Responses

200

Successfully stopped the training job.

400

Bad request. The request was not formatted correctly.

401

Authentication error. The request was denied.

403

Forbidden. The request was denied.

404

The requested resource was not found.

500

An unexpected error occurred.

ModelTunings

Up
put /models/{modelname}/hypersearch/{tuningname}/create/{newmodelname}
Create a new model using the tuning result (createModelUsingTuningResult)
Create a new model using the tuning result.

Path parameters

modelname (required)
Path Parameter — The deep learning model name.
tuningname (required)
Path Parameter — The deep learning tuning name.
newmodelname (required)
Path Parameter — The deep learning new created model name.

Consumes

This API call consumes the following media types via the Content-Type request header:

Produces

This API call produces the following media types according to the Accept request header; the media type will be conveyed by the Content-Type response header.

Responses

201

Successfully created a new model using the tuning result.

400

Bad request. The request was not formatted correctly.

401

Authentication error. The request was denied.

403

Forbidden. The request was denied.

404

The requested resource was not found.

500

An unexpected error occurred.

Up
delete /models/{modelname}/hypersearch/{tuningname}
Deletes a model tuning (deleteModelAutoTuning)
Deletes a model tuning.

Path parameters

modelname (required)
Path Parameter — The deep learning model name.
tuningname (required)
Path Parameter — The deep learning tuning name.

Consumes

This API call consumes the following media types via the Content-Type request header:

Produces

This API call produces the following media types according to the Accept request header; the media type will be conveyed by the Content-Type response header.

Responses

200

Successfully deleted the deep learning model tuning.

400

The request format is invalid.

401

Authentication error. The request was denied.

403

Forbidden. The request was denied.

404

The requested resource is not found.

409

Conflict. The requested resource cannot be deleted because it is in use.

500

An unexpected error occurred.

Up
get /models/{modelname}/hypersearch
Retrieve all tunings for a model (getModelAutoTuningStatus)
Returns full listing of all tunings for a deep learning model.

Path parameters

modelname (required)
Path Parameter — The deep learning model name.

Consumes

This API call consumes the following media types via the Content-Type request header:

Return type

array[HpoTaskDetail]

Example data

Content-Type: application/json
[ {
  "input" : {
    "modelName" : "modelName",
    "algoDef" : {
      "hyperbandEta" : 7.386281948385884,
      "algoParams" : [ {
        "name" : "name",
        "value" : "value"
      }, {
        "name" : "name",
        "value" : "value"
      } ],
      "maxRunTime" : 3,
      "maxJobNum" : 2,
      "maxParalleJobNum" : 4,
      "algorithm" : "algorithm",
      "objective" : "Maximize"
    },
    "hpoName" : "hpoName",
    "experiments" : [ {
      "fixedHyperParams" : [ {
        "fixedVal" : "fixedVal",
        "dataType" : "dataType",
        "name" : "name"
      }, {
        "fixedVal" : "fixedVal",
        "dataType" : "dataType",
        "name" : "name"
      } ],
      "id" : 1
    }, {
      "fixedHyperParams" : [ {
        "fixedVal" : "fixedVal",
        "dataType" : "dataType",
        "name" : "name"
      }, {
        "fixedVal" : "fixedVal",
        "dataType" : "dataType",
        "name" : "name"
      } ],
      "id" : 1
    } ],
    "resDef" : {
      "resourceInstanceId" : "resourceInstanceId",
      "framework" : "Caffe",
      "maxiteration" : "maxiteration",
      "initWeightPath" : "initWeightPath",
      "syncMode" : "SYNC",
      "gpuNum" : 7,
      "workerNum" : 9,
      "distribute" : true,
      "batchsize" : 32,
      "miniteration" : "miniteration"
    },
    "hyperParams" : [ {
      "maxIntVal" : 5,
      "fixedVal" : "fixedVal",
      "minIntVal" : 1,
      "dataType" : "int",
      "userDefined" : true,
      "discreateStrVal" : [ "discreateStrVal", "discreateStrVal" ],
      "type" : "range",
      "discreteIntVal" : [ 2, 2 ],
      "maxDbVal" : 6.027456183070403,
      "name" : "name",
      "step" : "step",
      "power" : "power",
      "discreteDbVal" : [ 5.637376656633329, 5.637376656633329 ],
      "minDbVal" : 0.8008281904610115
    }, {
      "maxIntVal" : 5,
      "fixedVal" : "fixedVal",
      "minIntVal" : 1,
      "dataType" : "int",
      "userDefined" : true,
      "discreateStrVal" : [ "discreateStrVal", "discreateStrVal" ],
      "type" : "range",
      "discreteIntVal" : [ 2, 2 ],
      "maxDbVal" : 6.027456183070403,
      "name" : "name",
      "step" : "step",
      "power" : "power",
      "discreteDbVal" : [ 5.637376656633329, 5.637376656633329 ],
      "minDbVal" : 0.8008281904610115
    } ]
  },
  "creator" : "creator",
  "createtime" : "createtime",
  "sigName" : "sigName",
  "sigId" : "sigId",
  "state" : "RUNNING",
  "searchGrid" : {
    "running" : 7,
    "duration" : "duration",
    "experiments" : [ {
      "maxiteration" : 6,
      "driverId" : "driverId",
      "appId" : "appId",
      "metricVal" : 1.4894159098541704,
      "startTime" : "startTime",
      "id" : 1,
      "state" : "state",
      "endTime" : "endTime",
      "hyperParams" : {
        "maxIntVal" : 5,
        "fixedVal" : "fixedVal",
        "minIntVal" : 1,
        "dataType" : "int",
        "userDefined" : true,
        "discreateStrVal" : [ "discreateStrVal", "discreateStrVal" ],
        "type" : "range",
        "discreteIntVal" : [ 2, 2 ],
        "maxDbVal" : 6.027456183070403,
        "name" : "name",
        "step" : "step",
        "power" : "power",
        "discreteDbVal" : [ 5.637376656633329, 5.637376656633329 ],
        "minDbVal" : 0.8008281904610115
      }
    }, {
      "maxiteration" : 6,
      "driverId" : "driverId",
      "appId" : "appId",
      "metricVal" : 1.4894159098541704,
      "startTime" : "startTime",
      "id" : 1,
      "state" : "state",
      "endTime" : "endTime",
      "hyperParams" : {
        "maxIntVal" : 5,
        "fixedVal" : "fixedVal",
        "minIntVal" : 1,
        "dataType" : "int",
        "userDefined" : true,
        "discreateStrVal" : [ "discreateStrVal", "discreateStrVal" ],
        "type" : "range",
        "discreteIntVal" : [ 2, 2 ],
        "maxDbVal" : 6.027456183070403,
        "name" : "name",
        "step" : "step",
        "power" : "power",
        "discreteDbVal" : [ 5.637376656633329, 5.637376656633329 ],
        "minDbVal" : 0.8008281904610115
      }
    } ],
    "progress" : "progress",
    "best" : {
      "maxiteration" : 6,
      "driverId" : "driverId",
      "appId" : "appId",
      "metricVal" : 1.4894159098541704,
      "startTime" : "startTime",
      "id" : 1,
      "state" : "state",
      "endTime" : "endTime",
      "hyperParams" : {
        "maxIntVal" : 5,
        "fixedVal" : "fixedVal",
        "minIntVal" : 1,
        "dataType" : "int",
        "userDefined" : true,
        "discreateStrVal" : [ "discreateStrVal", "discreateStrVal" ],
        "type" : "range",
        "discreteIntVal" : [ 2, 2 ],
        "maxDbVal" : 6.027456183070403,
        "name" : "name",
        "step" : "step",
        "power" : "power",
        "discreteDbVal" : [ 5.637376656633329, 5.637376656633329 ],
        "minDbVal" : 0.8008281904610115
      }
    },
    "failed" : 4,
    "complete" : 1
  },
  "consumerName" : "consumerName"
}, {
  "input" : {
    "modelName" : "modelName",
    "algoDef" : {
      "hyperbandEta" : 7.386281948385884,
      "algoParams" : [ {
        "name" : "name",
        "value" : "value"
      }, {
        "name" : "name",
        "value" : "value"
      } ],
      "maxRunTime" : 3,
      "maxJobNum" : 2,
      "maxParalleJobNum" : 4,
      "algorithm" : "algorithm",
      "objective" : "Maximize"
    },
    "hpoName" : "hpoName",
    "experiments" : [ {
      "fixedHyperParams" : [ {
        "fixedVal" : "fixedVal",
        "dataType" : "dataType",
        "name" : "name"
      }, {
        "fixedVal" : "fixedVal",
        "dataType" : "dataType",
        "name" : "name"
      } ],
      "id" : 1
    }, {
      "fixedHyperParams" : [ {
        "fixedVal" : "fixedVal",
        "dataType" : "dataType",
        "name" : "name"
      }, {
        "fixedVal" : "fixedVal",
        "dataType" : "dataType",
        "name" : "name"
      } ],
      "id" : 1
    } ],
    "resDef" : {
      "resourceInstanceId" : "resourceInstanceId",
      "framework" : "Caffe",
      "maxiteration" : "maxiteration",
      "initWeightPath" : "initWeightPath",
      "syncMode" : "SYNC",
      "gpuNum" : 7,
      "workerNum" : 9,
      "distribute" : true,
      "batchsize" : 32,
      "miniteration" : "miniteration"
    },
    "hyperParams" : [ {
      "maxIntVal" : 5,
      "fixedVal" : "fixedVal",
      "minIntVal" : 1,
      "dataType" : "int",
      "userDefined" : true,
      "discreateStrVal" : [ "discreateStrVal", "discreateStrVal" ],
      "type" : "range",
      "discreteIntVal" : [ 2, 2 ],
      "maxDbVal" : 6.027456183070403,
      "name" : "name",
      "step" : "step",
      "power" : "power",
      "discreteDbVal" : [ 5.637376656633329, 5.637376656633329 ],
      "minDbVal" : 0.8008281904610115
    }, {
      "maxIntVal" : 5,
      "fixedVal" : "fixedVal",
      "minIntVal" : 1,
      "dataType" : "int",
      "userDefined" : true,
      "discreateStrVal" : [ "discreateStrVal", "discreateStrVal" ],
      "type" : "range",
      "discreteIntVal" : [ 2, 2 ],
      "maxDbVal" : 6.027456183070403,
      "name" : "name",
      "step" : "step",
      "power" : "power",
      "discreteDbVal" : [ 5.637376656633329, 5.637376656633329 ],
      "minDbVal" : 0.8008281904610115
    } ]
  },
  "creator" : "creator",
  "createtime" : "createtime",
  "sigName" : "sigName",
  "sigId" : "sigId",
  "state" : "RUNNING",
  "searchGrid" : {
    "running" : 7,
    "duration" : "duration",
    "experiments" : [ {
      "maxiteration" : 6,
      "driverId" : "driverId",
      "appId" : "appId",
      "metricVal" : 1.4894159098541704,
      "startTime" : "startTime",
      "id" : 1,
      "state" : "state",
      "endTime" : "endTime",
      "hyperParams" : {
        "maxIntVal" : 5,
        "fixedVal" : "fixedVal",
        "minIntVal" : 1,
        "dataType" : "int",
        "userDefined" : true,
        "discreateStrVal" : [ "discreateStrVal", "discreateStrVal" ],
        "type" : "range",
        "discreteIntVal" : [ 2, 2 ],
        "maxDbVal" : 6.027456183070403,
        "name" : "name",
        "step" : "step",
        "power" : "power",
        "discreteDbVal" : [ 5.637376656633329, 5.637376656633329 ],
        "minDbVal" : 0.8008281904610115
      }
    }, {
      "maxiteration" : 6,
      "driverId" : "driverId",
      "appId" : "appId",
      "metricVal" : 1.4894159098541704,
      "startTime" : "startTime",
      "id" : 1,
      "state" : "state",
      "endTime" : "endTime",
      "hyperParams" : {
        "maxIntVal" : 5,
        "fixedVal" : "fixedVal",
        "minIntVal" : 1,
        "dataType" : "int",
        "userDefined" : true,
        "discreateStrVal" : [ "discreateStrVal", "discreateStrVal" ],
        "type" : "range",
        "discreteIntVal" : [ 2, 2 ],
        "maxDbVal" : 6.027456183070403,
        "name" : "name",
        "step" : "step",
        "power" : "power",
        "discreteDbVal" : [ 5.637376656633329, 5.637376656633329 ],
        "minDbVal" : 0.8008281904610115
      }
    } ],
    "progress" : "progress",
    "best" : {
      "maxiteration" : 6,
      "driverId" : "driverId",
      "appId" : "appId",
      "metricVal" : 1.4894159098541704,
      "startTime" : "startTime",
      "id" : 1,
      "state" : "state",
      "endTime" : "endTime",
      "hyperParams" : {
        "maxIntVal" : 5,
        "fixedVal" : "fixedVal",
        "minIntVal" : 1,
        "dataType" : "int",
        "userDefined" : true,
        "discreateStrVal" : [ "discreateStrVal", "discreateStrVal" ],
        "type" : "range",
        "discreteIntVal" : [ 2, 2 ],
        "maxDbVal" : 6.027456183070403,
        "name" : "name",
        "step" : "step",
        "power" : "power",
        "discreteDbVal" : [ 5.637376656633329, 5.637376656633329 ],
        "minDbVal" : 0.8008281904610115
      }
    },
    "failed" : 4,
    "complete" : 1
  },
  "consumerName" : "consumerName"
} ]

Produces

This API call produces the following media types according to the Accept request header; the media type will be conveyed by the Content-Type response header.

Responses

200

Successful response that contains a list of all tunings for a deep learning model.

400

Bad request. The request was not formatted correctly.

401

Authentication error. The request was denied.

403

Forbidden. The request was denied.

404

The requested resource was not found.

500

An unexpected error occurred.

Up
get /models/{modelname}/hypersearch/{tuningname}
Retrieves tuning details (getModelAutoTuningStatusByName)
Returns full details for a deep learning model tuning.

Path parameters

modelname (required)
Path Parameter — The deep learning model name.
tuningname (required)
Path Parameter — The deep learning tuning name.

Consumes

This API call consumes the following media types via the Content-Type request header:

Return type

HpoTaskDetail

Example data

Content-Type: application/json
{
  "input" : {
    "modelName" : "modelName",
    "algoDef" : {
      "hyperbandEta" : 7.386281948385884,
      "algoParams" : [ {
        "name" : "name",
        "value" : "value"
      }, {
        "name" : "name",
        "value" : "value"
      } ],
      "maxRunTime" : 3,
      "maxJobNum" : 2,
      "maxParalleJobNum" : 4,
      "algorithm" : "algorithm",
      "objective" : "Maximize"
    },
    "hpoName" : "hpoName",
    "experiments" : [ {
      "fixedHyperParams" : [ {
        "fixedVal" : "fixedVal",
        "dataType" : "dataType",
        "name" : "name"
      }, {
        "fixedVal" : "fixedVal",
        "dataType" : "dataType",
        "name" : "name"
      } ],
      "id" : 1
    }, {
      "fixedHyperParams" : [ {
        "fixedVal" : "fixedVal",
        "dataType" : "dataType",
        "name" : "name"
      }, {
        "fixedVal" : "fixedVal",
        "dataType" : "dataType",
        "name" : "name"
      } ],
      "id" : 1
    } ],
    "resDef" : {
      "resourceInstanceId" : "resourceInstanceId",
      "framework" : "Caffe",
      "maxiteration" : "maxiteration",
      "initWeightPath" : "initWeightPath",
      "syncMode" : "SYNC",
      "gpuNum" : 7,
      "workerNum" : 9,
      "distribute" : true,
      "batchsize" : 32,
      "miniteration" : "miniteration"
    },
    "hyperParams" : [ {
      "maxIntVal" : 5,
      "fixedVal" : "fixedVal",
      "minIntVal" : 1,
      "dataType" : "int",
      "userDefined" : true,
      "discreateStrVal" : [ "discreateStrVal", "discreateStrVal" ],
      "type" : "range",
      "discreteIntVal" : [ 2, 2 ],
      "maxDbVal" : 6.027456183070403,
      "name" : "name",
      "step" : "step",
      "power" : "power",
      "discreteDbVal" : [ 5.637376656633329, 5.637376656633329 ],
      "minDbVal" : 0.8008281904610115
    }, {
      "maxIntVal" : 5,
      "fixedVal" : "fixedVal",
      "minIntVal" : 1,
      "dataType" : "int",
      "userDefined" : true,
      "discreateStrVal" : [ "discreateStrVal", "discreateStrVal" ],
      "type" : "range",
      "discreteIntVal" : [ 2, 2 ],
      "maxDbVal" : 6.027456183070403,
      "name" : "name",
      "step" : "step",
      "power" : "power",
      "discreteDbVal" : [ 5.637376656633329, 5.637376656633329 ],
      "minDbVal" : 0.8008281904610115
    } ]
  },
  "creator" : "creator",
  "createtime" : "createtime",
  "sigName" : "sigName",
  "sigId" : "sigId",
  "state" : "RUNNING",
  "searchGrid" : {
    "running" : 7,
    "duration" : "duration",
    "experiments" : [ {
      "maxiteration" : 6,
      "driverId" : "driverId",
      "appId" : "appId",
      "metricVal" : 1.4894159098541704,
      "startTime" : "startTime",
      "id" : 1,
      "state" : "state",
      "endTime" : "endTime",
      "hyperParams" : {
        "maxIntVal" : 5,
        "fixedVal" : "fixedVal",
        "minIntVal" : 1,
        "dataType" : "int",
        "userDefined" : true,
        "discreateStrVal" : [ "discreateStrVal", "discreateStrVal" ],
        "type" : "range",
        "discreteIntVal" : [ 2, 2 ],
        "maxDbVal" : 6.027456183070403,
        "name" : "name",
        "step" : "step",
        "power" : "power",
        "discreteDbVal" : [ 5.637376656633329, 5.637376656633329 ],
        "minDbVal" : 0.8008281904610115
      }
    }, {
      "maxiteration" : 6,
      "driverId" : "driverId",
      "appId" : "appId",
      "metricVal" : 1.4894159098541704,
      "startTime" : "startTime",
      "id" : 1,
      "state" : "state",
      "endTime" : "endTime",
      "hyperParams" : {
        "maxIntVal" : 5,
        "fixedVal" : "fixedVal",
        "minIntVal" : 1,
        "dataType" : "int",
        "userDefined" : true,
        "discreateStrVal" : [ "discreateStrVal", "discreateStrVal" ],
        "type" : "range",
        "discreteIntVal" : [ 2, 2 ],
        "maxDbVal" : 6.027456183070403,
        "name" : "name",
        "step" : "step",
        "power" : "power",
        "discreteDbVal" : [ 5.637376656633329, 5.637376656633329 ],
        "minDbVal" : 0.8008281904610115
      }
    } ],
    "progress" : "progress",
    "best" : {
      "maxiteration" : 6,
      "driverId" : "driverId",
      "appId" : "appId",
      "metricVal" : 1.4894159098541704,
      "startTime" : "startTime",
      "id" : 1,
      "state" : "state",
      "endTime" : "endTime",
      "hyperParams" : {
        "maxIntVal" : 5,
        "fixedVal" : "fixedVal",
        "minIntVal" : 1,
        "dataType" : "int",
        "userDefined" : true,
        "discreateStrVal" : [ "discreateStrVal", "discreateStrVal" ],
        "type" : "range",
        "discreteIntVal" : [ 2, 2 ],
        "maxDbVal" : 6.027456183070403,
        "name" : "name",
        "step" : "step",
        "power" : "power",
        "discreteDbVal" : [ 5.637376656633329, 5.637376656633329 ],
        "minDbVal" : 0.8008281904610115
      }
    },
    "failed" : 4,
    "complete" : 1
  },
  "consumerName" : "consumerName"
}

Produces

This API call produces the following media types according to the Accept request header; the media type will be conveyed by the Content-Type response header.

Responses

200

Successful response that contains tuning details. HpoTaskDetail

400

Bad request. The request was not formatted correctly.

401

Authentication error. The request was denied.

403

Forbidden. The request was denied.

404

The requested resource was not found.

500

An unexpected error occurred.

Up
post /models/{modelname}/hypersearch
Creates new model tuning (startModelAutoTuning)
Crates a new deep learning model tuning.

Path parameters

modelname (required)
Path Parameter — The deep learning model name.

Consumes

This API call consumes the following media types via the Content-Type request header:

Request body

tuningOpts HpoTaskInput (required)
Body Parameter — The tuning parameters required to start model tuning.

Produces

This API call produces the following media types according to the Accept request header; the media type will be conveyed by the Content-Type response header.

Responses

200

The deep learning model auto tuning has started.

400

Bad request. The request was not formatted correctly.

401

Authentication error. The request was denied.

403

Forbidden. The request was denied.

404

The requested resource was not found.

409

Conflict. The requested resource already exists.

500

An unexpected error occurred.

Up
put /models/{modelname}/hypersearch/{tuningname}/stop
Stops a model tuning task (stopModelAutoTuning)
Stops a running deep learning model tuning task.

Path parameters

modelname (required)
Path Parameter — The deep learning model name.
tuningname (required)
Path Parameter — The deep learning tuning name.

Consumes

This API call consumes the following media types via the Content-Type request header:

Produces

This API call produces the following media types according to the Accept request header; the media type will be conveyed by the Content-Type response header.

Responses

200

Successfully stopped the tuning job.

400

Bad request. The request was not formatted correctly.

401

Authentication error. The request was denied.

403

Forbidden. The request was denied.

404

The requested resource was not found.

500

An unexpected error occurred.

Up
put /models/{modelname}/hypersearch/{tuningname}/force
Stop a model tuning forcely (stopModelAutoTuningForce)
Stops a running deep learning model tuning task forcely

Path parameters

modelname (required)
Path Parameter — The deep learning model name.
tuningname (required)
Path Parameter — The deep learning tuning name.

Consumes

This API call consumes the following media types via the Content-Type request header:

Produces

This API call produces the following media types according to the Accept request header; the media type will be conveyed by the Content-Type response header.

Responses

200

Successfully stopped the hpo task forcely.

400

Bad request. The request was not formatted correctly.

401

Authentication error. The request was denied.

403

Forbidden. The request was denied.

404

The requested resource was not found.

500

An unexpected error occurred.

Up
put /models/{modelname}/hypersearch/{tuningname}/update
Update the model using the tuning result (updateModelUsingTuningResult)
Update the model using the tuning result.

Path parameters

modelname (required)
Path Parameter — The deep learning model name.
tuningname (required)
Path Parameter — The deep learning tuning name.

Consumes

This API call consumes the following media types via the Content-Type request header:

Produces

This API call produces the following media types according to the Accept request header; the media type will be conveyed by the Content-Type response header.

Responses

200

Successfully updated the model using the tuning result.

400

Bad request. The request was not formatted correctly.

401

Authentication error. The request was denied.

403

Forbidden. The request was denied.

404

The requested resource was not found.

500

An unexpected error occurred.

ModelValidations

Up
delete /models/{modelname}/validations/{valname}
Deletes a validation for a model (deleteValidation)
Deletes a validation for a deep learning model.

Path parameters

modelname (required)
Path Parameter — The deep learning model name to delete.
valname (required)
Path Parameter — The deep learning validation name to delete.

Consumes

This API call consumes the following media types via the Content-Type request header:

Produces

This API call produces the following media types according to the Accept request header; the media type will be conveyed by the Content-Type response header.

Responses

200

Successfully deleted the model validation.

400

The request format is invalid.

401

Authentication error. The request was denied.

403

Forbidden. The request was denied.

404

The requested resource is not found.

409

Conflict. The requested resource cannot be deleted because it is in use.

500

An unexpected error occurred.

Up
get /models/{modelname}/validations
Retrieves all model validations (getValidations)
Returns full listing of all the validations for a deep learning model.

Path parameters

modelname (required)
Path Parameter — The deep learning model name

Consumes

This API call consumes the following media types via the Content-Type request header:

Return type

array[ValidateDetail]

Example data

Content-Type: application/json
[ {
  "valParameters" : {
    "valName" : "valName",
    "sigName" : "sigName",
    "createTime" : "createTime",
    "trainName" : "trainName",
    "sigId" : "sigId",
    "metrics" : [ "metrics", "metrics" ],
    "sigMasterUrl" : "sigMasterUrl",
    "user" : "user"
  },
  "driverId" : "driverId",
  "modelname" : "modelname",
  "appid" : "appid",
  "outPairs" : {
    "name" : "name",
    "value" : "value"
  },
  "appURL" : "appURL",
  "historyServerUrl" : "historyServerUrl",
  "dataSet" : "dataSet",
  "status" : "status"
}, {
  "valParameters" : {
    "valName" : "valName",
    "sigName" : "sigName",
    "createTime" : "createTime",
    "trainName" : "trainName",
    "sigId" : "sigId",
    "metrics" : [ "metrics", "metrics" ],
    "sigMasterUrl" : "sigMasterUrl",
    "user" : "user"
  },
  "driverId" : "driverId",
  "modelname" : "modelname",
  "appid" : "appid",
  "outPairs" : {
    "name" : "name",
    "value" : "value"
  },
  "appURL" : "appURL",
  "historyServerUrl" : "historyServerUrl",
  "dataSet" : "dataSet",
  "status" : "status"
} ]

Produces

This API call produces the following media types according to the Accept request header; the media type will be conveyed by the Content-Type response header.

Responses

200

List of all validations for the specified model.

400

Bad request. The request was not formatted correctly.

401

Authentication error. The request was denied.

403

Forbidden. The request was denied.

404

The requested resource was not found.

500

An unexpected error occurred.

Up
post /models/{modelname}/validations
Starts a new model validation (startValidation)
Starts a new validation for a deep learning model.

Path parameters

modelname (required)
Path Parameter — The deep learning model name.

Consumes

This API call consumes the following media types via the Content-Type request header:

Request body

valParams ValidationCreateParam (required)
Body Parameter — The validation parameters

Produces

This API call produces the following media types according to the Accept request header; the media type will be conveyed by the Content-Type response header.

Responses

200

Successfully started validation for a deep learning model.

400

Bad request. The request was not formatted correctly.

401

Authentication error. The request was denied.

403

Forbidden. The request was denied.

404

The requested resource was not round.

500

An unexpected error occurred.

Up
put /models/{modelname}/validations/{valname}/stop
Stops a model validation task (stopValidation)
Stops a running deep learning model validation task.

Path parameters

modelname (required)
Path Parameter — The deep learning model name.
valname (required)
Path Parameter — The deep learning validation name.

Consumes

This API call consumes the following media types via the Content-Type request header:

Produces

This API call produces the following media types according to the Accept request header; the media type will be conveyed by the Content-Type response header.

Responses

200

Successfully stopped the validation job.

400

Bad request. The request was not formatted correctly.

401

Authentication error. The request was denied.

403

Forbidden. The request was denied.

404

The requested resource was not found.

500

An unexpected error occurred.

Models

Up
post /models
Creates a new deep learning model (addModel)
Creates a new deep learning model.

Consumes

This API call consumes the following media types via the Content-Type request header:

Request body

model ModelCreateParam (required)
Body Parameter — The information that specifies the details of a deep learning model to create.

Produces

This API call produces the following media types according to the Accept request header; the media type will be conveyed by the Content-Type response header.

Responses

201

The deep learning model is created successfully.

400

The request format is invalid.

401

Authentication error. The request was denied.

403

Forbidden. The request was denied.

409

Conflict. The requested resource already exists.

500

An unexpected error occurred.

Up
delete /models/{modelname}
Deletes a deep learning model (deleteModel)
Deletes a deep learning model.

Path parameters

modelname (required)
Path Parameter — The deep learning model name.

Consumes

This API call consumes the following media types via the Content-Type request header:

Produces

This API call produces the following media types according to the Accept request header; the media type will be conveyed by the Content-Type response header.

Responses

200

OK. Successfully deleted the deep learning model.

400

The request format is invalid.

401

Authentication error. The request was denied.

403

Forbidden. The request was denied.

404

The requested resource is not found.

409

Conflict. The requested resource cannot be deleted because it is in use.

500

An unexpected error occurred.

Up
get /models/{modelname}
Retrieves details for a model (getModelByName)
Returns full details for a deep learning model.

Path parameters

modelname (required)
Path Parameter — The deep learning model name.

Consumes

This API call consumes the following media types via the Content-Type request header:

Return type

ModelDetail

Example data

Content-Type: application/json
{
  "wfinit" : "wfinit",
  "tmpfileContent" : "tmpfileContent",
  "tfmainpath" : "tfmainpath",
  "description" : "description",
  "solverContent" : "solverContent",
  "type" : "Training",
  "batchsize" : 32,
  "dimimage" : "dimimage",
  "hyperparameter" : {
    "learningrate" : 0.8008282,
    "l2_regularization" : 6.84685269835264,
    "maxiteration" : 2,
    "lambd" : 6.683562403749608,
    "centered" : true,
    "threshold_mode" : "threshold_mode",
    "epoch" : 7,
    "lrpolicy" : "multistep",
    "nesterov" : true,
    "threshold" : 6.778324963048013,
    "lr_power" : 4.965218492984954,
    "cycle" : true,
    "dampening" : 6.438423552598547,
    "epsilon" : 1.2315135367772556,
    "mode" : "mode",
    "l1_regularization" : 1.4894159098541704,
    "solvertype" : "AdaDelta",
    "lr_decay" : 9.369310271410669,
    "amsgrad" : true,
    "beta1" : 7.457744773683766,
    "beta2" : 1.1730742509559433,
    "t_max" : 3,
    "alpha" : 8.762042012749001,
    "stepvalues" : "2000,4000,6000",
    "optdecay" : 7.386281948385884,
    "patience" : 2,
    "cooldown" : 6,
    "hiddenstatesize" : 4,
    "power" : 2.027123023002322,
    "weightdecay" : 1.4658129,
    "factor" : 1.284659006116532,
    "staircase" : "staircase",
    "decayrate" : 5.962134,
    "decaysteps" : 5.63737665663332876420099637471139430999755859375,
    "eps" : 5.944895607614016,
    "eta_min" : 6.965117697638846,
    "momentum" : 6.0274563,
    "end_learning_rate" : 5.025004791520295,
    "rho" : 9.965781217890562,
    "accumulator" : 1.0246457001441578,
    "t0" : 9.018348186070783,
    "stepsize" : 9,
    "gamma" : 3.616076749251911
  },
  "sig" : "sig",
  "wtfolder" : "wtfolder",
  "path" : "path",
  "tfmainContent" : "tfmainContent",
  "frameworkVersion" : "frameworkVersion",
  "templatename" : "templatename",
  "distributeStrategy" : "distributeStrategy",
  "accelerator" : "Native",
  "signame" : "signame",
  "inferenceprototxtpath" : "inferenceprototxtpath",
  "tmpfilePath" : "tmpfilePath",
  "inferenceContent" : "inferenceContent",
  "traintestprototxtpath" : "traintestprototxtpath",
  "solverprototxtpath" : "solverprototxtpath",
  "framework" : "Caffe",
  "createTime" : "createTime",
  "name" : "name",
  "trainTestContent" : "trainTestContent",
  "dataset" : "dataset",
  "user" : "user"
}

Produces

This API call produces the following media types according to the Accept request header; the media type will be conveyed by the Content-Type response header.

Responses

200

Successful response that contains the resulting deep learning model. ModelDetail

400

Bad request. The request was not formatted correctly.

401

Authentication error. The request was denied.

404

The requested resource was not found.

500

An unexpected error occurred.

Up
get /models/files/{filename}
Retrieves the specified model file contents (getModelFileContentByName)
Returns the contents of a specified model file.

Path parameters

filename (required)
Path Parameter — The model file name.

Consumes

This API call consumes the following media types via the Content-Type request header:

Return type

String

Example data

Content-Type: application/json
""

Produces

This API call produces the following media types according to the Accept request header; the media type will be conveyed by the Content-Type response header.

Responses

200

Successful response that contains the resulting contents of the specified model file. String

400

Bad request. The request was not formatted correctly.

401

Authentication error. The request was denied.

403

Forbidden. The request was denied.

404

The requested resource was not found.

500

An unexpected error occurred.

Up
get /models/{modelname}/files
Retrieves model files (getModelFiles)
Returns full list of the files related with the specified model.

Path parameters

modelname (required)
Path Parameter — The deep learning model name.

Consumes

This API call consumes the following media types via the Content-Type request header:

Return type

String

Example data

Content-Type: application/json
""

Produces

This API call produces the following media types according to the Accept request header; the media type will be conveyed by the Content-Type response header.

Responses

200

Successful response that contains the resulting files related with the specified model. String

400

Bad request. The request was not formatted correctly.

401

Authentication error. The request was denied.

403

Forbidden. The request was denied.

404

The requested resource was not found.

500

An unexpected error occurred.

Up
get /models
Retrieves all models defined in the system (getModels)
Returns full listing of all the deep learning models defined in the system.

Consumes

This API call consumes the following media types via the Content-Type request header:

Return type

array[ModelDetail]

Example data

Content-Type: application/json
[ {
  "wfinit" : "wfinit",
  "tmpfileContent" : "tmpfileContent",
  "tfmainpath" : "tfmainpath",
  "description" : "description",
  "solverContent" : "solverContent",
  "type" : "Training",
  "batchsize" : 32,
  "dimimage" : "dimimage",
  "hyperparameter" : {
    "learningrate" : 0.8008282,
    "l2_regularization" : 6.84685269835264,
    "maxiteration" : 2,
    "lambd" : 6.683562403749608,
    "centered" : true,
    "threshold_mode" : "threshold_mode",
    "epoch" : 7,
    "lrpolicy" : "multistep",
    "nesterov" : true,
    "threshold" : 6.778324963048013,
    "lr_power" : 4.965218492984954,
    "cycle" : true,
    "dampening" : 6.438423552598547,
    "epsilon" : 1.2315135367772556,
    "mode" : "mode",
    "l1_regularization" : 1.4894159098541704,
    "solvertype" : "AdaDelta",
    "lr_decay" : 9.369310271410669,
    "amsgrad" : true,
    "beta1" : 7.457744773683766,
    "beta2" : 1.1730742509559433,
    "t_max" : 3,
    "alpha" : 8.762042012749001,
    "stepvalues" : "2000,4000,6000",
    "optdecay" : 7.386281948385884,
    "patience" : 2,
    "cooldown" : 6,
    "hiddenstatesize" : 4,
    "power" : 2.027123023002322,
    "weightdecay" : 1.4658129,
    "factor" : 1.284659006116532,
    "staircase" : "staircase",
    "decayrate" : 5.962134,
    "decaysteps" : 5.63737665663332876420099637471139430999755859375,
    "eps" : 5.944895607614016,
    "eta_min" : 6.965117697638846,
    "momentum" : 6.0274563,
    "end_learning_rate" : 5.025004791520295,
    "rho" : 9.965781217890562,
    "accumulator" : 1.0246457001441578,
    "t0" : 9.018348186070783,
    "stepsize" : 9,
    "gamma" : 3.616076749251911
  },
  "sig" : "sig",
  "wtfolder" : "wtfolder",
  "path" : "path",
  "tfmainContent" : "tfmainContent",
  "frameworkVersion" : "frameworkVersion",
  "templatename" : "templatename",
  "distributeStrategy" : "distributeStrategy",
  "accelerator" : "Native",
  "signame" : "signame",
  "inferenceprototxtpath" : "inferenceprototxtpath",
  "tmpfilePath" : "tmpfilePath",
  "inferenceContent" : "inferenceContent",
  "traintestprototxtpath" : "traintestprototxtpath",
  "solverprototxtpath" : "solverprototxtpath",
  "framework" : "Caffe",
  "createTime" : "createTime",
  "name" : "name",
  "trainTestContent" : "trainTestContent",
  "dataset" : "dataset",
  "user" : "user"
}, {
  "wfinit" : "wfinit",
  "tmpfileContent" : "tmpfileContent",
  "tfmainpath" : "tfmainpath",
  "description" : "description",
  "solverContent" : "solverContent",
  "type" : "Training",
  "batchsize" : 32,
  "dimimage" : "dimimage",
  "hyperparameter" : {
    "learningrate" : 0.8008282,
    "l2_regularization" : 6.84685269835264,
    "maxiteration" : 2,
    "lambd" : 6.683562403749608,
    "centered" : true,
    "threshold_mode" : "threshold_mode",
    "epoch" : 7,
    "lrpolicy" : "multistep",
    "nesterov" : true,
    "threshold" : 6.778324963048013,
    "lr_power" : 4.965218492984954,
    "cycle" : true,
    "dampening" : 6.438423552598547,
    "epsilon" : 1.2315135367772556,
    "mode" : "mode",
    "l1_regularization" : 1.4894159098541704,
    "solvertype" : "AdaDelta",
    "lr_decay" : 9.369310271410669,
    "amsgrad" : true,
    "beta1" : 7.457744773683766,
    "beta2" : 1.1730742509559433,
    "t_max" : 3,
    "alpha" : 8.762042012749001,
    "stepvalues" : "2000,4000,6000",
    "optdecay" : 7.386281948385884,
    "patience" : 2,
    "cooldown" : 6,
    "hiddenstatesize" : 4,
    "power" : 2.027123023002322,
    "weightdecay" : 1.4658129,
    "factor" : 1.284659006116532,
    "staircase" : "staircase",
    "decayrate" : 5.962134,
    "decaysteps" : 5.63737665663332876420099637471139430999755859375,
    "eps" : 5.944895607614016,
    "eta_min" : 6.965117697638846,
    "momentum" : 6.0274563,
    "end_learning_rate" : 5.025004791520295,
    "rho" : 9.965781217890562,
    "accumulator" : 1.0246457001441578,
    "t0" : 9.018348186070783,
    "stepsize" : 9,
    "gamma" : 3.616076749251911
  },
  "sig" : "sig",
  "wtfolder" : "wtfolder",
  "path" : "path",
  "tfmainContent" : "tfmainContent",
  "frameworkVersion" : "frameworkVersion",
  "templatename" : "templatename",
  "distributeStrategy" : "distributeStrategy",
  "accelerator" : "Native",
  "signame" : "signame",
  "inferenceprototxtpath" : "inferenceprototxtpath",
  "tmpfilePath" : "tmpfilePath",
  "inferenceContent" : "inferenceContent",
  "traintestprototxtpath" : "traintestprototxtpath",
  "solverprototxtpath" : "solverprototxtpath",
  "framework" : "Caffe",
  "createTime" : "createTime",
  "name" : "name",
  "trainTestContent" : "trainTestContent",
  "dataset" : "dataset",
  "user" : "user"
} ]

Produces

This API call produces the following media types according to the Accept request header; the media type will be conveyed by the Content-Type response header.

Responses

200

Successful response that contains the resulting deep learning models.

400

Bad request. The request was not formatted correctly.

401

Authentication error. The request was denied.

403

Forbidden. The request was denied.

500

An unexpected error occurred.

Up
put /models/{modelname}/files
Modifies a deep learning model file (saveModelFileContentByName)
Modifies a deep learning model file.

Path parameters

modelname (required)
Path Parameter — The deep learning model name.

Consumes

This API call consumes the following media types via the Content-Type request header:

Request body

model ModelDetail (required)
Body Parameter — The deep learning model information.

Produces

This API call produces the following media types according to the Accept request header; the media type will be conveyed by the Content-Type response header.

Responses

200

The deep learning model file is modified on the server.

400

Bad request. The request was not formatted correctly.

401

Authentication error. The request was denied.

403

Forbidden. The request was denied.

404

The requested resource was not found.

500

An unexpected error occurred.

Up
put /models/{modelname}
Modifies a deep learning model (updateModel)
Modifies a deep learning model.

Path parameters

modelname (required)
Path Parameter — The deep learning model name.

Consumes

This API call consumes the following media types via the Content-Type request header:

Request body

model ModelDetail (required)
Body Parameter — The deep learning model information.

Produces

This API call produces the following media types according to the Accept request header; the media type will be conveyed by the Content-Type response header.

Responses

200

The deep learning model is modified on the server.

400

Bad request. The request was not formatted correctly.

401

Authentication error. The request was denied.

403

Forbidden. The request was denied.

404

The requested resource was not found.

500

An unexpected error occurred.

Up
post /models/weightfile
Uploads a new weight file (uploadWf)
Upload a new weight file which can be used for trainings and inferences.

Consumes

This API call consumes the following media types via the Content-Type request header:

Form parameters

file (required)
Form Parameter — Weight file for model training or inference.

Produces

This API call produces the following media types according to the Accept request header; the media type will be conveyed by the Content-Type response header.

Responses

200

Successfully uploaded a new weight file.

400

The request format is invalid.

401

Authentication error. The request was denied.

403

Forbidden. The request was denied.

409

Conflict. The requested resource already exists.

500

An unexpected error occurred.

Scheduler

Up
get /scheduler/instances
Retrieves all Spark application instances (getAppInstances)
Retrieves all the Spark application instances.

Consumes

This API call consumes the following media types via the Content-Type request header:

Return type

array[SigAppInstanceDetail]

Example data

Content-Type: application/json
[ {
  "masterUrl" : "masterUrl",
  "executionUser" : "executionUser",
  "name" : "name",
  "state" : "state",
  "historyServerUrl" : "historyServerUrl",
  "uuid" : "uuid",
  "version" : "version"
}, {
  "masterUrl" : "masterUrl",
  "executionUser" : "executionUser",
  "name" : "name",
  "state" : "state",
  "historyServerUrl" : "historyServerUrl",
  "uuid" : "uuid",
  "version" : "version"
} ]

Produces

This API call produces the following media types according to the Accept request header; the media type will be conveyed by the Content-Type response header.

Responses

200

Successful response which contains a list of deep learning Spark application instances.

400

Bad request. The request was not formatted correctly.

401

Authentication error. The request was denied.

403

Forbidden. The request was denied.

500

An unexpected error occurred.

Up
get /scheduler/applications
Retrieves deep learning Spark applications (getApplications)
Retrieves deep learning Spark applications.

Consumes

This API call consumes the following media types via the Content-Type request header:

Query parameters

applicationid (optional)
Query Parameter — The ID of the Spark application.
applicationname (optional)
Query Parameter — The name of the Spark application.
driverid (optional)
Query Parameter — The ID of the Spark application driver.
search (optional)
Query Parameter — search
sort (optional)
Query Parameter — The field name to sort the response by. Only one field name can be specified as the sort type. Prefix the field name with "-" to sort in descending order.
order (optional)
Query Parameter — order
start (optional)
Query Parameter — start
length (optional)
Query Parameter — length
state (optional)
Query Parameter — state
sigId (optional)
Query Parameter — The ID of the Spark instance group

Return type

array[SparkApplicationDetail]

Example data

Content-Type: application/json
[ {
  "scheduleName" : "scheduleName",
  "memused" : 4.145608029883936,
  "type" : "BATCH",
  "executorexecutionuser" : "executorexecutionuser",
  "dltype" : "Caffe",
  "tunningname" : "tunningname",
  "submittedtime" : 1,
  "demandslots" : 9,
  "sigName" : "sigName",
  "model" : "model",
  "state" : "state",
  "applicationid" : "applicationid",
  "timestamp" : 7,
  "sparkinstancegroupid" : "sparkinstancegroupid",
  "hosts" : 3,
  "masterSeqNo" : 6,
  "endtime" : 1,
  "masterService" : "masterService",
  "applicationname" : "applicationname",
  "slots" : 7,
  "driver" : {
    "driverstdout" : "driverstdout",
    "coresused" : 0.8008281904610115,
    "memused" : 6.027456183070403,
    "host" : "host",
    "driverstderr" : "driverstderr",
    "id" : "id",
    "state" : "state",
    "containerid" : "containerid",
    "timestamp" : 1
  },
  "issharedapp" : "issharedapp",
  "coresused" : 2.027123023002322,
  "masterUrl" : "masterUrl",
  "uiport" : "uiport",
  "apprunduration" : 1.4894159098541704,
  "executors" : [ {
    "executorstdout" : "executorstdout",
    "coresused" : 5.962133916683182,
    "memused" : 5.637376656633329,
    "host" : "host",
    "executorstderr" : "executorstderr",
    "id" : "id",
    "state" : "state",
    "containerid" : "containerid",
    "timestamp" : 2
  }, {
    "executorstdout" : "executorstdout",
    "coresused" : 5.962133916683182,
    "memused" : 5.637376656633329,
    "host" : "host",
    "executorstderr" : "executorstderr",
    "id" : "id",
    "state" : "state",
    "containerid" : "containerid",
    "timestamp" : 2
  } ],
  "historyServerUrl" : "historyServerUrl",
  "driverexecutionuser" : "driverexecutionuser",
  "dataset" : "dataset",
  "username" : "username"
}, {
  "scheduleName" : "scheduleName",
  "memused" : 4.145608029883936,
  "type" : "BATCH",
  "executorexecutionuser" : "executorexecutionuser",
  "dltype" : "Caffe",
  "tunningname" : "tunningname",
  "submittedtime" : 1,
  "demandslots" : 9,
  "sigName" : "sigName",
  "model" : "model",
  "state" : "state",
  "applicationid" : "applicationid",
  "timestamp" : 7,
  "sparkinstancegroupid" : "sparkinstancegroupid",
  "hosts" : 3,
  "masterSeqNo" : 6,
  "endtime" : 1,
  "masterService" : "masterService",
  "applicationname" : "applicationname",
  "slots" : 7,
  "driver" : {
    "driverstdout" : "driverstdout",
    "coresused" : 0.8008281904610115,
    "memused" : 6.027456183070403,
    "host" : "host",
    "driverstderr" : "driverstderr",
    "id" : "id",
    "state" : "state",
    "containerid" : "containerid",
    "timestamp" : 1
  },
  "issharedapp" : "issharedapp",
  "coresused" : 2.027123023002322,
  "masterUrl" : "masterUrl",
  "uiport" : "uiport",
  "apprunduration" : 1.4894159098541704,
  "executors" : [ {
    "executorstdout" : "executorstdout",
    "coresused" : 5.962133916683182,
    "memused" : 5.637376656633329,
    "host" : "host",
    "executorstderr" : "executorstderr",
    "id" : "id",
    "state" : "state",
    "containerid" : "containerid",
    "timestamp" : 2
  }, {
    "executorstdout" : "executorstdout",
    "coresused" : 5.962133916683182,
    "memused" : 5.637376656633329,
    "host" : "host",
    "executorstderr" : "executorstderr",
    "id" : "id",
    "state" : "state",
    "containerid" : "containerid",
    "timestamp" : 2
  } ],
  "historyServerUrl" : "historyServerUrl",
  "driverexecutionuser" : "driverexecutionuser",
  "dataset" : "dataset",
  "username" : "username"
} ]

Produces

This API call produces the following media types according to the Accept request header; the media type will be conveyed by the Content-Type response header.

Responses

200

Successful response which contains a list of deep learning Spark applications.

400

Bad request. The request was not formatted correctly.

401

Authentication error. The request was denied.

403

Forbidden. The request was denied.

416

An index is out of range.

500

An unexpected error occurred.

Models

[ Jump to Methods ]

Table of Contents

  1. Attr -
  2. Batch -
  3. CSRFToken -
  4. ClassificationDetDetail -
  5. ClassificationDetResult -
  6. ComparisonDetail -
  7. Container -
  8. DLFramework -
  9. DatasetCreateParam -
  10. DatasetDetail -
  11. DoubleSet -
  12. DriverDetail -
  13. Envs -
  14. ExecutorDetail -
  15. FrameworkDetail -
  16. HpoAlgorithmDesc -
  17. HpoExperiment -
  18. HpoHyperParameter -
  19. HpoTaskDetail -
  20. HpoTaskInput -
  21. HpoTaskState -
  22. HyperParameter -
  23. IaSInstanceParam -
  24. IaSModelDescription -
  25. IaSParam -
  26. IaSProfileParam -
  27. IaSReadmeParam -
  28. IaSTestInputParam -
  29. IaSTestResultParam -
  30. ImageDetail -
  31. InferenceCreateParam -
  32. InferenceDetail -
  33. Instance -
  34. Isd -
  35. Kernel -
  36. ModelCreateParam -
  37. ModelDetail -
  38. ModelTemplateCreateParam -
  39. ModelTemplateDetail -
  40. Obj -
  41. Pictures -
  42. Policy -
  43. PredictParameters -
  44. PredictParams -
  45. PredictResult -
  46. RAKernel -
  47. RAService -
  48. ResourceAllocation -
  49. SigAppInstanceDetail -
  50. SparkApplicationDetail -
  51. StringMap -
  52. StringObjectMap -
  53. StringSet -
  54. StringSetStringMap -
  55. TrainDetail -
  56. TrainingCreateParam -
  57. TrainingParameters -
  58. ValidateDetail -
  59. ValidateOutPair -
  60. ValidateParameters -
  61. ValidationCreateParam -
  62. algoDef -
  63. algoParams -
  64. csvDetail -
  65. fixedHyperParam -
  66. resDef -
  67. searchExperiment -
  68. searchGrid -

Attr - Up

key
String The key.
value
String The value.

Batch - Up

userName (optional)
String Name of the user who started the task.
sigName (optional)
String Name of the Spark instance group.
sigId (optional)
String ID of the Spark instance group.
id (optional)
String ID of the batch.
args (optional)
String arguments to the tasks.
submissionId (optional)
String ID of the task.
appId (optional)
String ID of the application.
masterURL (optional)
String URL of the Spark.
state (optional)
String batch state.
executionUserName (optional)
String User name.

CSRFToken - Up

csrftoken
String The CSRF token that is obtained from successful login. This token must be passed as a request parameter for all POST, PUT, and DELETE requests that use session authentication.

ClassificationDetDetail - Up

sampleId (optional)
String The sample id.
inputPath (optional)
String The input path.
isImage (optional)
Boolean True for image classification.
results (optional)
array[ClassificationDetResult] The result details.

ClassificationDetResult - Up

label (optional)
String The label.
prob (optional)
Double The probability that there is an object in the grid cell. format: double
bbox (optional)
String The bounding box to describe the target location.

ComparisonDetail - Up

sampleId1 (optional)
String The first sample id.
sampleId2 (optional)
String The second sample id.
inputPath (optional)
String The input path.
isImage (optional)
Boolean True for image classification.
distance (optional)
Double The distance. format: double
isSimilar (optional)
Boolean True if similar.

Container - Up

container_uid (optional)
String The uid for container.
container_host (optional)
String The host for container.
container_status (optional)
String The status for container.
total_task (optional)
Integer The number of all tasks in the container.
running_task (optional)
Integer The number of running tasks in the container.
finish_task (optional)
Integer The number of finish tasks in the container.
failed_task (optional)
Integer The number of failed tasks in the container.

DLFramework - Up

name (optional)
String Name of the deep learning framework.
desc (optional)
array[String] Description of the deep learning framework.
frameworkVersion (optional)
String The framework version.
distributeStrategy (optional)
String The distributed strategies.
Enum:
MultiWorkerMirroredStrategy
ParameterServerStrategy
description (optional)
String Description.
numPs (optional)
Integer Number of parameter server workers

DatasetCreateParam - Up

The parameters for a creating dataset.
name
String The dataset name.
dbbackend
String The backend database (e.g. LMDB, TFrecords, CSV, ImageVector, ObjectDetection, Other).
trainpath (optional)
String The dataset training folder path.
valpath (optional)
String The dataset validation folder path.
testpath (optional)
String The dataset test folder path.
meanfilepath (optional)
String The dataset mean file path.
sigid
String The Spark instance group ID.
imagedetail (optional)
shards (optional)
Integer The number of shards of the dataset. This parameter is only used when dbbackend is TFrecords.
byclass (optional)
Boolean Whether to generate records by class. This parameter is only used when dbbackend is TFrecords.
plugin (optional)
String the csv plugin file path. This parameter is only used when dbbackend is CSV.
datasourcetype
String Type of source data for creating a new dataset.
Enum:
LMDB
TFRECORDS
OTHER
IMAGEFORCLASSIFICATION
CSV
IMAGEFOROBJECTDETECTION
IMGTOVECTOR

DatasetDetail - Up

name (optional)
String The dataset name.
dbbackend (optional)
String The backend database (e.g. LMDB, Other, TFrecords, CSV, ObjectDetection).
trainpath (optional)
String The dataset training folder path.
valpath (optional)
String The dataset validation folder path.
testpath (optional)
String The dataset test folder path.
meanfilepath (optional)
String The dataset mean file path.
status (optional)
String The dataset status.
runduration (optional)
Double The application run duration. format: double
sigid (optional)
String The Spark instance group ID.
signame (optional)
String The Spark instance group Name.
masterUrl (optional)
String The Spark master URL.
driverid (optional)
String The Spark driver ID.
sparkappid (optional)
String The Spark Application ID.
imagedetail (optional)
trainlabels (optional)
array[StringSet] The dataset training labels.
vallabels (optional)
array[StringSet] The dataset validation labels.
testlabels (optional)
array[StringSet] The dataset test labels.
datasourcetype (optional)
String Type of source data for creating a new dataset.
Enum:
LMDB
TFRECORDS
OTHER
IMAGEFORCLASSIFICATION
CSV
IMAGEFOROBJECTDETECTION
IMGTOVECTOR
submittedtime (optional)
String The application submitted time.
createUser (optional)
String The user that creates the dataset.
size (optional)
Double The size of the dataset. format: double
shards (optional)
Integer The number of shards of the dataset.
byclass (optional)
Boolean Whether to generate records by class.
plugin (optional)
String the csv plugin file path.

DoubleSet - Up

DriverDetail - Up

id (optional)
String The Spark drivers ID.
containerid (optional)
String The resource orchestrator activity ID that starts the Spark drivers.
state (optional)
String The Spark drivers state.
host (optional)
String The host on which the Spark drivers run.
coresused (optional)
Double The number of CPU cores allocated. format: double
memused (optional)
Double The amount of memory, in MB that is used by the Spark drivers. format: double
timestamp (optional)
Long The time-stamp of the updated Spark drivers. format: int64
driverstdout (optional)
String The path to the Spark drivers stdout log.
driverstderr (optional)
String The path to the Spark drivers stderr log.

Envs - Up

name
String The name.
value
String The value.

ExecutorDetail - Up

id (optional)
String The Spark executor ID.
containerid (optional)
String The resource orchestrator activity ID that starts the Spark executors.
state (optional)
String The Spark executor state.
host (optional)
String The host on which the Spark executors run.
coresused (optional)
Double The number of CPU cores that are allocated. format: double
memused (optional)
Double The amount of memory, in MB, that is used by the executors. format: double
timestamp (optional)
Long The time-stamp of the updated Spark executors. format: int64
executorstdout (optional)
String The path to the Spark executors stdout log.
executorstderr (optional)
String The path to the Spark executors stderr log.

FrameworkDetail - Up

name (optional)
String The name of the deep learning framework.
home (optional)
String The home folder of the deep learning framework.
backend (optional)
String The deep learning framework backend.
accelerator (optional)
String The deep learning training engine.
Enum:
Native
Elastic
psNum (optional)
String The psNum.
commIPNetwork (optional)
String The communication network.

HpoAlgorithmDesc - Up

name (optional)
String The hpo algorithm name.
path (optional)
String The hpo algorithm installation path (only for plugin algorithm).
condaHome (optional)
String The CONDA_HOME used to run hpo algorithm (only for plugin algorithm).
condaEnv (optional)
String The conda environment used to run hpo algorithm (only for plugin algorithm).
createtime (optional)
String The creation time of the hpo algorithm (only for plugin algorithm).
type (optional)
String The type of the hpo algorithm.
remoteExec (optional)
Boolean The plugin algorithm execution mode is remoted or not (only for plugin algorithm).
logLevel (optional)
String The log level for the plugin algorithm (only for plugin algorithm).

HpoExperiment - Up

id (optional)
Integer Experiment id.
state (optional)
String Experiment state.
metricVal (optional)
Double metric value. format: double
maxiteration (optional)
Integer maximum iteration.
hyperParams (optional)
appId (optional)
String spark application Id.
driverId (optional)
String spark driver Id.
startTime (optional)
String The start time of experiment training.
endTime (optional)
String The end time of experiment training.

HpoHyperParameter - Up

name
String Hyperparameter name, the same name will be used in the config.json so user model can load it.
type
String One of Range, Discrete, Fix.
Enum:
range
discrete
fix
dataType
String One of int, double, str.
Enum:
int
double
str
minDbVal (optional)
Double Minimal double value if type=Range and datatype=double. format: double
maxDbVal (optional)
Double Maximal double value if type=Range and datatype=double. format: double
minIntVal (optional)
Integer Minimal int value if type=Range and datatype=int.
maxIntVal (optional)
Integer Maximal int value if type=Range and datatype=int.
discreteDbVal (optional)
array[Double] Double list like [0.1,0.2] if type=Discreate and datatype=double. format: double
discreteIntVal (optional)
array[Integer] Int list like [1,2] if type=Discreate and datatype=int.
discreateStrVal (optional)
array[String] str list like ['1','2'] if type=Discreate and datatype=double.
userDefined (optional)
Boolean whether is user defined parameter.
fixedVal (optional)
String fixed hyperparameter.
step (optional)
String A number value in string format, step size to split the Range space. ONLY valid when type is Range.
power (optional)
String A number value in string format, the base value for power calculation. ONLY valid when type is Range.

HpoTaskDetail - Up

input (optional)
searchGrid (optional)
state (optional)
String The tuning status.
creator (optional)
String The user who created the tuning task.
createtime (optional)
String The time the tuning task was created.
sigId (optional)
String Spark instance group id.
sigName (optional)
String Spark instance group name.
consumerName (optional)
String consumer name.

HpoTaskInput - Up

modelName
String The deep learning model name.
hpoName
String The deep learning tuning name.
hyperParams (optional)
array[HpoHyperParameter] The deep learning tuning hyperparameters.
resDef
algoDef
experiments (optional)
array[searchExperiment] Only valid for ExperimentGridSearch algorithm which will submit train with this list of experiments.

HpoTaskState - Up

hpoName (optional)
String The name of hyperparameter optimization(HPO) task.
state (optional)
String The state of HPO task.
progress (optional)
String The progress of HPO task.
duration (optional)
String The duration of HPO task.
creator (optional)
String The creator of HPO task.
createtime (optional)
String The create time of HPO task.
best (optional)
HpoExperiment The best hyper parameters of HPO
experiments (optional)
array[HpoExperiment] All experiments of HPO.

HyperParameter - Up

learningrate (optional)
Float The learning rate hyperparameter. format: float
momentum (optional)
Float The momentum hyperparameter. format: float
weightdecay (optional)
Float The Caffe and PyTorch weight decay hyperparameter. format: float
decayrate (optional)
Float The TensorFlow learning rate decay hyperparameter. format: float
decaysteps (optional)
BigDecimal The TensorFlow decaysteps hyperparameter. format: integer
staircase (optional)
String The TensorFlow staircase hyperparameter.
maxiteration (optional)
Integer The Caffe and TensorFlow maximum iteration hyperparameter.
epoch (optional)
Integer The PyTorch maximum iteration hyperparameter.
solvertype (optional)
String The solver or optimizer type hyperparameter. "Cf" marks a valid parameter for Caffe, "TF" for TensorFlow, "PT" for PyTorch.
Enum:
AdaGrad (Cf)
AdaDelta (Cf)
Adam (Cf, TF and PT)
Momentum (TF)
RMSProp (Cf, TF and PT)
SGD (Cf and PT)
ASGD (PT)
Nesterov (Cf)
GradientDescent (TF)
Adadelta (TF and PT)
Adagrad (TF and PT)
AdagradDA (TF)
Ftrl (TF)
SparseAdam (PT)
Adamax (PT)
Rprop (PT)
ProximalGradientDescent (TF)
ProximalAdagrad (TF)
lrpolicy (optional)
String The learning rate policy. "Cf" marks a valid parameter for Caffe, and "TF" for TensorFlow.
Enum:
fixed (Cf, TF and PT)
step (Cf and PT)
multistep (Cf and PT)
exp (Cf)
inv (Cf)
poly (Cf)
sigmoid (Cf)
exponential (TF and PT)
inversetime (TF)
naturalexp (TF)
piecewise (TF)
polynomial (TF)
cosineannealing (PT)
reducelronplateau (PT)
stepsize (optional)
Integer The Caffe and PyTorch model stepsize hyperparameter.
stepvalues (optional)
String The Caffe model stepvalue hyperparameter, a list of step values separated by comma.
gamma (optional)
Double The Caffe and PyTorch model gamma hyperparameter. format: double
power (optional)
Double The Caffe and TensorFlow model power hyperparameter. format: double
cycle (optional)
Boolean The TensorFlow model power hyperparameter.
hiddenstatesize (optional)
Integer The TensorFlow LSTM model hidden state size hyperparameter.
optdecay (optional)
Double The TensorFlow model optdecay hyperparameter. format: double
epsilon (optional)
Double The TensorFlow and PyTorch model epsilon hyperparameter. format: double
accumulator (optional)
Double The TensorFlow and PyTorch model accumulator hyperparameter. format: double
l1_regularization (optional)
Double The TensorFlow model l1_regularization hyperparameter. format: double
l2_regularization (optional)
Double The TensorFlow model l2_regularization hyperparameter. format: double
beta1 (optional)
Double The TensorFlow model beta1 hyperparameter. format: double
beta2 (optional)
Double The TensorFlow model beta2 hyperparameter. format: double
lr_power (optional)
Double The TensorFlow model lr_power hyperparameter. format: double
end_learning_rate (optional)
Double The TensorFlow model end_learning_rate hyperparameter. format: double
rho (optional)
Double The PyTorch model rho hyperparameter. format: double
lr_decay (optional)
Double The PyTorch model lr_decay hyperparameter. format: double
amsgrad (optional)
Boolean The PyTorch model amsgrad hyperparameter.
lambd (optional)
Double The PyTorch model lambd hyperparameter. format: double
alpha (optional)
Double The PyTorch model alpha hyperparameter. format: double
t0 (optional)
Double The PyTorch model t0 hyperparameter. format: double
centered (optional)
Boolean The PyTorch model centered hyperparameter.
dampening (optional)
Double The PyTorch model dampening hyperparameter. format: double
nesterov (optional)
Boolean The PyTorch model nesterov hyperparameter.
t_max (optional)
Integer The PyTorch model t_max hyperparameter.
eta_min (optional)
Double The PyTorch model eta_min hyperparameter. format: double
mode (optional)
String The PyTorch model mode hyperparameter, value is one of min, max.
factor (optional)
Double The PyTorch model factor hyperparameter. format: double
patience (optional)
Integer The PyTorch model patience hyperparameter.
threshold (optional)
Double The PyTorch model threshold hyperparameter. format: double
threshold_mode (optional)
String The PyTorch model threshold_mode hyperparameter, value is one of rel, abs.
cooldown (optional)
Integer The PyTorch model cooldown hyperparameter.
eps (optional)
Double The PyTorch model eps hyperparameter. format: double

IaSInstanceParam - Up

name
String The name for Elastic Distributed Inference model.
state (optional)
String The state for Elastic Distributed Inference model.
instance (optional)

IaSModelDescription - Up

schema_version (optional)
String The version of Elastic Distributed Inference model.
name
String The name of the Elastic Distributed Inference model.
tag (optional)
String The tag of the Elastic Distributed Inference model.
weight_path (optional)
String The model weight which used for inference.
model_path (optional)
String The inference model path.
creator (optional)
String The creator of the Elastic Distributed Inference model.
runtime (optional)
String The runtime of Elastic Distributed Inference model.
kernel_path (optional)
String The execution kernel for inference model.
mk_resource_req (optional)
String The kernel resource request of the Elastic Distributed Inference model.
mk_umask (optional)
String The kernel umask of Elastic Distributed Inference model.
attributes (optional)
array[Attr] Key-value of attributes can be accessed in model kernel.
mk_environments (optional)
array[Envs] Additional environment variables to run model kernel.
service_uri (optional)
String Rest Service URL.
size (optional)
Integer The size of the Elastic Distributed Inference model.
mk_instance_min (optional)
Integer The minimal number of instance.
mk_instance_max (optional)
Integer The maximal number of instance.
create_time (optional)
String The create time of the Elastic Distributed Inference model.
last_update_time (optional)
String The last update time of the Elastic Distributed Inference model.
state (optional)
String The state of Elastic Distributed Inference model.

IaSParam - Up

edi_py
String The execution kernel for inference model.
attribute (optional)
String Key-value of attributes can be accessed in model kernel.
mcenv (optional)
String Additional environment variables to run model kernel.
name
String The name inference model.
type (optional)
String The type for inference model.
modelPath
String The model file path for inference model.
weightPath
String The weight file path for inference model.
runtime
String The runtime for inference model.

IaSProfileParam - Up

name
String The name for Elastic Distributed Inference model.
create_time (optional)
String The create time for Elastic Distributed Inference model.
update_time (optional)
String The update time for Elastic Distributed Inference model.
replica (optional)
Integer The replication number for inference model instance.
type (optional)
String The type for Elastic Distributed Inference model.
schema_version (optional)
String The schema version for Elastic Distributed Inference model.
policy (optional)
kernel (optional)
resource_allocation (optional)
envs (optional)
array[Envs] Additional environment variables to run model kernel.

IaSReadmeParam - Up

readme (optional)
String The readme for Elastic Distributed Inference model.

IaSTestInputParam - Up

action_type
String The action type for the inference, including Classification, Object Detection.
data_type
String The data type for the inference, including image:raw_data, image:jpeg_uri
user (optional)
String The usr who run the inference.
attributes (optional)
array[Attr] The attributes for inference, for example threshold.
data_value
array[Attr] Key-value for inference data.

IaSTestResultParam - Up

modelName (optional)
String The name of inference model.
reslove (optional)
Boolean Whether or not the inference result can be resolved.
other (optional)
String Return value for inference result can not be resolved.
results (optional)
array[PredictResult] The result for the inference.

ImageDetail - Up

isusingtext (optional)
Boolean Whether using text or not.
traintextpath (optional)
String The train text path.
valtextpath (optional)
String The validation text path.
testtextpath (optional)
String The test text path.
labeltextpath (optional)
String The label text path.
trainimagepath (optional)
String The train image path.
valimagepath (optional)
String The validation image path.
testimagepath (optional)
String The test image path.
imagetype (optional)
String The image type.
height (optional)
Integer The height of the image.
width (optional)
Integer The width of the image.
resizetransformation (optional)
String The resize transformation.
valpercentage (optional)
Integer The percentage for validation.
testpercentage (optional)
Integer The percentage for test.
splitalgorithm (optional)
String The algorithm for splitting images.

InferenceCreateParam - Up

modelName
String The name of the model.
trainName
String The name of the model training.
inferenceModelName (optional)
String The name of the new inference model.

InferenceDetail - Up

modelname (optional)
String The deep learning model name.
predictname (optional)
String The prediction name.
inputpath (optional)
String The input directory path.
inputfiles (optional)
String The input files.
output (optional)
String The output directory path
threshold (optional)
String The probability threshold for classification.
resultfile (optional)
String The result file name.
result (optional)
status (optional)
String The inference status.
sigid (optional)
String The Spark instance group ID.
signame (optional)
String The Spark instance group name
masterUrl (optional)
String The Spark master URL
driverid (optional)
String The Spark driver ID.
appid (optional)
String The Spark application ID.
appURL (optional)
String The Spark application URL.
createTime (optional)
String The time the inference was created.
user (optional)
String The user who created the inference.
historyServerUrl (optional)
String The Spark history server URL.

Instance - Up

name (optional)
String The name of the Elastic Distributed Inference model.
state (optional)
String The state of the instance.
instances (optional)
array[Isd] The instance detail for an instance deamon.

Isd - Up

isd_uid (optional)
String The uid of the instance.
client_number (optional)
Integer The number of the instance client.
pending_number (optional)
Integer The number of the pending instance.
request_per_sec (optional)
Integer The number of request dealing with per second.
data_size_per_sec (optional)
Integer The size of data dealing with per second.
isd_container (optional)
array[Container] The container detail for an instance deamon.

Kernel - Up

working_directory (optional)
String Working Directory.
connection_timeout (optional)
Integer The kernel connection timeout.
log_directory (optional)
String Log Directory.
run_as (optional)
String The kernel run as.
umask (optional)
String The kernel umask.
gpu (optional)
String Nvidia GPU policy, including no, shared, exclusive.
envs (optional)

ModelCreateParam - Up

name
String The name of the deep learning model.
description (optional)
String The description of the deep learning model.
templatename
String The deep learning model template name.
sig (optional)
String The Spark instance group id. This parameter is required when create an inference model.
accelerator (optional)
String The deep learning model training engine.
Enum:
Single
Native
Elastic
hyperparameter (optional)
dataset (optional)
String The name of the the dataset associated with the deep learning model. This parameter is required when create a training model.
batchsize (optional)
Integer The batch size.
tfmainContent (optional)
String The contents of the main.py file.
type (optional)
String The type of the model, indicates whether it is inference model or normal model.
Enum:
Training
Inference
wtfolder (optional)
String The folder that contains the weight file.
frameworkVersion (optional)
String The framework version
distributeStrategy (optional)
String The distribution strategy

ModelDetail - Up

name (optional)
String The name of the deep learning model.
path (optional)
String The path of the deep learning model.
description (optional)
String The description of the deep learning model.
templatename (optional)
String The deep learning model template name.
framework (optional)
String The deep learning model framework.
Enum:
Caffe
TensorFlow
PyTorch
accelerator (optional)
String The deep learning model training engine.
Enum:
Single
Native
Elastic
hyperparameter (optional)
dataset (optional)
String The name of the the dataset associated with the deep learning model.
batchsize (optional)
Integer The batch size.
solverprototxtpath (optional)
String The path to *solver.prototxt configuration file.
traintestprototxtpath (optional)
String The path to *train_test.prototxt configuration file.
inferenceprototxtpath (optional)
String The path for inference configuration file.
dimimage (optional)
String The dimimage.
solverContent (optional)
String The content of the *solver.prototxt configuration file.
trainTestContent (optional)
String The content of the *train_test.prototxt configuration file.
inferenceContent (optional)
String The content of the inference configuration file.
tfmainpath (optional)
String The main executor file path.
tfmainContent (optional)
String The contents of the main.py file.
sig (optional)
String The Spark instance group id.
signame (optional)
String The Spark instance group name.
tmpfilePath (optional)
String The path of the temporary file.
tmpfileContent (optional)
String Contents of the temporary file.
wfinit (optional)
String The initial weight file.
wtfolder (optional)
String The folder that contains the weight file.
type (optional)
String The type of the model, indicates whether it is inference model or training model.
Enum:
Training
Inference
user (optional)
String The user who created the model.
createTime (optional)
String The time the model was created.
frameworkVersion (optional)
String The framework version
distributeStrategy (optional)
String The distribution strategy

ModelTemplateCreateParam - Up

name
String The name of the model template.
path
String The path of the model template.
description (optional)
String The description.
framework
String The deep learning framework.
Enum:
Caffe
TensorFlow
PyTorch
frameworkVersion (optional)
String The framework version.

ModelTemplateDetail - Up

name (optional)
String The name of the model template.
path (optional)
String The path of the model template.
description (optional)
String The description.
hyperparameter (optional)
framework (optional)
String The deep learning framework name.
solverprototxtpath (optional)
String The path to Caffe *solver.prototxt configuration file.
traintestprototxtpath (optional)
String The path to Caffe *train_test.prototxt configuration file.
inferenceprototxtpath (optional)
String The path to inference prototxt configuration file.
solverContent (optional)
String The solverContent.
trainTestContent (optional)
String The trainTestContent.
inferenceContent (optional)
String The inferenceContent.
tfmainpath (optional)
String The main executor file path.
tfmainContent (optional)
String The contents of the main.py.
frameworkVersion (optional)
String The framework version.

Obj - Up

Pictures - Up

name (optional)
String The name of the image.
path (optional)
String The path of the image.
labels (optional)
String The labels of the image.

Policy - Up

name (optional)
String The name of the policy.
schedule_intervel (optional)
Integer The intervel of schedule.
kernel_min (optional)
Integer The minimal number of model kernel.
kernel_max (optional)
Integer The maximal number of model kernel.
kernel_delay_release_time (optional)
Integer The idle time to wait to release the kernel.
task_execution_timeout (optional)
Integer The task execution timeout.
task_batch_size (optional)
Integer The maximal number of task which single model can handle each time.
stream_number_per_group (optional)
Integer The number of stream task per group.
stream_discard_slow_tasks (optional)
Boolean Discard stream slow task if set true.

PredictParameters - Up

predictItem (optional)
String Prediction item.
predictResults (optional)

PredictParams - Up

index (optional)
String The prediction item index.
name (optional)
String The prediction item name.
proba (optional)
Float The prediction item probability. format: float

PredictResult - Up

type (optional)
String The type of the prediction.
classificationResults (optional)
array[ClassificationDetDetail] The results of classification.
detResults (optional)
comparisonResults (optional)
array[ComparisonDetail] Comparison results.

RAKernel - Up

type (optional)
String Resource manager for model kernel, currently only support ego
resource_group (optional)
String Ego resource group for model kernel
consumer (optional)
String Ego consumer for model kernel
resreq (optional)
String Ego resource filter for model kernel

RAService - Up

type (optional)
String Resource manager for Elastic Distributed Inference, currently only support ego
resource_group (optional)
String Ego resource group for Elastic Distributed Inference
consumer (optional)
String Ego consumer for Elastic Distributed Inference
resreq (optional)
String Ego resource filter for Elastic Distributed Inference

ResourceAllocation - Up

service (optional)
kernel (optional)

SigAppInstanceDetail - Up

uuid (optional)
String The unique ID of the Spark instance group.
name (optional)
String The name of the Spark instance group.
version (optional)
String The Spark version of the Spark instance group.
masterUrl (optional)
String The URL of the Spark instance group master.
executionUser (optional)
String The execution user of the Spark instance group.
state (optional)
String The state of the Spark instance group.
historyServerUrl (optional)
String The Spark history server URL.

SparkApplicationDetail - Up

sparkinstancegroupid (optional)
String The Spark instance group ID.
applicationid (optional)
String The Spark application ID.
applicationname (optional)
String The Spark application name.
type (optional)
String The Spark application type.
Enum:
BATCH
NOTEBOOK
state (optional)
String The Spark application state.
uiport (optional)
String The port number on which to access the Spark application UI.
driver (optional)
executors (optional)
array[ExecutorDetail] A list of Spark executors.
slots (optional)
Integer The number of slots that are used by the Spark instance group.
demandslots (optional)
Integer The number of demanded slots that is being used by the Spark application.
hosts (optional)
Integer The number of hosts on which Spark applications run.
coresused (optional)
Double The number of CPU cores that are allocated to the Spark application. format: double
memused (optional)
Double The amount of memory, in MB, that is used by the Spark application. format: double
username (optional)
String The user that executes the Spark application.
driverexecutionuser (optional)
String The execution user for the Spark drivers.
executorexecutionuser (optional)
String The execution user for the Spark executors.
timestamp (optional)
Long The time-stamp of the updated Spark application. format: int64
submittedtime (optional)
Long The Spark application submitted time. format: int64
masterUrl (optional)
String The Spark master URL.
endtime (optional)
Long The Spark application finish time. format: int64
scheduleName (optional)
String The application schedule name.
issharedapp (optional)
String Specifies whether the Spark application shares RDD.
apprunduration (optional)
Double The application run duration. format: double
masterSeqNo (optional)
Integer The master sequence number.
masterService (optional)
String The master service name.
model (optional)
String The deep learning model name.
dataset (optional)
String The deep learning dataset name.
dltype (optional)
String The deep learning framework name (e.g Caffe or TensorFlow).
tunningname (optional)
String The deep learning tuning name.
sigName (optional)
String The Spark instance group name.
historyServerUrl (optional)
String The Spark history server URL.

StringMap - Up

example_key (optional)

StringObjectMap - Up

example_key (optional)

StringSet - Up

StringSetStringMap - Up

example_key (optional)

TrainDetail - Up

model (optional)
String The deep learning model name.
dataset (optional)
String The dataset name.
trainingParameters (optional)

TrainingCreateParam - Up

cmd (optional)
String The training command.
trainName
String The deep learning training name.
dlFramework
String The deep learning framework name.
wtURL (optional)
String The training weight file URL.
wfinit (optional)
String The initial weight file for training.
wtfolder (optional)
String The training weight file folder name.
gpuRatio (optional)
Integer The gpu ratio.
clusterSize
Integer The number of workers in the cluster.
testInterval (optional)
Integer Number of training runs that are run in a test interval. At each test interval the model is run against the test dataset to verify that the accuracy is sufficient. By default, the interval is set to 100.
testIteration (optional)
Integer Number of times that the model runs against the test dataset in each interval. By default, the iteration is set to 10. For example, if the test interval is set to 100 and the iteration is set to 10, on the hundredth training run, the model will run against the test dataset 10 times.
syncMode (optional)
String The gradient synchronization mode in elastic distributed training. This parameter to specify whether the training is a synchronous training, or an asynchronous training.
Enum:
SYNC
ASYNC
distribute (optional)
Boolean Denotes whether it is distributed or not.

TrainingParameters - Up

sigId (optional)
String The Spark instance group ID.
sigName (optional)
String The Spark instance group name.
sigMasterUrl (optional)
String The Spark instance group master URL.
driverid (optional)
String The Spark driver ID.
cmd (optional)
String The training command.
trainName (optional)
String The deep learning training name.
dlFramework (optional)
String The deep learning framework name.
status (optional)
String The training status.
appid (optional)
String The Spark application ID.
appURL (optional)
String The Spark application URL.
wtURL (optional)
String The training weight file URL.
wfinit (optional)
String The initial weight file for training.
wtfolder (optional)
String The training weight file folder name.
gpuRatio (optional)
Integer The gpu ratio.
createTime (optional)
String The time the training task was created.
user (optional)
String The user who created the training task.
clusterSize (optional)
Integer The number of workers in the cluster.
testInterval (optional)
Integer Number of training runs that are run in a test interval. At each test interval the model is run against the test dataset to verify that the accuracy is enough.
testIteration (optional)
Integer Number of times that the model runs against the test dataset in each interval. For example, if the test interval is set to 100 and the test iteration is set to 10, on the hundredth training run, the model will run against the test dataset 10 times.
syncMode (optional)
String The gradient synchronization mode in elastic distributed training. This parameter specifies whether the training is a synchronous or asynchronous.
Enum:
SYNC
ASYNC
progress (optional)
Integer The progress.
historyServerUrl (optional)
String The Spark history server URL.

ValidateDetail - Up

modelname (optional)
String The deep learning model name.
dataSet (optional)
String The deep learning dataset name.
status (optional)
String The deep learning validation status.
driverId (optional)
String The Spark driver ID.
appid (optional)
String The Spark application ID.
appURL (optional)
String The Spark application URL.
historyServerUrl (optional)
String The Spark history server URL.
valParameters (optional)
outPairs (optional)

ValidateOutPair - Up

name (optional)
String The validation result pair name.
value (optional)
String The validation result pair value.

ValidateParameters - Up

valName (optional)
String The deep learning validation name.
sigId (optional)
String Spark instance group ID.
sigName (optional)
String Spark instance group name.
sigMasterUrl (optional)
String URL of the Spark master for the Spark instance group.
createTime (optional)
String The time the validation was created.
user (optional)
String The user who created the validation.
trainName (optional)
String Name of the training to validate.
metrics (optional)
array[String] The list of metrics.

ValidationCreateParam - Up

valName
String The deep learning validation name
trainName
String Name of the training to validate.
threshold (optional)
Double The threshold value, for example, 0.1 format: double
metrics
array[String] The list of metrics, for example, "Top1", "ConfusionMatrix", "IoU", "mAP"
Enum:

algoDef - Up

algorithm definition.
algorithm
String The tuning algorithm. it can be build in algorithms like Random, Bayesian, Tpe, Hyperband and ExperimentGridSearch, or user installed algorithms.
maxRunTime (optional)
Integer Max running time of the hpo task in munites, default -1(unlimited).
maxJobNum (optional)
Integer Max number of training job to submitted for hpo task, default -1(unlimited).
maxParalleJobNum (optional)
Integer Max number of training job to run in parallel, default 1.
hyperbandEta (optional)
Double hyperband eta value. format: double
objective (optional)
String Optimize policy, one of minimize and maximize.
Enum:
Maximize
Minimize
algoParams (optional)
array[algoParams] optional, additional algorithm parameters and it could be different for each algorithm.

algoParams - Up

name
String Name of the search algorithm parameter name.
value
String Value for the corresponding algirhtm parameter.

csvDetail - Up

columns (optional)
array[String] A list of the column name.
index (optional)
array[String] A list of the index.
data (optional)
array[DoubleSet] The data.
JSONString (optional)
String The Json string of the csv data.

fixedHyperParam - Up

name
String Hyperparameter name, the same name will be used in the config.json so user model can load it
dataType
String one of int, double, str
fixedVal
String The same type with datatype specified, if dataTye=double, need fixedVal type doulbe

resDef - Up

The deep learning tuning resource definition.
framework
String The deep learning framework.
Enum:
Caffe
TensorFlow
PyTorch
PyTorchOnElastic
initWeightPath (optional)
String Weight file path.
maxiteration
String The maximum iteration count.
miniteration (optional)
String The minimum iteration count, optional for hyperband, default value 1.
batchsize
Integer The batch size tuning parameter.
gpuNum (optional)
Integer The gpu number.
workerNum (optional)
Integer The number of workers in the cluster.
distribute (optional)
Boolean Whether using distribute mode.
syncMode (optional)
String The gradient synchronization mode in elastic distributed training. This parameter to specify whether the training is a synchronous training, or an asynchronous training.
Enum:
SYNC
ASYNC
resourceInstanceId (optional)
String Instance group id

searchExperiment - Up

id
Integer experiment id.
fixedHyperParams
array[fixedHyperParam] List of hyperparameters used in this experiment training.

searchGrid - Up

experiments (optional)
best (optional)
running (optional)
Integer The total number of parallel running jobs.
complete (optional)
Integer The number of completed jobs.
failed (optional)
Integer The number of failed jobs.
progress (optional)
String The progress.
duration (optional)
String Run duration of this task.