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.
application/json
Responses
200
Successful response that contains a dictionary of key-value string pairs that is defined in the dlpd.conf file.
StringMap
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.
Consumes
This API call consumes the following media types via the Content-Type request header:
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.
application/json
Responses
201
The deep learning dataset created successfully.
400
Bad request. The request was not formatted correctly.
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.
application/json
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.
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:
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.
application/json
Responses
204
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.
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.
application/json
Responses
200
Successful response that contains the resulting deep learning dataset.
DatasetDetail
400
Bad request. The request was not formatted correctly.
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.
application/json
Responses
200
Successful response that contains the resulting deep learning datasets.
400
Bad request. The request was not formatted correctly.
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.
application/json
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.
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:
application/json
Return type
Integer
Example data
Content-Type: application/json
0
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.
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:
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.
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:
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.
application/json
Responses
200
Successful response that contains the task.
ExecDetails
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.
application/json
Responses
200
Successful response that contains the logs of this training task.
LogDetails
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.
application/json
Responses
200
Successful response that contains the trained model of the training task. Returned as a zip file.
ResultDetails
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:
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.
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.
application/json
Responses
200
Successful response that contains all deep learning framework plugins. Framework plugin names are used to start a task.
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.
This API call consumes the following media types via the Content-Type request header:
application/json
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.
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:
application/json
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.
application/json
Responses
200
Successful response that contains the resulting framework information.
400
Bad request. The request was not formatted correctly.
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.
application/json
Responses
200
Successful response that contains the resulting framework information.
400
Bad request. The request was not formatted correctly.
This API call consumes the following media types via the Content-Type request header:
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.
application/json
Responses
204
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.
This API call consumes the following media types via the Content-Type request header:
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.
application/json
Responses
204
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.
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:
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.
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.
application/json
Responses
200
Successful response that contains the resulting hpo tasks.
400
Bad request. The request was not formatted correctly.
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.
application/json
Responses
200
Successful response that contains the resulting hpo tasks.
400
Bad request. The request was not formatted correctly.
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.
application/json
Responses
200
Successful response that contains the resulting hpo algorithm.
HpoAlgorithmDesc
400
Bad request. The request was not formatted correctly.
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.
application/json
Responses
200
Successful response that contains the resulting hpo task.
HpoTaskState
400
Bad request. The request was not formatted correctly.
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:
multipart/form-data
application/x-www-form-urlencoded
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.
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.
application/json
Responses
200
Successfully installed the hpo plugin algorithm.
String
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, one of Random, Bayesian, Tpe, Hyperband',
'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, currently only Hyperband will require this field for resource definition which will be covered more 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:
As for search algorithm Hyperband, 'algoParams' is required with following input:
'algoParams':
[
{
'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 correspongind upper limited value for the ResourceName.'
}
]
Consumes
This API call consumes the following media types via the Content-Type request header:
multipart/form-data
application/x-www-form-urlencoded
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.
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.
This API call consumes the following media types via the Content-Type request header:
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.
application/json
Responses
200
Successfully stopped the hpo task.
400
Bad request. The request was not formatted correctly.
This API call consumes the following media types via the Content-Type request header:
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.
application/json
Responses
200
Successfully stopped the hpo task forcely.
400
Bad request. The request was not formatted correctly.
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.
application/json
Responses
201
Successfully created model inference.
400
Bad request. The request was not formatted correctly.
This API call consumes the following media types via the Content-Type request header:
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.
application/json
Responses
204
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.
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.
application/json
Responses
200
Successful response containing all inference instances for a model.
400
Bad request. The request was not formatted correctly.
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.
application/json
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.
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.
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:
multipart/form-data
application/x-www-form-urlencoded
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 (required)
Form Parameter — The Spark instance group master URL.
sigid (required)
Form Parameter — The Spark instance group ID.
signame (required)
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.
This API call consumes the following media types via the Content-Type request header:
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.
application/json
Responses
200
Successfully stopped the prediction job.
400
Bad request. The request was not formatted correctly.
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.
application/json
Responses
201
The deep learning model template is created successfully.
Path Parameter — The deep learning model template name.
Consumes
This API call consumes the following media types via the Content-Type request header:
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.
application/json
Responses
204
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.
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.
application/json
Responses
200
Successful response that contains the resulting deep learning model template.
ModelTemplateDetail
400
Bad request. The request was not formatted correctly.
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.
application/json
Responses
200
Successful response that contains the resulting deep learning model templates.
400
Bad request. The request was not formatted correctly.
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:
application/json
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.
application/json
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.
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:
application/json
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.
application/json
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.
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.
application/json
Responses
200
The deep learning model template is modified on the server.
400
Bad request. The request was not formatted correctly.
This API call consumes the following media types via the Content-Type request header:
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.
application/json
Responses
204
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.
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:
application/json
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.
application/json
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.
get /models/{modelname}/trainings/{trainingname}/weightfile
Get a weight file for a model training (getModelTrainingWeightFile)
Retrieves a weight file 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:
application/json
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.
application/json
Responses
200
Successful response containing the weight file name.
String
400
Bad request. The request was not formatted correctly.
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.
application/json
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.
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.
application/json
Responses
200
Successful response containing a detailed list of all trainings associated with a model.
400
Bad request. The request was not formatted correctly.
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.
application/json
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.
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:
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.
application/json
Responses
200
Successfully stopped the training job.
400
Bad request. The request was not formatted correctly.
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:
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.
application/json
Responses
201
Successfully created a new model using the tuning result.
400
Bad request. The request was not formatted correctly.
This API call consumes the following media types via the Content-Type request header:
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.
application/json
Responses
204
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.
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.
application/json
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.
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.
application/json
Responses
200
Successful response that contains tuning details.
TuningDetail
400
Bad request. The request was not formatted correctly.
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.
application/json
Responses
200
The deep learning model auto tuning has started.
400
Bad request. The request was not formatted correctly.
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:
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.
application/json
Responses
200
Successfully stopped the tuning job.
400
Bad request. The request was not formatted correctly.
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:
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.
application/json
Responses
202
Successfully updated the model using the tuning result.
400
Bad request. The request was not formatted correctly.
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:
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.
application/json
Responses
204
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.
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.
application/json
Responses
200
List of all validations for the specified model.
400
Bad request. The request was not formatted correctly.
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.
application/json
Responses
200
Successfully started validation for a deep learning model.
400
Bad request. The request was not formatted correctly.
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:
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.
application/json
Responses
200
Successfully stopped the validation job.
400
Bad request. The request was not formatted correctly.
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.
Upload a new wight file. Weigh files can be used for trainings and inferences.
Consumes
This API call consumes the following media types via the Content-Type request header:
multipart/form-data
Form parameters
file (required)
Form Parameter — Weight file for model training.
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.
This API call consumes the following media types via the Content-Type request header:
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.
application/json
Responses
204
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.
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.
application/json
Responses
200
Successful response that contains the resulting deep learning model.
ModelDetail
400
Bad request. The request was not formatted correctly.
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:
application/json
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.
application/json
Responses
200
Successful response that contains the resulting contents of the specified model file.
String
400
Bad request. The request was not formatted correctly.
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:
application/json
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.
application/json
Responses
200
Successful response that contains the resulting files related with the specified model.
String
400
Bad request. The request was not formatted correctly.
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.
application/json
Responses
200
Successful response that contains the resulting deep learning models.
400
Bad request. The request was not formatted correctly.
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.
application/json
Responses
200
The deep learning model file is modified on the server.
400
Bad request. The request was not formatted correctly.
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.
application/json
Responses
200
The deep learning model is modified on the server.
400
Bad request. The request was not formatted correctly.
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.
application/json
Responses
200
Successful response which contains a list of deep learning Spark application instances.
400
Bad request. The request was not formatted correctly.
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:
application/json
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.
fields (optional)
Query Parameter — fields
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
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.
application/json
Responses
200
Successful response which contains a list of deep learning Spark applications.
400
Bad request. The request was not formatted correctly.
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.
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.
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.
String The gradient synchronization mode in elastic distributed training. This parameter to specify whether the training is a synchronous training, or an asynchronous training.