Description Usage Arguments Value Request syntax
View source: R/sagemaker_operations.R
Starts a hyperparameter tuning job. A hyperparameter tuning job finds the best version of a model by running many training jobs on your dataset using the algorithm you choose and values for hyperparameters within ranges that you specify. It then chooses the hyperparameter values that result in a model that performs the best, as measured by an objective metric that you choose.
1 2 3 | sagemaker_create_hyper_parameter_tuning_job(HyperParameterTuningJobName,
HyperParameterTuningJobConfig, TrainingJobDefinition,
TrainingJobDefinitions, WarmStartConfig, Tags)
|
HyperParameterTuningJobName |
[required] The name of the tuning job. This name is the prefix for the names of all training jobs that this tuning job launches. The name must be unique within the same AWS account and AWS Region. The name must have 1 to 32 characters. Valid characters are a-z, A-Z, 0-9, and : + = @ _ % - (hyphen). The name is not case sensitive. |
HyperParameterTuningJobConfig |
[required] The HyperParameterTuningJobConfig object that describes the tuning job, including the search strategy, the objective metric used to evaluate training jobs, ranges of parameters to search, and resource limits for the tuning job. For more information, see How Hyperparameter Tuning Works. |
TrainingJobDefinition |
The HyperParameterTrainingJobDefinition object that describes the training jobs that this tuning job launches, including static hyperparameters, input data configuration, output data configuration, resource configuration, and stopping condition. |
TrainingJobDefinitions |
A list of the HyperParameterTrainingJobDefinition objects launched for this tuning job. |
WarmStartConfig |
Specifies the configuration for starting the hyperparameter tuning job using one or more previous tuning jobs as a starting point. The results of previous tuning jobs are used to inform which combinations of hyperparameters to search over in the new tuning job. All training jobs launched by the new hyperparameter tuning job are
evaluated by using the objective metric. If you specify
All training jobs launched by parent hyperparameter tuning jobs and the new hyperparameter tuning jobs count against the limit of training jobs for the tuning job. |
Tags |
An array of key-value pairs. You can use tags to categorize your AWS resources in different ways, for example, by purpose, owner, or environment. For more information, see Tagging AWS Resources. Tags that you specify for the tuning job are also added to all training jobs that the tuning job launches. |
A list with the following syntax:
1 2 3 | list(
HyperParameterTuningJobArn = "string"
)
|
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 117 118 119 120 121 122 123 124 125 126 127 128 129 130 131 132 133 134 135 136 137 138 139 140 141 142 143 144 145 146 147 148 149 150 151 152 153 154 155 156 157 158 159 160 161 162 163 164 165 166 167 168 169 170 171 172 173 174 175 176 177 178 179 180 181 182 183 184 185 186 187 188 189 190 191 192 193 194 195 196 197 198 199 200 201 202 203 204 205 206 207 208 209 210 211 212 213 214 215 216 217 218 219 220 221 222 223 224 225 226 227 228 229 230 231 232 233 234 235 236 237 238 239 240 241 242 243 244 245 246 247 248 249 250 251 252 253 254 255 256 257 258 259 260 261 262 263 264 265 266 267 268 269 270 | svc$create_hyper_parameter_tuning_job(
HyperParameterTuningJobName = "string",
HyperParameterTuningJobConfig = list(
Strategy = "Bayesian"|"Random",
HyperParameterTuningJobObjective = list(
Type = "Maximize"|"Minimize",
MetricName = "string"
),
ResourceLimits = list(
MaxNumberOfTrainingJobs = 123,
MaxParallelTrainingJobs = 123
),
ParameterRanges = list(
IntegerParameterRanges = list(
list(
Name = "string",
MinValue = "string",
MaxValue = "string",
ScalingType = "Auto"|"Linear"|"Logarithmic"|"ReverseLogarithmic"
)
),
ContinuousParameterRanges = list(
list(
Name = "string",
MinValue = "string",
MaxValue = "string",
ScalingType = "Auto"|"Linear"|"Logarithmic"|"ReverseLogarithmic"
)
),
CategoricalParameterRanges = list(
list(
Name = "string",
Values = list(
"string"
)
)
)
),
TrainingJobEarlyStoppingType = "Off"|"Auto",
TuningJobCompletionCriteria = list(
TargetObjectiveMetricValue = 123.0
)
),
TrainingJobDefinition = list(
DefinitionName = "string",
TuningObjective = list(
Type = "Maximize"|"Minimize",
MetricName = "string"
),
HyperParameterRanges = list(
IntegerParameterRanges = list(
list(
Name = "string",
MinValue = "string",
MaxValue = "string",
ScalingType = "Auto"|"Linear"|"Logarithmic"|"ReverseLogarithmic"
)
),
ContinuousParameterRanges = list(
list(
Name = "string",
MinValue = "string",
MaxValue = "string",
ScalingType = "Auto"|"Linear"|"Logarithmic"|"ReverseLogarithmic"
)
),
CategoricalParameterRanges = list(
list(
Name = "string",
Values = list(
"string"
)
)
)
),
StaticHyperParameters = list(
"string"
),
AlgorithmSpecification = list(
TrainingImage = "string",
TrainingInputMode = "Pipe"|"File",
AlgorithmName = "string",
MetricDefinitions = list(
list(
Name = "string",
Regex = "string"
)
)
),
RoleArn = "string",
InputDataConfig = list(
list(
ChannelName = "string",
DataSource = list(
S3DataSource = list(
S3DataType = "ManifestFile"|"S3Prefix"|"AugmentedManifestFile",
S3Uri = "string",
S3DataDistributionType = "FullyReplicated"|"ShardedByS3Key",
AttributeNames = list(
"string"
)
),
FileSystemDataSource = list(
FileSystemId = "string",
FileSystemAccessMode = "rw"|"ro",
FileSystemType = "EFS"|"FSxLustre",
DirectoryPath = "string"
)
),
ContentType = "string",
CompressionType = "None"|"Gzip",
RecordWrapperType = "None"|"RecordIO",
InputMode = "Pipe"|"File",
ShuffleConfig = list(
Seed = 123
)
)
),
VpcConfig = list(
SecurityGroupIds = list(
"string"
),
Subnets = list(
"string"
)
),
OutputDataConfig = list(
KmsKeyId = "string",
S3OutputPath = "string"
),
ResourceConfig = list(
InstanceType = "ml.m4.xlarge"|"ml.m4.2xlarge"|"ml.m4.4xlarge"|"ml.m4.10xlarge"|"ml.m4.16xlarge"|"ml.g4dn.xlarge"|"ml.g4dn.2xlarge"|"ml.g4dn.4xlarge"|"ml.g4dn.8xlarge"|"ml.g4dn.12xlarge"|"ml.g4dn.16xlarge"|"ml.m5.large"|"ml.m5.xlarge"|"ml.m5.2xlarge"|"ml.m5.4xlarge"|"ml.m5.12xlarge"|"ml.m5.24xlarge"|"ml.c4.xlarge"|"ml.c4.2xlarge"|"ml.c4.4xlarge"|"ml.c4.8xlarge"|"ml.p2.xlarge"|"ml.p2.8xlarge"|"ml.p2.16xlarge"|"ml.p3.2xlarge"|"ml.p3.8xlarge"|"ml.p3.16xlarge"|"ml.p3dn.24xlarge"|"ml.p4d.24xlarge"|"ml.c5.xlarge"|"ml.c5.2xlarge"|"ml.c5.4xlarge"|"ml.c5.9xlarge"|"ml.c5.18xlarge"|"ml.c5n.xlarge"|"ml.c5n.2xlarge"|"ml.c5n.4xlarge"|"ml.c5n.9xlarge"|"ml.c5n.18xlarge",
InstanceCount = 123,
VolumeSizeInGB = 123,
VolumeKmsKeyId = "string"
),
StoppingCondition = list(
MaxRuntimeInSeconds = 123,
MaxWaitTimeInSeconds = 123
),
EnableNetworkIsolation = TRUE|FALSE,
EnableInterContainerTrafficEncryption = TRUE|FALSE,
EnableManagedSpotTraining = TRUE|FALSE,
CheckpointConfig = list(
S3Uri = "string",
LocalPath = "string"
)
),
TrainingJobDefinitions = list(
list(
DefinitionName = "string",
TuningObjective = list(
Type = "Maximize"|"Minimize",
MetricName = "string"
),
HyperParameterRanges = list(
IntegerParameterRanges = list(
list(
Name = "string",
MinValue = "string",
MaxValue = "string",
ScalingType = "Auto"|"Linear"|"Logarithmic"|"ReverseLogarithmic"
)
),
ContinuousParameterRanges = list(
list(
Name = "string",
MinValue = "string",
MaxValue = "string",
ScalingType = "Auto"|"Linear"|"Logarithmic"|"ReverseLogarithmic"
)
),
CategoricalParameterRanges = list(
list(
Name = "string",
Values = list(
"string"
)
)
)
),
StaticHyperParameters = list(
"string"
),
AlgorithmSpecification = list(
TrainingImage = "string",
TrainingInputMode = "Pipe"|"File",
AlgorithmName = "string",
MetricDefinitions = list(
list(
Name = "string",
Regex = "string"
)
)
),
RoleArn = "string",
InputDataConfig = list(
list(
ChannelName = "string",
DataSource = list(
S3DataSource = list(
S3DataType = "ManifestFile"|"S3Prefix"|"AugmentedManifestFile",
S3Uri = "string",
S3DataDistributionType = "FullyReplicated"|"ShardedByS3Key",
AttributeNames = list(
"string"
)
),
FileSystemDataSource = list(
FileSystemId = "string",
FileSystemAccessMode = "rw"|"ro",
FileSystemType = "EFS"|"FSxLustre",
DirectoryPath = "string"
)
),
ContentType = "string",
CompressionType = "None"|"Gzip",
RecordWrapperType = "None"|"RecordIO",
InputMode = "Pipe"|"File",
ShuffleConfig = list(
Seed = 123
)
)
),
VpcConfig = list(
SecurityGroupIds = list(
"string"
),
Subnets = list(
"string"
)
),
OutputDataConfig = list(
KmsKeyId = "string",
S3OutputPath = "string"
),
ResourceConfig = list(
InstanceType = "ml.m4.xlarge"|"ml.m4.2xlarge"|"ml.m4.4xlarge"|"ml.m4.10xlarge"|"ml.m4.16xlarge"|"ml.g4dn.xlarge"|"ml.g4dn.2xlarge"|"ml.g4dn.4xlarge"|"ml.g4dn.8xlarge"|"ml.g4dn.12xlarge"|"ml.g4dn.16xlarge"|"ml.m5.large"|"ml.m5.xlarge"|"ml.m5.2xlarge"|"ml.m5.4xlarge"|"ml.m5.12xlarge"|"ml.m5.24xlarge"|"ml.c4.xlarge"|"ml.c4.2xlarge"|"ml.c4.4xlarge"|"ml.c4.8xlarge"|"ml.p2.xlarge"|"ml.p2.8xlarge"|"ml.p2.16xlarge"|"ml.p3.2xlarge"|"ml.p3.8xlarge"|"ml.p3.16xlarge"|"ml.p3dn.24xlarge"|"ml.p4d.24xlarge"|"ml.c5.xlarge"|"ml.c5.2xlarge"|"ml.c5.4xlarge"|"ml.c5.9xlarge"|"ml.c5.18xlarge"|"ml.c5n.xlarge"|"ml.c5n.2xlarge"|"ml.c5n.4xlarge"|"ml.c5n.9xlarge"|"ml.c5n.18xlarge",
InstanceCount = 123,
VolumeSizeInGB = 123,
VolumeKmsKeyId = "string"
),
StoppingCondition = list(
MaxRuntimeInSeconds = 123,
MaxWaitTimeInSeconds = 123
),
EnableNetworkIsolation = TRUE|FALSE,
EnableInterContainerTrafficEncryption = TRUE|FALSE,
EnableManagedSpotTraining = TRUE|FALSE,
CheckpointConfig = list(
S3Uri = "string",
LocalPath = "string"
)
)
),
WarmStartConfig = list(
ParentHyperParameterTuningJobs = list(
list(
HyperParameterTuningJobName = "string"
)
),
WarmStartType = "IdenticalDataAndAlgorithm"|"TransferLearning"
),
Tags = list(
list(
Key = "string",
Value = "string"
)
)
)
|
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