Class: Aws::SageMaker::Types::TrainingSpecification
- Inherits:
-
Struct
- Object
- Struct
- Aws::SageMaker::Types::TrainingSpecification
- Includes:
- Aws::Structure
- Defined in:
- lib/aws-sdk-sagemaker/types.rb
Overview
When making an API call, you may pass TrainingSpecification data as a hash:
{
training_image: "Image", # required
training_image_digest: "ImageDigest",
supported_hyper_parameters: [
{
name: "ParameterName", # required
description: "EntityDescription",
type: "Integer", # required, accepts Integer, Continuous, Categorical, FreeText
range: {
integer_parameter_range_specification: {
min_value: "ParameterValue", # required
max_value: "ParameterValue", # required
},
continuous_parameter_range_specification: {
min_value: "ParameterValue", # required
max_value: "ParameterValue", # required
},
categorical_parameter_range_specification: {
values: ["ParameterValue"], # required
},
},
is_tunable: false,
is_required: false,
default_value: "ParameterValue",
},
],
supported_training_instance_types: ["ml.m4.xlarge"], # required, accepts ml.m4.xlarge, ml.m4.2xlarge, ml.m4.4xlarge, ml.m4.10xlarge, ml.m4.16xlarge, 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.c5.xlarge, ml.c5.2xlarge, ml.c5.4xlarge, ml.c5.9xlarge, ml.c5.18xlarge
supports_distributed_training: false,
metric_definitions: [
{
name: "MetricName", # required
regex: "MetricRegex", # required
},
],
training_channels: [ # required
{
name: "ChannelName", # required
description: "EntityDescription",
is_required: false,
supported_content_types: ["ContentType"], # required
supported_compression_types: ["None"], # accepts None, Gzip
supported_input_modes: ["Pipe"], # required, accepts Pipe, File
},
],
supported_tuning_job_objective_metrics: [
{
type: "Maximize", # required, accepts Maximize, Minimize
metric_name: "MetricName", # required
},
],
}
Defines how the algorithm is used for a training job.
Instance Attribute Summary collapse
-
#metric_definitions ⇒ Array<Types::MetricDefinition>
A list of ‘MetricDefinition` objects, which are used for parsing metrics generated by the algorithm.
-
#supported_hyper_parameters ⇒ Array<Types::HyperParameterSpecification>
A list of the ‘HyperParameterSpecification` objects, that define the supported hyperparameters.
-
#supported_training_instance_types ⇒ Array<String>
A list of the instance types that this algorithm can use for training.
-
#supported_tuning_job_objective_metrics ⇒ Array<Types::HyperParameterTuningJobObjective>
A list of the metrics that the algorithm emits that can be used as the objective metric in a hyperparameter tuning job.
-
#supports_distributed_training ⇒ Boolean
Indicates whether the algorithm supports distributed training.
-
#training_channels ⇒ Array<Types::ChannelSpecification>
A list of ‘ChannelSpecification` objects, which specify the input sources to be used by the algorithm.
-
#training_image ⇒ String
The Amazon ECR registry path of the Docker image that contains the training algorithm.
-
#training_image_digest ⇒ String
An MD5 hash of the training algorithm that identifies the Docker image used for training.
Instance Attribute Details
#metric_definitions ⇒ Array<Types::MetricDefinition>
A list of ‘MetricDefinition` objects, which are used for parsing metrics generated by the algorithm.
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# File 'lib/aws-sdk-sagemaker/types.rb', line 10657 class TrainingSpecification < Struct.new( :training_image, :training_image_digest, :supported_hyper_parameters, :supported_training_instance_types, :supports_distributed_training, :metric_definitions, :training_channels, :supported_tuning_job_objective_metrics) include Aws::Structure end |
#supported_hyper_parameters ⇒ Array<Types::HyperParameterSpecification>
A list of the ‘HyperParameterSpecification` objects, that define the supported hyperparameters. This is required if the algorithm supports automatic model tuning.>
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# File 'lib/aws-sdk-sagemaker/types.rb', line 10657 class TrainingSpecification < Struct.new( :training_image, :training_image_digest, :supported_hyper_parameters, :supported_training_instance_types, :supports_distributed_training, :metric_definitions, :training_channels, :supported_tuning_job_objective_metrics) include Aws::Structure end |
#supported_training_instance_types ⇒ Array<String>
A list of the instance types that this algorithm can use for training.
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# File 'lib/aws-sdk-sagemaker/types.rb', line 10657 class TrainingSpecification < Struct.new( :training_image, :training_image_digest, :supported_hyper_parameters, :supported_training_instance_types, :supports_distributed_training, :metric_definitions, :training_channels, :supported_tuning_job_objective_metrics) include Aws::Structure end |
#supported_tuning_job_objective_metrics ⇒ Array<Types::HyperParameterTuningJobObjective>
A list of the metrics that the algorithm emits that can be used as the objective metric in a hyperparameter tuning job.
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# File 'lib/aws-sdk-sagemaker/types.rb', line 10657 class TrainingSpecification < Struct.new( :training_image, :training_image_digest, :supported_hyper_parameters, :supported_training_instance_types, :supports_distributed_training, :metric_definitions, :training_channels, :supported_tuning_job_objective_metrics) include Aws::Structure end |
#supports_distributed_training ⇒ Boolean
Indicates whether the algorithm supports distributed training. If set to false, buyers can’t request more than one instance during training.
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# File 'lib/aws-sdk-sagemaker/types.rb', line 10657 class TrainingSpecification < Struct.new( :training_image, :training_image_digest, :supported_hyper_parameters, :supported_training_instance_types, :supports_distributed_training, :metric_definitions, :training_channels, :supported_tuning_job_objective_metrics) include Aws::Structure end |
#training_channels ⇒ Array<Types::ChannelSpecification>
A list of ‘ChannelSpecification` objects, which specify the input sources to be used by the algorithm.
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# File 'lib/aws-sdk-sagemaker/types.rb', line 10657 class TrainingSpecification < Struct.new( :training_image, :training_image_digest, :supported_hyper_parameters, :supported_training_instance_types, :supports_distributed_training, :metric_definitions, :training_channels, :supported_tuning_job_objective_metrics) include Aws::Structure end |
#training_image ⇒ String
The Amazon ECR registry path of the Docker image that contains the training algorithm.
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# File 'lib/aws-sdk-sagemaker/types.rb', line 10657 class TrainingSpecification < Struct.new( :training_image, :training_image_digest, :supported_hyper_parameters, :supported_training_instance_types, :supports_distributed_training, :metric_definitions, :training_channels, :supported_tuning_job_objective_metrics) include Aws::Structure end |
#training_image_digest ⇒ String
An MD5 hash of the training algorithm that identifies the Docker image used for training.
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# File 'lib/aws-sdk-sagemaker/types.rb', line 10657 class TrainingSpecification < Struct.new( :training_image, :training_image_digest, :supported_hyper_parameters, :supported_training_instance_types, :supports_distributed_training, :metric_definitions, :training_channels, :supported_tuning_job_objective_metrics) include Aws::Structure end |