Class: OCI::GenerativeAi::Models::TrainingConfig

Inherits:
Object
  • Object
show all
Defined in:
lib/oci/generative_ai/models/training_config.rb

Overview

The fine-tuning method and hyperparameters used for fine-tuning a custom model. This class has direct subclasses. If you are using this class as input to a service operations then you should favor using a subclass over the base class

Constant Summary collapse

TRAINING_CONFIG_TYPE_ENUM = 
[
  TRAINING_CONFIG_TYPE_TFEW_TRAINING_CONFIG = 'TFEW_TRAINING_CONFIG'.freeze,
  TRAINING_CONFIG_TYPE_VANILLA_TRAINING_CONFIG = 'VANILLA_TRAINING_CONFIG'.freeze,
  TRAINING_CONFIG_TYPE_LORA_TRAINING_CONFIG = 'LORA_TRAINING_CONFIG'.freeze,
  TRAINING_CONFIG_TYPE_UNKNOWN_ENUM_VALUE = 'UNKNOWN_ENUM_VALUE'.freeze
].freeze

Instance Attribute Summary collapse

Class Method Summary collapse

Instance Method Summary collapse

Constructor Details

#initialize(attributes = {}) ⇒ TrainingConfig

Initializes the object

Parameters:

  • attributes (Hash) (defaults to: {}) —

    Model attributes in the form of hash

Options Hash (attributes):



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# File 'lib/oci/generative_ai/models/training_config.rb', line 112

def initialize(attributes = {})
  return unless attributes.is_a?(Hash)

  # convert string to symbol for hash key
  attributes = attributes.each_with_object({}) { |(k, v), h| h[k.to_sym] = v }

  self.training_config_type = attributes[:'trainingConfigType'] if attributes[:'trainingConfigType']
  self.training_config_type = "TFEW_TRAINING_CONFIG" if training_config_type.nil? && !attributes.key?(:'trainingConfigType') # rubocop:disable Style/StringLiterals

  raise 'You cannot provide both :trainingConfigType and :training_config_type' if attributes.key?(:'trainingConfigType') && attributes.key?(:'training_config_type')

  self.training_config_type = attributes[:'training_config_type'] if attributes[:'training_config_type']
  self.training_config_type = "TFEW_TRAINING_CONFIG" if training_config_type.nil? && !attributes.key?(:'trainingConfigType') && !attributes.key?(:'training_config_type') # rubocop:disable Style/StringLiterals

  self.total_training_epochs = attributes[:'totalTrainingEpochs'] if attributes[:'totalTrainingEpochs']

  raise 'You cannot provide both :totalTrainingEpochs and :total_training_epochs' if attributes.key?(:'totalTrainingEpochs') && attributes.key?(:'total_training_epochs')

  self.total_training_epochs = attributes[:'total_training_epochs'] if attributes[:'total_training_epochs']

  self.learning_rate = attributes[:'learningRate'] if attributes[:'learningRate']

  raise 'You cannot provide both :learningRate and :learning_rate' if attributes.key?(:'learningRate') && attributes.key?(:'learning_rate')

  self.learning_rate = attributes[:'learning_rate'] if attributes[:'learning_rate']

  self.training_batch_size = attributes[:'trainingBatchSize'] if attributes[:'trainingBatchSize']

  raise 'You cannot provide both :trainingBatchSize and :training_batch_size' if attributes.key?(:'trainingBatchSize') && attributes.key?(:'training_batch_size')

  self.training_batch_size = attributes[:'training_batch_size'] if attributes[:'training_batch_size']

  self.early_stopping_patience = attributes[:'earlyStoppingPatience'] if attributes[:'earlyStoppingPatience']

  raise 'You cannot provide both :earlyStoppingPatience and :early_stopping_patience' if attributes.key?(:'earlyStoppingPatience') && attributes.key?(:'early_stopping_patience')

  self.early_stopping_patience = attributes[:'early_stopping_patience'] if attributes[:'early_stopping_patience']

  self.early_stopping_threshold = attributes[:'earlyStoppingThreshold'] if attributes[:'earlyStoppingThreshold']

  raise 'You cannot provide both :earlyStoppingThreshold and :early_stopping_threshold' if attributes.key?(:'earlyStoppingThreshold') && attributes.key?(:'early_stopping_threshold')

  self.early_stopping_threshold = attributes[:'early_stopping_threshold'] if attributes[:'early_stopping_threshold']

  self.log_model_metrics_interval_in_steps = attributes[:'logModelMetricsIntervalInSteps'] if attributes[:'logModelMetricsIntervalInSteps']

  raise 'You cannot provide both :logModelMetricsIntervalInSteps and :log_model_metrics_interval_in_steps' if attributes.key?(:'logModelMetricsIntervalInSteps') && attributes.key?(:'log_model_metrics_interval_in_steps')

  self.log_model_metrics_interval_in_steps = attributes[:'log_model_metrics_interval_in_steps'] if attributes[:'log_model_metrics_interval_in_steps']
end

Instance Attribute Details

#early_stopping_patience ⇒ Integer

Stop training if the loss metric does not improve beyond 'early_stopping_threshold' for this many times of evaluation.

Returns:

  • (Integer) 


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# File 'lib/oci/generative_ai/models/training_config.rb', line 39

def early_stopping_patience
  @early_stopping_patience
end

#early_stopping_threshold ⇒ Float

How much the loss must improve to prevent early stopping.

Returns:

  • (Float) 


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# File 'lib/oci/generative_ai/models/training_config.rb', line 43

def early_stopping_threshold
  @early_stopping_threshold
end

#learning_rate ⇒ Float

The initial learning rate to be used during training

Returns:

  • (Float) 


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# File 'lib/oci/generative_ai/models/training_config.rb', line 30

def learning_rate
  @learning_rate
end

#log_model_metrics_interval_in_steps ⇒ Integer

Determines how frequently to log model metrics.

Every step is logged for the first 20 steps and then follows this parameter for log frequency. Set to 0 to disable logging the model metrics.

Returns:

  • (Integer) 


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# File 'lib/oci/generative_ai/models/training_config.rb', line 50

def log_model_metrics_interval_in_steps
  @log_model_metrics_interval_in_steps
end

#total_training_epochs ⇒ Integer

The maximum number of training epochs to run for.

Returns:

  • (Integer) 


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# File 'lib/oci/generative_ai/models/training_config.rb', line 26

def total_training_epochs
  @total_training_epochs
end

#training_batch_size ⇒ Integer

The batch size used during training.

Returns:

  • (Integer) 


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# File 'lib/oci/generative_ai/models/training_config.rb', line 34

def training_batch_size
  @training_batch_size
end

#training_config_type ⇒ String

[Required] The fine-tuning method for training a custom model.

Returns:

  • (String) 


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# File 'lib/oci/generative_ai/models/training_config.rb', line 22

def training_config_type
  @training_config_type
end

Class Method Details

.attribute_map ⇒ Object

Attribute mapping from ruby-style variable name to JSON key.



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# File 'lib/oci/generative_ai/models/training_config.rb', line 53

def self.attribute_map
  {
    # rubocop:disable Style/SymbolLiteral
    'training_config_type': :'trainingConfigType',
    'total_training_epochs': :'totalTrainingEpochs',
    'learning_rate': :'learningRate',
    'training_batch_size': :'trainingBatchSize',
    'early_stopping_patience': :'earlyStoppingPatience',
    'early_stopping_threshold': :'earlyStoppingThreshold',
    'log_model_metrics_interval_in_steps': :'logModelMetricsIntervalInSteps'
    # rubocop:enable Style/SymbolLiteral
  }
end

.get_subtype(object_hash) ⇒ Object

Given the hash representation of a subtype of this class, use the info in the hash to return the class of the subtype.



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# File 'lib/oci/generative_ai/models/training_config.rb', line 87

def self.get_subtype(object_hash)
  type = object_hash[:'trainingConfigType'] # rubocop:disable Style/SymbolLiteral

  return 'OCI::GenerativeAi::Models::LoraTrainingConfig' if type == 'LORA_TRAINING_CONFIG'
  return 'OCI::GenerativeAi::Models::VanillaTrainingConfig' if type == 'VANILLA_TRAINING_CONFIG'
  return 'OCI::GenerativeAi::Models::TFewTrainingConfig' if type == 'TFEW_TRAINING_CONFIG'

  # TODO: Log a warning when the subtype is not found.
  'OCI::GenerativeAi::Models::TrainingConfig'
end

.swagger_types ⇒ Object

Attribute type mapping.



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# File 'lib/oci/generative_ai/models/training_config.rb', line 68

def self.swagger_types
  {
    # rubocop:disable Style/SymbolLiteral
    'training_config_type': :'String',
    'total_training_epochs': :'Integer',
    'learning_rate': :'Float',
    'training_batch_size': :'Integer',
    'early_stopping_patience': :'Integer',
    'early_stopping_threshold': :'Float',
    'log_model_metrics_interval_in_steps': :'Integer'
    # rubocop:enable Style/SymbolLiteral
  }
end

Instance Method Details

#==(other) ⇒ Object

Checks equality by comparing each attribute.

Parameters:

  • other (Object) —

    the other object to be compared



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# File 'lib/oci/generative_ai/models/training_config.rb', line 183

def ==(other)
  return true if equal?(other)

  self.class == other.class &&
    training_config_type == other.training_config_type &&
    total_training_epochs == other.total_training_epochs &&
    learning_rate == other.learning_rate &&
    training_batch_size == other.training_batch_size &&
    early_stopping_patience == other.early_stopping_patience &&
    early_stopping_threshold == other.early_stopping_threshold &&
    log_model_metrics_interval_in_steps == other.log_model_metrics_interval_in_steps
end

#build_from_hash(attributes) ⇒ Object

Builds the object from hash

Parameters:

  • attributes (Hash) —

    Model attributes in the form of hash

Returns:

  • (Object) —

    Returns the model itself



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# File 'lib/oci/generative_ai/models/training_config.rb', line 219

def build_from_hash(attributes)
  return nil unless attributes.is_a?(Hash)

  self.class.swagger_types.each_pair do |key, type|
    if type =~ /^Array<(.*)>/i
      # check to ensure the input is an array given that the the attribute
      # is documented as an array but the input is not
      if attributes[self.class.attribute_map[key]].is_a?(Array)
        public_method("#{key}=").call(
          attributes[self.class.attribute_map[key]]
            .map { |v| OCI::Internal::Util.convert_to_type(Regexp.last_match(1), v) }
        )
      end
    elsif !attributes[self.class.attribute_map[key]].nil?
      public_method("#{key}=").call(
        OCI::Internal::Util.convert_to_type(type, attributes[self.class.attribute_map[key]])
      )
    end
    # or else data not found in attributes(hash), not an issue as the data can be optional
  end

  self
end

#eql?(other) ⇒ Boolean

Parameters:

  • other (Object) —

    the other object to be compared

Returns:

  • (Boolean)

See Also:

  • `==` method


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# File 'lib/oci/generative_ai/models/training_config.rb', line 199

def eql?(other)
  self == other
end

#hash ⇒ Fixnum

Calculates hash code according to all attributes.

Returns:

  • (Fixnum) —

    Hash code



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# File 'lib/oci/generative_ai/models/training_config.rb', line 208

def hash
  [training_config_type, total_training_epochs, learning_rate, training_batch_size, early_stopping_patience, early_stopping_threshold, log_model_metrics_interval_in_steps].hash
end

#to_hash ⇒ Hash

Returns the object in the form of hash

Returns:

  • (Hash) —

    Returns the object in the form of hash



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# File 'lib/oci/generative_ai/models/training_config.rb', line 252

def to_hash
  hash = {}
  self.class.attribute_map.each_pair do |attr, param|
    value = public_method(attr).call
    next if value.nil? && !instance_variable_defined?("@#{attr}")

    hash[param] = _to_hash(value)
  end
  hash
end

#to_s ⇒ String

Returns the string representation of the object

Returns:

  • (String) —

    String presentation of the object



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# File 'lib/oci/generative_ai/models/training_config.rb', line 246

def to_s
  to_hash.to_s
end