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This project contains the SDK distribution used for Oracle Cloud Infrastructure, and all the dependencies that can be shaded. It also has Maven dependencies that cannot be shaded. Therefore, use this module to depend on the shaded distribution via Maven -- it will shade everything that can be shaded, and automatically pull in the other dependencies.
/**
* Copyright (c) 2016, 2024, Oracle and/or its affiliates. All rights reserved.
* This software is dual-licensed to you under the Universal Permissive License (UPL) 1.0 as shown at https://oss.oracle.com/licenses/upl or Apache License 2.0 as shown at http://www.apache.org/licenses/LICENSE-2.0. You may choose either license.
*/
package com.oracle.bmc.generativeai.model;
/**
* The Lora training method hyperparameters.
* Note: Objects should always be created or deserialized using the {@link Builder}. This model
* distinguishes fields that are {@code null} because they are unset from fields that are explicitly
* set to {@code null}. This is done in the setter methods of the {@link Builder}, which maintain a
* set of all explicitly set fields called {@link Builder#__explicitlySet__}. The {@link
* #hashCode()} and {@link #equals(Object)} methods are implemented to take the explicitly set
* fields into account. The constructor, on the other hand, does not take the explicitly set fields
* into account (since the constructor cannot distinguish explicit {@code null} from unset {@code
* null}).
*/
@jakarta.annotation.Generated(value = "OracleSDKGenerator", comments = "API Version: 20231130")
@com.fasterxml.jackson.databind.annotation.JsonDeserialize(
builder = LoraTrainingConfig.Builder.class)
@com.fasterxml.jackson.annotation.JsonTypeInfo(
use = com.fasterxml.jackson.annotation.JsonTypeInfo.Id.NAME,
include = com.fasterxml.jackson.annotation.JsonTypeInfo.As.PROPERTY,
property = "trainingConfigType")
@com.fasterxml.jackson.annotation.JsonFilter(
com.oracle.bmc.http.client.internal.ExplicitlySetBmcModel.EXPLICITLY_SET_FILTER_NAME)
public final class LoraTrainingConfig extends TrainingConfig {
@com.fasterxml.jackson.databind.annotation.JsonPOJOBuilder(withPrefix = "")
public static class Builder {
@com.fasterxml.jackson.annotation.JsonProperty("totalTrainingEpochs")
private Integer totalTrainingEpochs;
public Builder totalTrainingEpochs(Integer totalTrainingEpochs) {
this.totalTrainingEpochs = totalTrainingEpochs;
this.__explicitlySet__.add("totalTrainingEpochs");
return this;
}
@com.fasterxml.jackson.annotation.JsonProperty("learningRate")
private Double learningRate;
public Builder learningRate(Double learningRate) {
this.learningRate = learningRate;
this.__explicitlySet__.add("learningRate");
return this;
}
@com.fasterxml.jackson.annotation.JsonProperty("trainingBatchSize")
private Integer trainingBatchSize;
public Builder trainingBatchSize(Integer trainingBatchSize) {
this.trainingBatchSize = trainingBatchSize;
this.__explicitlySet__.add("trainingBatchSize");
return this;
}
@com.fasterxml.jackson.annotation.JsonProperty("earlyStoppingPatience")
private Integer earlyStoppingPatience;
public Builder earlyStoppingPatience(Integer earlyStoppingPatience) {
this.earlyStoppingPatience = earlyStoppingPatience;
this.__explicitlySet__.add("earlyStoppingPatience");
return this;
}
@com.fasterxml.jackson.annotation.JsonProperty("earlyStoppingThreshold")
private Double earlyStoppingThreshold;
public Builder earlyStoppingThreshold(Double earlyStoppingThreshold) {
this.earlyStoppingThreshold = earlyStoppingThreshold;
this.__explicitlySet__.add("earlyStoppingThreshold");
return this;
}
@com.fasterxml.jackson.annotation.JsonProperty("logModelMetricsIntervalInSteps")
private Integer logModelMetricsIntervalInSteps;
public Builder logModelMetricsIntervalInSteps(Integer logModelMetricsIntervalInSteps) {
this.logModelMetricsIntervalInSteps = logModelMetricsIntervalInSteps;
this.__explicitlySet__.add("logModelMetricsIntervalInSteps");
return this;
}
/** This parameter represents the LoRA rank of the update matrices. */
@com.fasterxml.jackson.annotation.JsonProperty("loraR")
private Integer loraR;
/**
* This parameter represents the LoRA rank of the update matrices.
*
* @param loraR the value to set
* @return this builder
*/
public Builder loraR(Integer loraR) {
this.loraR = loraR;
this.__explicitlySet__.add("loraR");
return this;
}
/** This parameter represents the scaling factor for the weight matrices in LoRA. */
@com.fasterxml.jackson.annotation.JsonProperty("loraAlpha")
private Integer loraAlpha;
/**
* This parameter represents the scaling factor for the weight matrices in LoRA.
*
* @param loraAlpha the value to set
* @return this builder
*/
public Builder loraAlpha(Integer loraAlpha) {
this.loraAlpha = loraAlpha;
this.__explicitlySet__.add("loraAlpha");
return this;
}
/** This parameter indicates the dropout probability for LoRA layers. */
@com.fasterxml.jackson.annotation.JsonProperty("loraDropout")
private Double loraDropout;
/**
* This parameter indicates the dropout probability for LoRA layers.
*
* @param loraDropout the value to set
* @return this builder
*/
public Builder loraDropout(Double loraDropout) {
this.loraDropout = loraDropout;
this.__explicitlySet__.add("loraDropout");
return this;
}
@com.fasterxml.jackson.annotation.JsonIgnore
private final java.util.Set __explicitlySet__ = new java.util.HashSet();
public LoraTrainingConfig build() {
LoraTrainingConfig model =
new LoraTrainingConfig(
this.totalTrainingEpochs,
this.learningRate,
this.trainingBatchSize,
this.earlyStoppingPatience,
this.earlyStoppingThreshold,
this.logModelMetricsIntervalInSteps,
this.loraR,
this.loraAlpha,
this.loraDropout);
for (String explicitlySetProperty : this.__explicitlySet__) {
model.markPropertyAsExplicitlySet(explicitlySetProperty);
}
return model;
}
@com.fasterxml.jackson.annotation.JsonIgnore
public Builder copy(LoraTrainingConfig model) {
if (model.wasPropertyExplicitlySet("totalTrainingEpochs")) {
this.totalTrainingEpochs(model.getTotalTrainingEpochs());
}
if (model.wasPropertyExplicitlySet("learningRate")) {
this.learningRate(model.getLearningRate());
}
if (model.wasPropertyExplicitlySet("trainingBatchSize")) {
this.trainingBatchSize(model.getTrainingBatchSize());
}
if (model.wasPropertyExplicitlySet("earlyStoppingPatience")) {
this.earlyStoppingPatience(model.getEarlyStoppingPatience());
}
if (model.wasPropertyExplicitlySet("earlyStoppingThreshold")) {
this.earlyStoppingThreshold(model.getEarlyStoppingThreshold());
}
if (model.wasPropertyExplicitlySet("logModelMetricsIntervalInSteps")) {
this.logModelMetricsIntervalInSteps(model.getLogModelMetricsIntervalInSteps());
}
if (model.wasPropertyExplicitlySet("loraR")) {
this.loraR(model.getLoraR());
}
if (model.wasPropertyExplicitlySet("loraAlpha")) {
this.loraAlpha(model.getLoraAlpha());
}
if (model.wasPropertyExplicitlySet("loraDropout")) {
this.loraDropout(model.getLoraDropout());
}
return this;
}
}
/** Create a new builder. */
public static Builder builder() {
return new Builder();
}
public Builder toBuilder() {
return new Builder().copy(this);
}
@Deprecated
public LoraTrainingConfig(
Integer totalTrainingEpochs,
Double learningRate,
Integer trainingBatchSize,
Integer earlyStoppingPatience,
Double earlyStoppingThreshold,
Integer logModelMetricsIntervalInSteps,
Integer loraR,
Integer loraAlpha,
Double loraDropout) {
super(
totalTrainingEpochs,
learningRate,
trainingBatchSize,
earlyStoppingPatience,
earlyStoppingThreshold,
logModelMetricsIntervalInSteps);
this.loraR = loraR;
this.loraAlpha = loraAlpha;
this.loraDropout = loraDropout;
}
/** This parameter represents the LoRA rank of the update matrices. */
@com.fasterxml.jackson.annotation.JsonProperty("loraR")
private final Integer loraR;
/**
* This parameter represents the LoRA rank of the update matrices.
*
* @return the value
*/
public Integer getLoraR() {
return loraR;
}
/** This parameter represents the scaling factor for the weight matrices in LoRA. */
@com.fasterxml.jackson.annotation.JsonProperty("loraAlpha")
private final Integer loraAlpha;
/**
* This parameter represents the scaling factor for the weight matrices in LoRA.
*
* @return the value
*/
public Integer getLoraAlpha() {
return loraAlpha;
}
/** This parameter indicates the dropout probability for LoRA layers. */
@com.fasterxml.jackson.annotation.JsonProperty("loraDropout")
private final Double loraDropout;
/**
* This parameter indicates the dropout probability for LoRA layers.
*
* @return the value
*/
public Double getLoraDropout() {
return loraDropout;
}
@Override
public String toString() {
return this.toString(true);
}
/**
* Return a string representation of the object.
*
* @param includeByteArrayContents true to include the full contents of byte arrays
* @return string representation
*/
public String toString(boolean includeByteArrayContents) {
java.lang.StringBuilder sb = new java.lang.StringBuilder();
sb.append("LoraTrainingConfig(");
sb.append("super=").append(super.toString(includeByteArrayContents));
sb.append(", loraR=").append(String.valueOf(this.loraR));
sb.append(", loraAlpha=").append(String.valueOf(this.loraAlpha));
sb.append(", loraDropout=").append(String.valueOf(this.loraDropout));
sb.append(")");
return sb.toString();
}
@Override
public boolean equals(Object o) {
if (this == o) {
return true;
}
if (!(o instanceof LoraTrainingConfig)) {
return false;
}
LoraTrainingConfig other = (LoraTrainingConfig) o;
return java.util.Objects.equals(this.loraR, other.loraR)
&& java.util.Objects.equals(this.loraAlpha, other.loraAlpha)
&& java.util.Objects.equals(this.loraDropout, other.loraDropout)
&& super.equals(other);
}
@Override
public int hashCode() {
final int PRIME = 59;
int result = super.hashCode();
result = (result * PRIME) + (this.loraR == null ? 43 : this.loraR.hashCode());
result = (result * PRIME) + (this.loraAlpha == null ? 43 : this.loraAlpha.hashCode());
result = (result * PRIME) + (this.loraDropout == null ? 43 : this.loraDropout.hashCode());
return result;
}
}
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