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/**
 * 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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