84 lines
3.3 KiB
TypeScript
84 lines
3.3 KiB
TypeScript
import type { TrainingConfigState } from "../types/config";
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import type { TrainingStartRequest } from "../types/api";
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const BACKEND_LORA_TYPE = "LoRA/QLoRA";
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const BACKEND_FULL_TYPE = "Full Finetuning";
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function parseSliceValue(value: string | null): number | null {
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if (value == null) return null;
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const trimmed = value.trim();
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if (!trimmed) return null;
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const num = Number(trimmed);
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if (!Number.isFinite(num) || !Number.isInteger(num)) return null;
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return num;
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}
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export function toBackendTrainingType(trainingMethod: string): string {
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return trainingMethod === "full" ? BACKEND_FULL_TYPE : BACKEND_LORA_TYPE;
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}
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export function buildTrainingStartPayload(
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config: TrainingConfigState,
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): TrainingStartRequest {
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const adapterMethod = config.trainingMethod !== "full";
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const isQlorMethod = config.trainingMethod === "qlora";
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const hfDataset = config.datasetSource === "huggingface" ? config.dataset : null;
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const customFormatMapping =
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Object.keys(config.datasetManualMapping).length > 0 ? config.datasetManualMapping : undefined;
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return {
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model_name: config.selectedModel ?? "",
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training_type: toBackendTrainingType(config.trainingMethod),
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hf_token: config.hfToken.trim() || null,
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load_in_4bit: adapterMethod ? isQlorMethod : false,
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max_seq_length: config.contextLength,
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hf_dataset: hfDataset,
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subset: hfDataset ? config.datasetSubset : null,
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train_split: hfDataset ? config.datasetSplit : null,
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eval_split: hfDataset ? config.datasetEvalSplit : null,
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dataset_slice_start: parseSliceValue(config.datasetSliceStart),
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dataset_slice_end: parseSliceValue(config.datasetSliceEnd),
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local_datasets: [],
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format_type: config.datasetFormat,
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custom_format_mapping: customFormatMapping,
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num_epochs: config.epochs,
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learning_rate: String(config.learningRate),
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batch_size: config.batchSize,
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gradient_accumulation_steps: config.gradientAccumulation,
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warmup_steps: config.warmupSteps,
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warmup_ratio: null,
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max_steps: config.maxSteps,
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save_steps: config.saveSteps,
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eval_steps: config.evalSteps,
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weight_decay: config.weightDecay,
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random_seed: config.randomSeed,
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packing: config.packing,
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optim: config.optimizerType,
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lr_scheduler_type: config.lrSchedulerType,
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use_lora: adapterMethod,
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lora_r: config.loraRank,
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lora_alpha: config.loraAlpha,
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lora_dropout: config.loraDropout,
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target_modules: adapterMethod ? config.targetModules : [],
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gradient_checkpointing: config.gradientCheckpointing,
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use_rslora: config.loraVariant === "rslora",
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use_loftq: config.loraVariant === "loftq",
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train_on_completions: config.trainOnCompletions,
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finetune_vision_layers: config.finetuneVisionLayers,
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finetune_language_layers: config.finetuneLanguageLayers,
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finetune_attention_modules: config.finetuneAttentionModules,
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finetune_mlp_modules: config.finetuneMLPModules,
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is_dataset_image: !!config.isDatasetImage,
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is_dataset_audio: config.isDatasetAudio,
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enable_wandb: config.enableWandb,
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wandb_token: config.enableWandb ? config.wandbToken.trim() || null : null,
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wandb_project: config.enableWandb
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? config.wandbProject.trim() || null
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: null,
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enable_tensorboard: config.enableTensorboard,
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tensorboard_dir: config.enableTensorboard
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? config.tensorboardDir.trim() || null
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: null,
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};
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}
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