How to use TSDataLoader to train large datasets on TSClassifier

Can somebody please help to let me know how to use TSDataLoader with TSClassifier.
Below is my code.

import numpy as np
import multiprocessing
from tsai.basics import *
from tsai.all import *
from fastai.metrics import Recall, Precision
from fastai.callback.tracker import SaveModelCallback, EarlyStoppingCallback
from fastai.losses import FocalLoss
from import TSDataset

def train(dataset_idx):
    print("starting process:", dataset_idx)
    X_train = np.load(str(dataset_idx)+'_X_train.npy').transpose((0, 2, 1))
    y_train = np.load(str(dataset_idx)+'_y_train.npy').astype(int)
    X_test = np.load(str(dataset_idx)+'_X_test.npy').transpose((0, 2, 1))
    y_test = np.load(str(dataset_idx)+'_y_test.npy').astype(int)
    l = X_train.shape[0]
    print("data loaded")
    X_train = np.concatenate([X_train, X_test], axis=0)
    y_train = np.concatenate([y_train, y_test], axis=0)
    del X_test, y_test
    splits = [i for i in range(l)], [i for i in range(l, X_train.shape[0])]
    print("dataset generated")

    tfms = [None, TSClassification()]
    batch_tfms = TSStandardize()
    precision = Precision()
    recall = Recall()
    save_callback =  SaveModelCallback(monitor='valid_loss', comp=None, fname='sample_best_model', every_epoch=False, at_end=False, with_opt=False, reset_on_fit=True)
    early_stopping = EarlyStoppingCallback(monitor='valid_loss', patience=10)
    dataset = TSDataset(X_train, y=y_train, split=splits)
    dataloader = TSDataLoader(dataset, bs=2048, shuffle=True)

    //stuck here on how to use dataloader in TSCLassifier as it expects X_train and y_train

    clf = TSClassifier(X_train, y_train, splits=splits, arch="InceptionTimePlus", loss_func=FocalLoss(), tfms=tfms, batch_tfms=batch_tfms, bs=[2048], metrics=[precision, recall], cbs=[save_callback, early_stopping])
    clf.fit_one_cycle(10, 2.5e-4)