code snipped of create numTrainInstance:
    vidSeqTrain = makeDataset(trainDataset, trainLabels, spatial_transform=spatial_transform,
                                seqLen=seqLen)
    # torch iterator to give data in batches of specified size
    trainLoader = torch.utils.data.DataLoader(vidSeqTrain, batch_size=trainBatchSize,
                            shuffle=True, num_workers=numWorkers, pin_memory=True, drop_last=True)
mean, std=std)])
    
    vidSeqValid = makeDataset(validationDataset, validationLabels, seqLen=seqLen,
    spatial_transform=test_spatial_transform)

    validationLoader = torch.utils.data.DataLoader(vidSeqValid, batch_size=1,
                            shuffle=False, num_workers=int(numWorkers/2), pin_memory=True)

    numTrainInstances = vidSeqTrain.__len__()
    numValidationInstances = vidSeqValid.__len__()


<class ‘int’>