Given a short query with keyphrases about a research idea in 2019 in the domain of artificial intelligence, recommend the relevant datasets to validate the research idea from options provided. A short description of the datasets is also provided to help you.

Query: I am implementing an AutoGAN system for image generation.

Keyphrases: image generation images

Dataset description:
ConvAI2: The ConvAI2 NeurIPS competition aimed at finding approaches to creating high-quality dialogue agents capable of meaningful open domain conversation. The ConvAI2 dataset for training models is based on the PERSONA-CHAT dataset.
CIFAR-10: The CIFAR-10 dataset (Canadian Institute for Advanced Research, 10 classes) is a subset of the Tiny Images dataset and consists of 60000 32x32 color images. The images are labelled with one of 10 mutually exclusive classes: airplane, automobile (but not truck or pickup truck), bird, cat, deer, dog, frog, horse, ship, and truck (but not pickup truck).
AM-2k: AM-2k (Animal Matting 2,000 Dataset) consists of 2,000 high-resolution images collected and carefully selected from websites with open licenses. AM-2k contains 20 categories of animals including alpaca, antelope, bear, camel, cat, cattle, deer, dog, elephant, giraffe, horse, kangaroo, leopard, lion, monkey, rabbit, rhinoceros, sheep, tiger, zebra, each with 100 real-world images of various appearance and diverse backgrounds
CommonsenseQA: The CommonsenseQA is a dataset for commonsense question answering task. The dataset consists of 12,247 questions with 5 choices each.

Options:- A: ConvAI2  B: CIFAR-10  C: AM-2k  D: CommonsenseQA
CIFAR-10