Python load_imagenet_for_validation 예제들

예제 #1

def InferenceNet():
    assert os.path.exists(args.val_data_dir)
    print("Loading data from {}".format(args.val_data_dir))
    (labels, images) = ofrecord_util.load_imagenet_for_validation(args)

    logits = model_dict[args.model](images, args)
    predictions = flow.nn.softmax(logits)
    outputs = {"predictions": predictions, "labels": labels}
    return outputs

예제 #2

파일: of_cnn_train_val.py 프로젝트: yayeoCddy/OneFlow-Benchmark

def InferenceNet():
    if args.val_data_dir:
        assert os.path.exists(args.val_data_dir)
        print("Loading data from {}".format(args.val_data_dir))
        (labels, images) = ofrecord_util.load_imagenet_for_validation(args)

    else:
        print("Loading synthetic data.")
        (labels, images) = ofrecord_util.load_synthetic(args)

    logits = model_dict[args.model](
        images, need_transpose=False if args.val_data_dir else True)
    predictions = flow.nn.softmax(logits)
    outputs = {"predictions": predictions, "labels": labels}
    return outputs