"The Conv2D op currently only supports the NHWC tensor format on the CPU" 错误尽管 NHWC 格式 (YOLO 3)

Question

我正在尝试从 github in order to learn Working with Tensorflow 2 and the YOLO Framework. My Laptop has a M1000M Graphics Card and I installed the CUDA Platform from NVIDIA from here 中获取运行一些示例代码。

所以有问题的代码是这样的：

tf.compat.v1.disable_eager_execution()

_MODEL_SIZE = (416, 416)
_CLASS_NAMES_FILE = './data/labels/coco.names'
_MAX_OUTPUT_SIZE = 20


def main(type, iou_threshold, confidence_threshold, input_names):
    class_names = load_class_names(_CLASS_NAMES_FILE)
    n_classes = len(class_names)

    model = Yolo_v3(n_classes=n_classes, model_size=_MODEL_SIZE,
                    max_output_size=_MAX_OUTPUT_SIZE,
                    iou_threshold=iou_threshold,
                    confidence_threshold=confidence_threshold)

    if type == 'images':
        batch_size = len(input_names)
        batch = load_images(input_names, model_size=_MODEL_SIZE)
        inputs = tf.compat.v1.placeholder(tf.float32, [batch_size, *_MODEL_SIZE, 3])
        detections = model(inputs, training=False)
        saver = tf.compat.v1.train.Saver(tf.compat.v1.global_variables(scope='yolo_v3_model'))

        with tf.compat.v1.Session() as sess:
            saver.restore(sess, './weights/model.ckpt')
            detection_result = sess.run(detections, feed_dict={inputs: batch})

        draw_boxes(input_names, detection_result, class_names, _MODEL_SIZE)

        print('Detections have been saved successfully.')

执行此操作时（也想知道为什么启动 detection.py 不首先使用 GPU），我收到错误消息：

File "C:\SDKs etc\Python 3.8\lib\site-packages\tensorflow\python\client\session.py", line 1451, in _call_tf_sessionrun
    return tf_session.TF_SessionRun_wrapper(self._session, options, feed_dict,
tensorflow.python.framework.errors_impl.UnimplementedError: The Conv2D op currently only supports the NHWC tensor format on the CPU. The op was given the format: NCHW
         [[{{node yolo_v3_model/conv2d/Conv2D}}]]

完整日志见 here。

如果我理解正确，inputs = tf.compat.v1.placeholder(tf.float32, [batch_size, *_MODEL_SIZE, 3]) 的格式已经是 NHWC（模型大小是 2 个数字的元组），我不知道我需要如何更改代码中的内容才能得到这个运行宁 CPU。

Answer 1

If I am understanding this correctly, the format of inputs = tf.compat.v1.placeholder(tf.float32, [batch_size, *_MODEL_SIZE, 3]) is already NHWC (Model Size is a tuple of 2 Numbers) and I don't know how I need to change things in Code to get this running on CPU.

是的，你是。但是 look here:

def __init__(self, n_classes, model_size, max_output_size, iou_threshold,
                 confidence_threshold, data_format=None):
        """Creates the model.
        Args:
            n_classes: Number of class labels.
            model_size: The input size of the model.
            max_output_size: Max number of boxes to be selected for each class.
            iou_threshold: Threshold for the IOU.
            confidence_threshold: Threshold for the confidence score.
            data_format: The input format.
        Returns:
            None.
        """
        if not data_format:
            if tf.test.is_built_with_cuda():
                data_format = 'channels_first'
            else:
                data_format = 'channels_last'

以后：

def __call__(self, inputs, training):
    """Add operations to detect boxes for a batch of input images.
    Args:
        inputs: A Tensor representing a batch of input images.
        training: A boolean, whether to use in training or inference mode.
    Returns:
        A list containing class-to-boxes dictionaries
            for each sample in the batch.
    """
    with tf.compat.v1.variable_scope('yolo_v3_model'):
        if self.data_format == 'channels_first':
            inputs = tf.transpose(inputs, [0, 3, 1, 2])

解决方案：

检查 tf.test.is_built_with_cuda() 按预期工作
如果不是-创建模型时手动设置顺序：

model = Yolo_v3(n_classes=n_classes, model_size=_MODEL_SIZE,
max_output_size=_MAX_OUTPUT_SIZE,
iou_threshold=iou_threshold,
confidence_threshold=confidence_threshold,
data_format = 'channels_last')

"The Conv2D op currently only supports the NHWC tensor format on the CPU" 错误尽管 NHWC 格式 (YOLO 3)

"The Conv2D op currently only supports the NHWC tensor format on the CPU" Error despite NHWC Format (YOLO 3)

keras

tensorflow

yolo

tensorflow2.0