title: "The Conv2D op currently only supports the NHWC tensor format on the CPU" Error despite NHWC Format (YOLO 3)
body: <p>I am trying to get to run a bit of sample code from <a href="https://github.com/theAIGuysCode/yolo-v3" rel="nofollow noreferrer">github</a> 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 <a href="https://developer.nvidia.com/cuda-downloads" rel="nofollow noreferrer">here</a>.</p>
  <p>So the Code in question is this bit:</p>
  <pre><code>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.')
  </code></pre>
  <p>While executing this (also wondering why starting the detection.py doesnt use GPU in the first place), I  get the Error Message:</p>
  <pre><code>File &quot;C:\SDKs etc\Python 3.8\lib\site-packages\tensorflow\python\client\session.py&quot;, 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}}]]
  </code></pre>
  <p>Full Log see <a href="https://pastebin.com/A4NVhPqj" rel="nofollow noreferrer">here</a>.</p>
  <p>If I am understanding this correctly, the format of <code>inputs = tf.compat.v1.placeholder(tf.float32, [batch_size, *_MODEL_SIZE, 3])</code> 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.</p>