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RK1808M0在宿主机上跑demoinit_runtime报错

yiye

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发表于 2023-1-12 15:32:55    查看: 3773|回复: 0 | [复制链接]    打印 | 只看该作者
使用PCIe1x接口将RK1808M0连接至电脑,网卡已经设置好,主动模式在计算卡上推理正常无报错。
以下这应该是被动模式,在宿主机中配置好环境后,运行demo,一直到导出模型那步都是正确的,在init_runtime时报错。在导出模型后,在demo中打印了一下list devices。报错内容如下,windows和ubuntu下都报这个错。


(rknn) D:\download\rknn-toolkit-master\examples\onnx\yolov5>python test.py
--> Config model
done
--> Loading model
W Call onnx.optimizer.optimize fail, skip optimize
W Please confirm that your onnx opset_version <= 11 (current opset_verison = 12)!!!
W:tensorflow:From D:\software\anaconda\envs\rknn\lib\site-packages\rknn\api\rknn.py:150: The name tf.ConfigProto is deprecated. Please use tf.compat.v1.ConfigProto instead.

W:tensorflow:From D:\software\anaconda\envs\rknn\lib\site-packages\rknn\api\rknn.py:150: The name tf.Session is deprecated. Please use tf.compat.v1.Session instead.

W:tensorflow:From D:\software\anaconda\envs\rknn\lib\site-packages\rknn\api\rknn.py:150: The name tf.placeholder is deprecated. Please use tf.compat.v1.placeholder instead.

done
--> Building model
W:tensorflow:From D:\software\anaconda\envs\rknn\lib\site-packages\rknn\api\rknn.py:278: The name tf.reset_default_graph is deprecated. Please use tf.compat.v1.reset_default_graph instead.

W:tensorflow:From D:\software\anaconda\envs\rknn\lib\site-packages\rknn\api\rknn.py:278: The name tf.FIFOQueue is deprecated. Please use tf.queue.FIFOQueue instead.

W:tensorflow:From D:\software\anaconda\envs\rknn\lib\site-packages\tensorflow\python\ops\control_flow_ops.py:1814: py_func (from tensorflow.python.ops.script_ops) is deprecated and will be removed in a future version.
Instructions for updating:
tf.py_func is deprecated in TF V2. Instead, there are two
    options available in V2.
    - tf.py_function takes a python function which manipulates tf eager
    tensors instead of numpy arrays. It's easy to convert a tf eager tensor to
    an ndarray (just call tensor.numpy()) but having access to eager tensors
    means `tf.py_function`s can use accelerators such as GPUs as well as
    being differentiable using a gradient tape.
    - tf.numpy_function maintains the semantics of the deprecated tf.py_func
    (it is not differentiable, and manipulates numpy arrays). It drops the
    stateful argument making all functions stateful.

W:tensorflow:From D:\software\anaconda\envs\rknn\lib\site-packages\rknn\api\rknn.py:278: The name tf.nn.max_pool is deprecated. Please use tf.nn.max_pool2d instead.

W:tensorflow:From D:\software\anaconda\envs\rknn\lib\site-packages\rknn\api\rknn.py:278: The name tf.image.resize_nearest_neighbor is deprecated. Please use tf.compat.v1.image.resize_nearest_neighbor instead.

done
--> Export RKNN model
done
*************************
all device(s) with ntb mode:
TM018084220800980
*************************
([], ['TM018084220800980'])
--> Init runtime environment
E RKNNAPI: rknn_init,  recv(MsgLoadAck) fail, -9 != 368!
E Catch exception when init runtime!
E Traceback (most recent call last):
E   File "rknn\api\rknn_base.py", line 897, in rknn.api.rknn_base.RKNNBase.init_runtime
E   File "rknn\api\rknn_runtime.py", line 341, in rknn.api.rknn_runtime.RKNNRuntime.build_graph
E Exception: RKNN init failed. error code: RKNN_ERR_DEVICE_UNAVAILABLE
E Please feedback the detailed log file <log_feedback_to_the_rknn_toolkit_dev_team.log> to the RKNN Toolkit development team.
E You can also check github issues: https://github.com/rockchip-linux/rknn-toolkit/issues
E Current device id is: None
E Devices connected:
E ['TM018084220800980']
Init runtime environment failed




有个问题,被动模式是只能用USB连接吗,我看Ubuntu端开启服务后会在init_runtime时报错一个"USB read faild"这种,所以猜测是不是被动模式只能用。。。。




求大佬解答!!
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