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SK-TDA4VM: 模型部署错误!!!

Part Number: SK-TDA4VM


你好,

      运行编译好的yolov5s时会出现如下错误

libtidl_onnxrt_EP loaded 0x23ebc470
Final number of subgraphs created are : 3, - Offloaded Nodes - 196, Total Nodes - 236
APP: Init ... !!!
MEM: Init ... !!!
MEM: Initialized DMA HEAP (fd=4) !!!
MEM: Init ... Done !!!
IPC: Init ... !!!
IPC: Init ... Done !!!
REMOTE_SERVICE: Init ... !!!
REMOTE_SERVICE: Init ... Done !!!
165.858162 s: GTC Frequency = 200 MHz
APP: Init ... Done !!!
165.858182 s: VX_ZONE_INIT:Enabled
165.858185 s: VX_ZONE_ERROR:Enabled
165.858187 s: VX_ZONE_WARNING:Enabled
165.858780 s: VX_ZONE_INIT:[tivxInitLocal:130] Initialization Done !!!
165.859005 s: VX_ZONE_INIT:[tivxHostInitLocal:86] Initialization Done for HOST !!!
165.875596 s: VX_ZONE_ERROR:[ownContextSendCmd:815] Command ack message returned failure cmd_status: -1
165.875603 s: VX_ZONE_ERROR:[ownContextSendCmd:851] tivxEventWait() failed.
165.875608 s: VX_ZONE_ERROR:[ownNodeKernelInit:538] Target kernel, TIVX_CMD_NODE_CREATE failed for node TIDLNode
165.875611 s: VX_ZONE_ERROR:[ownNodeKernelInit:539] Please be sure the target callbacks have been registered for this core
165.875614 s: VX_ZONE_ERROR:[ownNodeKernelInit:540] If the target callbacks have been registered, please ensure no errors are occurring within the create callback of this kernel
165.875618 s: VX_ZONE_ERROR:[ownGraphNodeKernelInit:583] kernel init for node 0, kernel com.ti.tidl ... failed !!!
165.875625 s: VX_ZONE_ERROR:[vxVerifyGraph:2055] Node kernel init failed
165.875627 s: VX_ZONE_ERROR:[vxVerifyGraph:2109] Graph verify failed
TIDL_RT_OVX: ERROR: Verifying TIDL graph ... Failed !!!
TIDL_RT_OVX: ERROR: Verify OpenVX graph failed
165.998258 s: VX_ZONE_ERROR:[ownContextSendCmd:815] Command ack message returned failure cmd_status: -1
165.998265 s: VX_ZONE_ERROR:[ownContextSendCmd:851] tivxEventWait() failed.
165.998268 s: VX_ZONE_ERROR:[ownNodeKernelInit:538] Target kernel, TIVX_CMD_NODE_CREATE failed for node TIDLNode
165.998272 s: VX_ZONE_ERROR:[ownNodeKernelInit:539] Please be sure the target callbacks have been registered for this core
165.998274 s: VX_ZONE_ERROR:[ownNodeKernelInit:540] If the target callbacks have been registered, please ensure no errors are occurring within the create callback of this kernel
165.998279 s: VX_ZONE_ERROR:[ownGraphNodeKernelInit:583] kernel init for node 0, kernel com.ti.tidl ... failed !!!
165.998284 s: VX_ZONE_ERROR:[vxVerifyGraph:2055] Node kernel init failed
165.998287 s: VX_ZONE_ERROR:[vxVerifyGraph:2109] Graph verify failed
TIDL_RT_OVX: ERROR: Verifying TIDL graph ... Failed !!!
TIDL_RT_OVX: ERROR: Verify OpenVX graph failed
166.019533 s: VX_ZONE_ERROR:[ownContextSendCmd:815] Command ack message returned failure cmd_status: -1
166.019540 s: VX_ZONE_ERROR:[ownContextSendCmd:851] tivxEventWait() failed.
166.019544 s: VX_ZONE_ERROR:[ownNodeKernelInit:538] Target kernel, TIVX_CMD_NODE_CREATE failed for node TIDLNode
166.019546 s: VX_ZONE_ERROR:[ownNodeKernelInit:539] Please be sure the target callbacks have been registered for this core
166.019549 s: VX_ZONE_ERROR:[ownNodeKernelInit:540] If the target callbacks have been registered, please ensure no errors are occurring within the create callback of this kernel
166.019552 s: VX_ZONE_ERROR:[ownGraphNodeKernelInit:583] kernel init for node 0, kernel com.ti.tidl ... failed !!!
166.019557 s: VX_ZONE_ERROR:[vxVerifyGraph:2055] Node kernel init failed
166.019559 s: VX_ZONE_ERROR:[vxVerifyGraph:2109] Graph verify failed
TIDL_RT_OVX: ERROR: Verifying TIDL graph ... Failed !!!
TIDL_RT_OVX: ERROR: Verify OpenVX graph failed

请问是哪里出问题了?

  • 请看以下答复:

    能否确认您的电路板具有与网络编译期间使用的 SDK 版本相同的版本?

    请分享下网络编译日志。 

  • libtidl_onnxrt_EP loaded 0x2d3cc470 
    Final number of subgraphs created are : 3, - Offloaded Nodes - 196, Total Nodes - 236 
    APP: Init ... !!!
    MEM: Init ... !!!
    MEM: Initialized DMA HEAP (fd=4) !!!
    MEM: Init ... Done !!!
    IPC: Init ... !!!
    IPC: Init ... Done !!!
    REMOTE_SERVICE: Init ... !!!
    REMOTE_SERVICE: Init ... Done !!!
       305.600825 s: GTC Frequency = 200 MHz
    APP: Init ... Done !!!
       305.600852 s:  VX_ZONE_INIT:Enabled
       305.600855 s:  VX_ZONE_ERROR:Enabled
       305.600857 s:  VX_ZONE_WARNING:Enabled
       305.601366 s:  VX_ZONE_INIT:[tivxInitLocal:130] Initialization Done !!!
       305.601658 s:  VX_ZONE_INIT:[tivxHostInitLocal:86] Initialization Done for HOST !!!
       305.618095 s:  VX_ZONE_ERROR:[ownContextSendCmd:815] Command ack message returned failure cmd_status: -1
       305.618103 s:  VX_ZONE_ERROR:[ownContextSendCmd:851] tivxEventWait() failed.
       305.618108 s:  VX_ZONE_ERROR:[ownNodeKernelInit:538] Target kernel, TIVX_CMD_NODE_CREATE failed for node TIDLNode
       305.618110 s:  VX_ZONE_ERROR:[ownNodeKernelInit:539] Please be sure the target callbacks have been registered for this core
       305.618113 s:  VX_ZONE_ERROR:[ownNodeKernelInit:540] If the target callbacks have been registered, please ensure no errors are occurring within the create callback of this kernel
       305.618117 s:  VX_ZONE_ERROR:[ownGraphNodeKernelInit:583] kernel init for node 0, kernel com.ti.tidl ... failed !!!
       305.618123 s:  VX_ZONE_ERROR:[vxVerifyGraph:2055] Node kernel init failed
       305.618126 s:  VX_ZONE_ERROR:[vxVerifyGraph:2109] Graph verify failed
    TIDL_RT_OVX: ERROR: Verifying TIDL graph ... Failed !!!
    TIDL_RT_OVX: ERROR: Verify OpenVX graph failed
       305.740672 s:  VX_ZONE_ERROR:[ownContextSendCmd:815] Command ack message returned failure cmd_status: -1
       305.740679 s:  VX_ZONE_ERROR:[ownContextSendCmd:851] tivxEventWait() failed.
       305.740683 s:  VX_ZONE_ERROR:[ownNodeKernelInit:538] Target kernel, TIVX_CMD_NODE_CREATE failed for node TIDLNode
       305.740686 s:  VX_ZONE_ERROR:[ownNodeKernelInit:539] Please be sure the target callbacks have been registered for this core
       305.740689 s:  VX_ZONE_ERROR:[ownNodeKernelInit:540] If the target callbacks have been registered, please ensure no errors are occurring within the create callback of this kernel
       305.740693 s:  VX_ZONE_ERROR:[ownGraphNodeKernelInit:583] kernel init for node 0, kernel com.ti.tidl ... failed !!!
       305.740698 s:  VX_ZONE_ERROR:[vxVerifyGraph:2055] Node kernel init failed
       305.740701 s:  VX_ZONE_ERROR:[vxVerifyGraph:2109] Graph verify failed
    TIDL_RT_OVX: ERROR: Verifying TIDL graph ... Failed !!!
    TIDL_RT_OVX: ERROR: Verify OpenVX graph failed
       305.761984 s:  VX_ZONE_ERROR:[ownContextSendCmd:815] Command ack message returned failure cmd_status: -1
       305.761991 s:  VX_ZONE_ERROR:[ownContextSendCmd:851] tivxEventWait() failed.
       305.761994 s:  VX_ZONE_ERROR:[ownNodeKernelInit:538] Target kernel, TIVX_CMD_NODE_CREATE failed for node TIDLNode
       305.761997 s:  VX_ZONE_ERROR:[ownNodeKernelInit:539] Please be sure the target callbacks have been registered for this core
       305.762000 s:  VX_ZONE_ERROR:[ownNodeKernelInit:540] If the target callbacks have been registered, please ensure no errors are occurring within the create callback of this kernel
       305.762004 s:  VX_ZONE_ERROR:[ownGraphNodeKernelInit:583] kernel init for node 0, kernel com.ti.tidl ... failed !!!
       305.762009 s:  VX_ZONE_ERROR:[vxVerifyGraph:2055] Node kernel init failed
       305.762012 s:  VX_ZONE_ERROR:[vxVerifyGraph:2109] Graph verify failed
    TIDL_RT_OVX: ERROR: Verifying TIDL graph ... Failed !!!
    TIDL_RT_OVX: ERROR: Verify OpenVX graph failed
    )0[?7h
     +--------------------------------------------------------------------------+
     | Lane Detection|
     +--------------------------------------------------------------------------+
     +--------------------------------------------------------------------------+
     | Input Src: /opt/edge_ai_apps/data/videos/video_0000_h264.mp4|
     | Model Name: yolov5s|
     | Model Type: detection|
     +--------------------------------------------------------------------------+
     +--------------------------------------------------------------------------+   306.161757 s:  VX_ZONE_ERROR:[ownContextSendCmd:815] Command ack message returned failure cmd_status: -1
       306.161775 s:  VX_ZONE_ERROR:[ownContextSendCmd:851] tivxEventWait() failed.
       306.161783 s:  VX_ZONE_ERROR:[ownNodeKernelInit:538] Target kernel, TIVX_CMD_NODE_CREATE failed for node TIDLNode
       306.161788 s:  VX_ZONE_ERROR:[ownNodeKernelInit:539] Please be sure the target callbacks have been registered for this core
       306.161793 s:  VX_ZONE_ERROR:[ownNodeKernelInit:540] If the target callbacks have been registered, please ensure no errors are occurring within the create callback of this kernel
       306.161804 s:  VX_ZONE_ERROR:[ownGraphNodeKernelInit:583] kernel init for node 0, kernel com.ti.tidl ... failed !!!
       306.161817 s:  VX_ZONE_ERROR:[vxVerifyGraph:2055] Node kernel init failed
       306.161822 s:  VX_ZONE_ERROR:[vxVerifyGraph:2109] Graph verify failed
       306.162070 s:  VX_ZONE_ERROR:[ownGraphScheduleGraphWrapper:820] graph is not in a state required to be scheduled
       306.162075 s:  VX_ZONE_ERROR:[vxProcessGraph:755] schedule graph failed
       306.162079 s:  VX_ZONE_ERROR:[vxProcessGraph:760] wait graph failed
    ERROR: Running TIDL graph ... Failed !!!
       306.177924 s:  VX_ZONE_ERROR:[ownContextSendCmd:815] Command ack message returned failure cmd_status: -1
       306.177931 s:  VX_ZONE_ERROR:[ownContextSendCmd:851] tivxEventWait() failed.
       306.177935 s:  VX_ZONE_ERROR:[ownNodeKernelInit:538] Target kernel, TIVX_CMD_NODE_CREATE failed for node TIDLNode
       306.177938 s:  VX_ZONE_ERROR:[ownNodeKernelInit:539] Please be sure the target callbacks have been registered for this core
       306.177940 s:  VX_ZONE_ERROR:[ownNodeKernelInit:540] If the target callbacks have been registered, please ensure no errors are occurring within the create callback of this kernel
       306.177945 s:  VX_ZONE_ERROR:[ownGraphNodeKernelInit:583] kernel init for node 0, kernel com.ti.tidl ... failed !!!
       306.177951 s:  VX_ZONE_ERROR:[vxVerifyGraph:2055] Node kernel init failed
       306.177953 s:  VX_ZONE_ERROR:[vxVerifyGraph:2109] Graph verify failed
       306.178068 s:  VX_ZONE_ERROR:[ownGraphScheduleGraphWrapper:820] graph is not in a state required to be scheduled
       306.178074 s:  VX_ZONE_ERROR:[vxProcessGraph:755] schedule graph failed
       306.178084 s:  VX_ZONE_ERROR:[vxProcessGraph:760] wait graph failed
    ERROR: Running TIDL graph ... Failed !!!
       306.220401 s:  VX_ZONE_ERROR:[ownContextSendCmd:815] Command ack message returned failure cmd_status: -1
       306.220408 s:  VX_ZONE_ERROR:[ownContextSendCmd:851] tivxEventWait() failed.
       306.220411 s:  VX_ZONE_ERROR:[ownNodeKernelInit:538] Target kernel, TIVX_CMD_NODE_CREATE failed for node TIDLNode
       306.220415 s:  VX_ZONE_ERROR:[ownNodeKernelInit:539] Please be sure the target callbacks have been registered for this core
       306.220417 s:  VX_ZONE_ERROR:[ownNodeKernelInit:540] If the target callbacks have been registered, please ensure no errors are occurring within the create callback of this kernel
       306.220421 s:  VX_ZONE_ERROR:[ownGraphNodeKernelInit:583] kernel init for node 0, kernel com.ti.tidl ... failed !!!
       306.220427 s:  VX_ZONE_ERROR:[vxVerifyGraph:2055] Node kernel init failed
       306.220430 s:  VX_ZONE_ERROR:[vxVerifyGraph:2109] Graph verify failed
       306.220539 s:  VX_ZONE_ERROR:[ownGraphScheduleGraphWrapper:820] graph is not in a state required to be scheduled
       306.220542 s:  VX_ZONE_ERROR:[vxProcessGraph:755] schedule graph failed
       306.220544 s:  VX_ZONE_ERROR:[vxProcessGraph:760] wait graph failed
    ERROR: Running TIDL graph ... Failed !!!
    
     +--------------------------------------------------------------------------+
     | Lane Detection|
     +--------------------------------------------------------------------------+
     +--------------------------------------------------------------------------+
     | Input Src: /opt/edge_ai_apps/data/videos/video_0000_h264.mp4|
     | Model Name: yolov5s|
     | Model Type: detection|
     +--------------------------------------------------------------------------+
     | dl-inference:       181.26 ms   from   1    samples |
     +--------------------------------------------------------------------------+
     +--------------------------------------------------------------------------+
     | Lane Detection|
     +--------------------------------------------------------------------------+
     +--------------------------------------------------------------------------+
     | Input Src: /opt/edge_ai_apps/data/videos/video_0000_h264.mp4|
     | Model Name: yolov5s|
     | Model Type: detection|
     +--------------------------------------------------------------------------+
     | dl-inference:       181.26 ms   from   1    samples |
     +--------------------------------------------------------------------------+
     +--------------------------------------------------------------------------+
     | Lane Detection|
     +--------------------------------------------------------------------------+
     +--------------------------------------------------------------------------+
     | Input Src: /opt/edge_ai_apps/data/videos/video_0000_h264.mp4|
     | Model Name: yolov5s|
     | Model Type: detection|
     +--------------------------------------------------------------------------+
     | dl-inference:       181.26 ms   from   1    samples |
     +--------------------------------------------------------------------------+
     +--------------------------------------------------------------------------+
     | Lane Detection|
     +--------------------------------------------------------------------------+
     +--------------------------------------------------------------------------+
     | Input Src: /opt/edge_ai_apps/data/videos/video_0000_h264.mp4|
     | Model Name: yolov5s|
     | Model Type: detection|
     +--------------------------------------------------------------------------+
     | dl-inference:       181.26 ms   from   1    samples |
     +--------------------------------------------------------------------------+
     +--------------------------------------------------------------------------+
     | Lane Detection|
     +--------------------------------------------------------------------------+
     +--------------------------------------------------------------------------+
     | Input Src: /opt/edge_ai_apps/data/videos/video_0000_h264.mp4|
     | Model Name: yolov5s|
     | Model Type: detection|
     +--------------------------------------------------------------------------+
     | dl-inference:       181.26 ms   from   1    samples |
     +--------------------------------------------------------------------------+
     +--------------------------------------------------------------------------+
     | Lane Detection|
     +--------------------------------------------------------------------------+
     +--------------------------------------------------------------------------+
     | Input Src: /opt/edge_ai_apps/data/videos/video_0000_h264.mp4|
     | Model Name: yolov5s|
     | Model Type: detection|
     +--------------------------------------------------------------------------+
     | dl-inference:       181.26 ms   from   1    samples |
     +--------------------------------------------------------------------------+
     +--------------------------------------------------------------------------+
     | Lane Detection|
     +--------------------------------------------------------------------------+
     +--------------------------------------------------------------------------+
     | Input Src: /opt/edge_ai_apps/data/videos/video_0000_h264.mp4|
     | Model Name: yolov5s|
     | Model Type: detection|
     +--------------------------------------------------------------------------+
     | dl-inference:       181.26 ms   from   1    samples |
     +--------------------------------------------------------------------------+
     +--------------------------------------------------------------------------+
     | Lane Detection|
     +--------------------------------------------------------------------------+
     +--------------------------------------------------------------------------+
     | Input Src: /opt/edge_ai_apps/data/videos/video_0000_h264.mp4|
     | Model Name: yolov5s|
     | Model Type: detection|
     +--------------------------------------------------------------------------+
     | dl-inference:       181.26 ms   from   1    samples |
     +--------------------------------------------------------------------------+
     +--------------------------------------------------------------------------+
     | Lane Detection|
     +--------------------------------------------------------------------------+
     +--------------------------------------------------------------------------+
     | Input Src: /opt/edge_ai_apps/data/videos/video_0000_h264.mp4|
     | Model Name: yolov5s|
     | Model Type: detection|
     +--------------------------------------------------------------------------+
     | dl-inference:       181.26 ms   from   1    samples |
     +--------------------------------------------------------------------------+
     +--------------------------------------------------------------------------+
     | Lane Detection|
     +--------------------------------------------------------------------------+
     +--------------------------------------------------------------------------+
     | Input Src: /opt/edge_ai_apps/data/videos/video_0000_h264.mp4|
     | Model Name: yolov5s|
     | Model Type: detection|
     +--------------------------------------------------------------------------+
     | dl-inference:       181.26 ms   from   1    samples |
     +--------------------------------------------------------------------------+
     +--------------------------------------------------------------------------+
     | Lane Detection|
     +--------------------------------------------------------------------------+
     +--------------------------------------------------------------------------+
     | Input Src: /opt/edge_ai_apps/data/videos/video_0000_h264.mp4|
     | Model Name: yolov5s|
     | Model Type: detection|
     +--------------------------------------------------------------------------+
     | dl-inference:       181.26 ms   from   1    samples |
     +--------------------------------------------------------------------------+
     +--------------------------------------------------------------------------+
     | Lane Detection|
     +--------------------------------------------------------------------------+
     +--------------------------------------------------------------------------+
     | Input Src: /opt/edge_ai_apps/data/videos/video_0000_h264.mp4|
     | Model Name: yolov5s|
     | Model Type: detection|
     +--------------------------------------------------------------------------+
     | dl-inference:       181.26 ms   from   1    samples |
     +--------------------------------------------------------------------------+
     +--------------------------------------------------------------------------+
     | Lane Detection|
     +--------------------------------------------------------------------------+
     +--------------------------------------------------------------------------+
     | Input Src: /opt/edge_ai_apps/data/videos/video_0000_h264.mp4|
     | Model Name: yolov5s|
     | Model Type: detection|
     +--------------------------------------------------------------------------+
     | dl-inference:       181.26 ms   from   1    samples |
     +--------------------------------------------------------------------------+
     +--------------------------------------------------------------------------+
     | Lane Detection|
     +--------------------------------------------------------------------------+
     +--------------------------------------------------------------------------+
     | Input Src: /opt/edge_ai_apps/data/videos/video_0000_h264.mp4|
     | Model Name: yolov5s|
     | Model Type: detection|
     +--------------------------------------------------------------------------+
     | dl-inference:       181.26 ms   from   1    samples |
     +--------------------------------------------------------------------------+
     +--------------------------------------------------------------------------+
     | Lane Detection|
     +--------------------------------------------------------------------------+
     +--------------------------------------------------------------------------+
     | Input Src: /opt/edge_ai_apps/data/videos/video_0000_h264.mp4|
     | Model Name: yolov5s|
     | Model Type: detection|
     +--------------------------------------------------------------------------+
     | dl-inference:       181.26 ms   from   1    samples |
     +--------------------------------------------------------------------------+
     +--------------------------------------------------------------------------+
     | Lane Detection|
     +--------------------------------------------------------------------------+
     +--------------------------------------------------------------------------+
     | Input Src: /opt/edge_ai_apps/data/videos/video_0000_h264.mp4|
     | Model Name: yolov5s|
     | Model Type: detection|
     +--------------------------------------------------------------------------+
     | dl-inference:       181.26 ms   from   1    samples |
     +--------------------------------------------------------------------------+
     +--------------------------------------------------------------------------+
     | Lane Detection|
     +--------------------------------------------------------------------------+
     +--------------------------------------------------------------------------+
     | Input Src: /opt/edge_ai_apps/data/videos/video_0000_h264.mp4|
     | Model Name: yolov5s|
     | Model Type: detection|
     +--------------------------------------------------------------------------+
     | dl-inference:       181.26 ms   from   1    samples |
     +--------------------------------------------------------------------------+
     +--------------------------------------------------------------------------+
     | Lane Detection|
     +--------------------------------------------------------------------------+
     +--------------------------------------------------------------------------+
     | Input Src: /opt/edge_ai_apps/data/videos/video_0000_h264.mp4|
     | Model Name: yolov5s|
     | Model Type: detection|
     +--------------------------------------------------------------------------+
     | dl-inference:       181.26 ms   from   1    samples |
     +--------------------------------------------------------------------------+
     +--------------------------------------------------------------------------+
     | Lane Detection|
     +--------------------------------------------------------------------------+
     +--------------------------------------------------------------------------+
     | Input Src: /opt/edge_ai_apps/data/videos/video_0000_h264.mp4|
     | Model Name: yolov5s|
     | Model Type: detection|
     +--------------------------------------------------------------------------+
     | dl-inference:       181.26 ms   from   1    samples |
     +--------------------------------------------------------------------------+
     +--------------------------------------------------------------------------+
     | Lane Detection|
     +--------------------------------------------------------------------------+
     +--------------------------------------------------------------------------+
     | Input Src: /opt/edge_ai_apps/data/videos/video_0000_h264.mp4|
     | Model Name: yolov5s|
     | Model Type: detection|
     +--------------------------------------------------------------------------+
     | dl-inference:       181.26 ms   from   1    samples |
     +--------------------------------------------------------------------------+
     +--------------------------------------------------------------------------+
     | Lane Detection|
     +--------------------------------------------------------------------------+
     +--------------------------------------------------------------------------+
     | Input Src: /opt/edge_ai_apps/data/videos/video_0000_h264.mp4|
     | Model Name: yolov5s|
     | Model Type: detection|
     +--------------------------------------------------------------------------+
     | dl-inference:       181.26 ms   from   1    samples |
     +--------------------------------------------------------------------------+
     +--------------------------------------------------------------------------+
     | Lane Detection|
     +--------------------------------------------------------------------------+
     +--------------------------------------------------------------------------+
     | Input Src: /opt/edge_ai_apps/data/videos/video_0000_h264.mp4|
     | Model Name: yolov5s|
     | Model Type: detection|
     +--------------------------------------------------------------------------+
     | dl-inference:       181.26 ms   from   1    samples |
     +--------------------------------------------------------------------------+
     +--------------------------------------------------------------------------+
     | Lane Detection|
     +--------------------------------------------------------------------------+
     +--------------------------------------------------------------------------+
     | Input Src: /opt/edge_ai_apps/data/videos/video_0000_h264.mp4|
     | Model Name: yolov5s|
     | Model Type: detection|
     +--------------------------------------------------------------------------+
     | dl-inference:       181.26 ms   from   1    samples |
     +--------------------------------------------------------------------------+
     +--------------------------------------------------------------------------+
     | Lane Detection|
     +--------------------------------------------------------------------------+
     +--------------------------------------------------------------------------+
     | Input Src: /opt/edge_ai_apps/data/videos/video_0000_h264.mp4|
     | Model Name: yolov5s|
     | Model Type: detection|
     +--------------------------------------------------------------------------+
     | dl-inference:       181.26 ms   from   1    samples |
     +--------------------------------------------------------------------------+
     +--------------------------------------------------------------------------+
     | Lane Detection|
     +--------------------------------------------------------------------------+
     +--------------------------------------------------------------------------+
     | Input Src: /opt/edge_ai_apps/data/videos/video_0000_h264.mp4|
     | Model Name: yolov5s|
     | Model Type: detection|
     +--------------------------------------------------------------------------+
     | dl-inference:       181.26 ms   from   1    samples |
     +--------------------------------------------------------------------------+
     +--------------------------------------------------------------------------+
     | Lane Detection|
     +--------------------------------------------------------------------------+
     +--------------------------------------------------------------------------+
     | Input Src: /opt/edge_ai_apps/data/videos/video_0000_h264.mp4|
     | Model Name: yolov5s|
     | Model Type: detection|
     +--------------------------------------------------------------------------+
     | dl-inference:       181.26 ms   from   1    samples |
     +--------------------------------------------------------------------------+
     +--------------------------------------------------------------------------+
     | Lane Detection|
     +--------------------------------------------------------------------------+
     +--------------------------------------------------------------------------+
     | Input Src: /opt/edge_ai_apps/data/videos/video_0000_h264.mp4|
     | Model Name: yolov5s|
     | Model Type: detection|
     +--------------------------------------------------------------------------+
     | dl-inference:       181.26 ms   from   1    samples |
     +--------------------------------------------------------------------------+
     +--------------------------------------------------------------------------+
     | Lane Detection|
     +--------------------------------------------------------------------------+
     +--------------------------------------------------------------------------+
     | Input Src: /opt/edge_ai_apps/data/videos/video_0000_h264.mp4|
     | Model Name: yolov5s|
     | Model Type: detection|
     +--------------------------------------------------------------------------+
     | dl-inference:       181.26 ms   from   1    samples |
     +--------------------------------------------------------------------------+
     +--------------------------------------------------------------------------+
     | Lane Detection|
     +--------------------------------------------------------------------------+
     +--------------------------------------------------------------------------+
     | Input Src: /opt/edge_ai_apps/data/videos/video_0000_h264.mp4|
     | Model Name: yolov5s|
     | Model Type: detection|
     +--------------------------------------------------------------------------+
     | dl-inference:       181.26 ms   from   1    samples |
     +--------------------------------------------------------------------------+
     +--------------------------------------------------------------------------+
     | Lane Detection|
     +--------------------------------------------------------------------------+
     +--------------------------------------------------------------------------+
     | Input Src: /opt/edge_ai_apps/data/videos/video_0000_h264.mp4|
     | Model Name: yolov5s|
     | Model Type: detection|
     +--------------------------------------------------------------------------+
     | dl-inference:       181.26 ms   from   1    samples |
     +--------------------------------------------------------------------------+
     +--------------------------------------------------------------------------+
     | Lane Detection|
     +--------------------------------------------------------------------------+
     +--------------------------------------------------------------------------+
     | Input Src: /opt/edge_ai_apps/data/videos/video_0000_h264.mp4|
     | Model Name: yolov5s|
     | Model Type: detection|
     +--------------------------------------------------------------------------+
     | dl-inference:       181.26 ms   from   1    samples |
     +--------------------------------------------------------------------------+
     +--------------------------------------------------------------------------+
     | Lane Detection|
     +--------------------------------------------------------------------------+
     +--------------------------------------------------------------------------+
     | Input Src: /opt/edge_ai_apps/data/videos/video_0000_h264.mp4|
     | Model Name: yolov5s|
     | Model Type: detection|
     +--------------------------------------------------------------------------+
     | dl-inference:       181.26 ms   from   1    samples |
     +--------------------------------------------------------------------------+
     +--------------------------------------------------------------------------+
     | Lane Detection|
     +--------------------------------------------------------------------------+
     +--------------------------------------------------------------------------+
     | Input Src: /opt/edge_ai_apps/data/videos/video_0000_h264.mp4|
     | Model Name: yolov5s|
     | Model Type: detection|
     +--------------------------------------------------------------------------+
     | dl-inference:       181.26 ms   from   1    samples |
     +--------------------------------------------------------------------------+
     +--------------------------------------------------------------------------+
     | Lane Detection|
     +--------------------------------------------------------------------------+
     +--------------------------------------------------------------------------+
     | Input Src: /opt/edge_ai_apps/data/videos/video_0000_h264.mp4|
     | Model Name: yolov5s|
     | Model Type: detection|
     +--------------------------------------------------------------------------+
     | dl-inference:       181.26 ms   from   1    samples |
     +--------------------------------------------------------------------------+
     +--------------------------------------------------------------------------+
     | Lane Detection|
     +--------------------------------------------------------------------------+
     +--------------------------------------------------------------------------+
     | Input Src: /opt/edge_ai_apps/data/videos/video_0000_h264.mp4|
     | Model Name: yolov5s|
     | Model Type: detection|
     +--------------------------------------------------------------------------+
     | dl-inference:       181.26 ms   from   1    samples |
     +--------------------------------------------------------------------------+
     +--------------------------------------------------------------------------+
     | Lane Detection|
     +--------------------------------------------------------------------------+
     +--------------------------------------------------------------------------+
     | Input Src: /opt/edge_ai_apps/data/videos/video_0000_h264.mp4|
     | Model Name: yolov5s|
     | Model Type: detection|
     +--------------------------------------------------------------------------+
     | dl-inference:       181.26 ms   from   1    samples |
     +--------------------------------------------------------------------------+
     +--------------------------------------------------------------------------+
     | Lane Detection|
     +--------------------------------------------------------------------------+
     +--------------------------------------------------------------------------+
     | Input Src: /opt/edge_ai_apps/data/videos/video_0000_h264.mp4|
     | Model Name: yolov5s|
     | Model Type: detection|
     +--------------------------------------------------------------------------+
     | dl-inference:       181.26 ms   from   1    samples |
     +--------------------------------------------------------------------------+
     +--------------------------------------------------------------------------+
     | Lane Detection|
     +--------------------------------------------------------------------------+
     +--------------------------------------------------------------------------+
     | Input Src: /opt/edge_ai_apps/data/videos/video_0000_h264.mp4|
     | Model Name: yolov5s|
     | Model Type: detection|
     +--------------------------------------------------------------------------+
     | dl-inference:       181.26 ms   from   1    samples |
     +--------------------------------------------------------------------------+
     +--------------------------------------------------------------------------+
     | Lane Detection|
     +--------------------------------------------------------------------------+
     +--------------------------------------------------------------------------+
     | Input Src: /opt/edge_ai_apps/data/videos/video_0000_h264.mp4|
     | Model Name: yolov5s|
     | Model Type: detection|
     +--------------------------------------------------------------------------+
     | dl-inference:       181.26 ms   from   1    samples |
     +--------------------------------------------------------------------------+
     +--------------------------------------------------------------------------+
     | Lane Detection|
     +--------------------------------------------------------------------------+
     +--------------------------------------------------------------------------+
     | Input Src: /opt/edge_ai_apps/data/videos/video_0000_h264.mp4|
     | Model Name: yolov5s|
     | Model Type: detection|
     +--------------------------------------------------------------------------+
     | dl-inference:       181.26 ms   from   1    samples |
     +--------------------------------------------------------------------------+
     +--------------------------------------------------------------------------+
     | Lane Detection|
     +--------------------------------------------------------------------------+
     +--------------------------------------------------------------------------+
     | Input Src: /opt/edge_ai_apps/data/videos/video_0000_h264.mp4|
     | Model Name: yolov5s|
     | Model Type: detection|
     +--------------------------------------------------------------------------+
     | dl-inference:       181.26 ms   from   1    samples |
     +--------------------------------------------------------------------------+
     +--------------------------------------------------------------------------+
     | Lane Detection|
     +--------------------------------------------------------------------------+
     +--------------------------------------------------------------------------+
     | Input Src: /opt/edge_ai_apps/data/videos/video_0000_h264.mp4|
     | Model Name: yolov5s|
     | Model Type: detection|
     +--------------------------------------------------------------------------+
     | dl-inference:       181.26 ms   from   1    samples |
     +--------------------------------------------------------------------------+
     +--------------------------------------------------------------------------+
     | Lane Detection|
     +--------------------------------------------------------------------------+
     +--------------------------------------------------------------------------+
     | Input Src: /opt/edge_ai_apps/data/videos/video_0000_h264.mp4|
     | Model Name: yolov5s|
     | Model Type: detection|
     +--------------------------------------------------------------------------+
     | dl-inference:       181.26 ms   from   1    samples |
     +--------------------------------------------------------------------------+
     +--------------------------------------------------------------------------+
     | Lane Detection|
     +--------------------------------------------------------------------------+
     +--------------------------------------------------------------------------+
     | Input Src: /opt/edge_ai_apps/data/videos/video_0000_h264.mp4|
     | Model Name: yolov5s|
     | Model Type: detection|
     +--------------------------------------------------------------------------+
     | dl-inference:       181.26 ms   from   1    samples |
     +--------------------------------------------------------------------------+
     +--------------------------------------------------------------------------+
     | Lane Detection|
     +--------------------------------------------------------------------------+
     +--------------------------------------------------------------------------+
     | Input Src: /opt/edge_ai_apps/data/videos/video_0000_h264.mp4|
     | Model Name: yolov5s|
     | Model Type: detection|
     +--------------------------------------------------------------------------+
     | dl-inference:       181.26 ms   from   1    samples |
     +--------------------------------------------------------------------------+
     +--------------------------------------------------------------------------+
     | Lane Detection|
     +--------------------------------------------------------------------------+
     +--------------------------------------------------------------------------+
     | Input Src: /opt/edge_ai_apps/data/videos/video_0000_h264.mp4|
     | Model Name: yolov5s|
     | Model Type: detection|
     +--------------------------------------------------------------------------+
     | dl-inference:       181.26 ms   from   1    samples |
     +--------------------------------------------------------------------------+
     +--------------------------------------------------------------------------+
     | Lane Detection|
     +--------------------------------------------------------------------------+
     +--------------------------------------------------------------------------+
     | Input Src: /opt/edge_ai_apps/data/videos/video_0000_h264.mp4|
     | Model Name: yolov5s|
     | Model Type: detection|
     +--------------------------------------------------------------------------+
     | dl-inference:       181.26 ms   from   1    samples |
     +--------------------------------------------------------------------------+
     +--------------------------------------------------------------------------+
     | Lane Detection|
     +--------------------------------------------------------------------------+
     +--------------------------------------------------------------------------+
     | Input Src: /opt/edge_ai_apps/data/videos/video_0000_h264.mp4|
     | Model Name: yolov5s|
     | Model Type: detection|
     +--------------------------------------------------------------------------+
     | dl-inference:       181.26 ms   from   1    samples |
     +--------------------------------------------------------------------------+
     +--------------------------------------------------------------------------+
     | Lane Detection|
     +--------------------------------------------------------------------------+
     +--------------------------------------------------------------------------+
     | Input Src: /opt/edge_ai_apps/data/videos/video_0000_h264.mp4|
     | Model Name: yolov5s|
     | Model Type: detection|
     +--------------------------------------------------------------------------+
     | dl-inference:       181.26 ms   from   1    samples |
     +--------------------------------------------------------------------------+
     +--------------------------------------------------------------------------+
     | Lane Detection|
     +--------------------------------------------------------------------------+
     +--------------------------------------------------------------------------+
     | Input Src: /opt/edge_ai_apps/data/videos/video_0000_h264.mp4|
     | Model Name: yolov5s|
     | Model Type: detection|
     +--------------------------------------------------------------------------+
     | dl-inference:       181.26 ms   from   1    samples |
     +--------------------------------------------------------------------------+
     +--------------------------------------------------------------------------+
     | Lane Detection|
     +--------------------------------------------------------------------------+
     +--------------------------------------------------------------------------+
     | Input Src: /opt/edge_ai_apps/data/videos/video_0000_h264.mp4|
     | Model Name: yolov5s|
     | Model Type: detection|
     +--------------------------------------------------------------------------+
     | dl-inference:       181.26 ms   from   1    samples |
     +--------------------------------------------------------------------------+
     +--------------------------------------------------------------------------+
     | Lane Detection|
     +--------------------------------------------------------------------------+
     +--------------------------------------------------------------------------+
     | Input Src: /opt/edge_ai_apps/data/videos/video_0000_h264.mp4|
     | Model Name: yolov5s|
     | Model Type: detection|
     +--------------------------------------------------------------------------+
     | dl-inference:       181.26 ms   from   1    samples |
     +--------------------------------------------------------------------------+
     +--------------------------------------------------------------------------+
     | Lane Detection|
     +--------------------------------------------------------------------------+
     +--------------------------------------------------------------------------+
     | Input Src: /opt/edge_ai_apps/data/videos/video_0000_h264.mp4|
     | Model Name: yolov5s|
     | Model Type: detection|
     +--------------------------------------------------------------------------+
     | dl-inference:       181.26 ms   from   1    samples |
     +--------------------------------------------------------------------------+
     +--------------------------------------------------------------------------+
     | Lane Detection|
     +--------------------------------------------------------------------------+
     +--------------------------------------------------------------------------+
     | Input Src: /opt/edge_ai_apps/data/videos/video_0000_h264.mp4|
     | Model Name: yolov5s|
     | Model Type: detection|
     +--------------------------------------------------------------------------+
     | dl-inference:       181.26 ms   from   1    samples |
     +--------------------------------------------------------------------------+
     +--------------------------------------------------------------------------+
     | Lane Detection|
     +--------------------------------------------------------------------------+
     +--------------------------------------------------------------------------+
     | Input Src: /opt/edge_ai_apps/data/videos/video_0000_h264.mp4|
     | Model Name: yolov5s|
     | Model Type: detection|
     +--------------------------------------------------------------------------+
     | dl-inference:       181.26 ms   from   1    samples |
     +--------------------------------------------------------------------------+
     +--------------------------------------------------------------------------+
     | Lane Detection|
     +--------------------------------------------------------------------------+
     +--------------------------------------------------------------------------+
     | Input Src: /opt/edge_ai_apps/data/videos/video_0000_h264.mp4|
     | Model Name: yolov5s|
     | Model Type: detection|
     +--------------------------------------------------------------------------+
     | dl-inference:       181.26 ms   from   1    samples |
     +--------------------------------------------------------------------------+
     +--------------------------------------------------------------------------+
     | Lane Detection|
     +--------------------------------------------------------------------------+
     +--------------------------------------------------------------------------+
     | Input Src: /opt/edge_ai_apps/data/videos/video_0000_h264.mp4|
     | Model Name: yolov5s|
     | Model Type: detection|
     +--------------------------------------------------------------------------+
     | dl-inference:       181.26 ms   from   1    samples |
     +--------------------------------------------------------------------------+
     +--------------------------------------------------------------------------+
     | Lane Detection|
     +--------------------------------------------------------------------------+
     +--------------------------------------------------------------------------+
     | Input Src: /opt/edge_ai_apps/data/videos/video_0000_h264.mp4|
     | Model Name: yolov5s|
     | Model Type: detection|
     +--------------------------------------------------------------------------+
     | dl-inference:       181.26 ms   from   1    samples |
     +--------------------------------------------------------------------------+
    这是运行后生成的log文件

  • Available execution providers :  ['TIDLExecutionProvider', 'TIDLCompilationProvider', 'CPUExecutionProvider']
    
    Running 1 Models - ['besta']
    
    
    Running_Model :  besta  
    
    
    Running shape inference on model ../../../models/public/yolov5s.onnx 
    
    
    Preliminary subgraphs created = 5 
    Final number of subgraphs created are : 3, - Offloaded Nodes - 196, Total Nodes - 236 
    /home/leo/code/edgeai-tidl-tools-master/examples/osrt_python/ort/tidl_tools/tidl_graphVisualiser_runtimes.out: error while loading shared libraries: libcgraph.so.6: cannot open shared object file: No such file or directory
    
     ************** Frame index 1 : Running float import ************* 
    /home/leo/code/edgeai-tidl-tools-master/examples/osrt_python/ort/tidl_tools/tidl_graphVisualiser.out: error while loading shared libraries: libcgraph.so.6: cannot open shared object file: No such file or directory
    ****************************************************
    **                ALL MODEL CHECK PASSED          **
    ****************************************************
    
    The soft limit is 2048
    The hard limit is 2048
    MEM: Init ... !!!
    MEM: Init ... Done !!!
     0.0s:  VX_ZONE_INIT:Enabled
     0.6s:  VX_ZONE_ERROR:Enabled
     0.7s:  VX_ZONE_WARNING:Enabled
     0.1533s:  VX_ZONE_INIT:[tivxInit:184] Initialization Done !!!
    
    **********  Frame Index 1 : Running float inference **********
    
     ************** Frame index 1 : Running float import ************* 
    /home/leo/code/edgeai-tidl-tools-master/examples/osrt_python/ort/tidl_tools/tidl_graphVisualiser.out: error while loading shared libraries: libcgraph.so.6: cannot open shared object file: No such file or directory
    INFORMATION: [TIDL_ResizeLayer] Resize_118 Any resize ratio which is power of 2 and greater than 4 will be placed by combination of 4x4 resize layer and 2x2 resize layer. For example a 8x8 resize will be replaced by 4x4 resize followed by 2x2 resize.
    INFORMATION: [TIDL_ResizeLayer] Resize_140 Any resize ratio which is power of 2 and greater than 4 will be placed by combination of 4x4 resize layer and 2x2 resize layer. For example a 8x8 resize will be replaced by 4x4 resize followed by 2x2 resize.
    ****************************************************
    **          2 WARNINGS          0 ERRORS          **
    ****************************************************
    
    **********  Frame Index 1 : Running float inference **********
    
     ************** Frame index 1 : Running float import ************* 
    /home/leo/code/edgeai-tidl-tools-master/examples/osrt_python/ort/tidl_tools/tidl_graphVisualiser.out: error while loading shared libraries: libcgraph.so.6: cannot open shared object file: No such file or directory
    ****************************************************
    **                ALL MODEL CHECK PASSED          **
    ****************************************************
    
    
    **********  Frame Index 1 : Running float inference **********
    
    **********  Frame Index 2 : Running fixed point mode for calibration **********
    
    ~~~~~Running TIDL in PC emulation mode to collect Activations range for each layer~~~~~
    
    Processing config file #0 : /home/leo/code/edgeai-tidl-tools-master/model-artifacts/besta/tempDir/228_tidl_io_.qunat_stats_config.txt 
     Freeing memory for user provided Net
     ----------------------- TIDL Process with REF_ONLY FLOW ------------------------
    
    #    0 . .. T    9640.59  .... ..... ... .... .....
    #    1 . .. T    9591.98  .... ..... ... .... .....
    ~~~~~Running TIDL in PC emulation mode to collect Activations range for each layer~~~~~
    
    Processing config file #0 : /home/leo/code/edgeai-tidl-tools-master/model-artifacts/besta/tempDir/228_tidl_io_.qunat_stats_config.txt 
     Freeing memory for user provided Net
     ----------------------- TIDL Process with REF_ONLY FLOW ------------------------
    
    #    0 . .. T    7122.62  .... ..... ... .... .....
    #    1 . .. T    7123.85  .... ..... ... .... .....
     
     
     *****************   Calibration iteration number 0 completed ************************ 
     
     
     
    
    ~~~~~Running TIDL in PC emulation mode to collect Activations range for each layer~~~~~
    
    Processing config file #0 : /home/leo/code/edgeai-tidl-tools-master/model-artifacts/besta/tempDir/228_tidl_io_.qunat_stats_config.txt 
     Freeing memory for user provided Net
     ----------------------- TIDL Process with REF_ONLY FLOW ------------------------
    
    #    0 . .. T    7126.32  .... ..... ... .... .....
    #    1 . .. T    7126.64  .... ..... ... .... .....
     
     
     *****************   Calibration iteration number 1 completed ************************ 
     
     
     
    
    ~~~~~Running TIDL in PC emulation mode to collect Activations range for each layer~~~~~
    
    Processing config file #0 : /home/leo/code/edgeai-tidl-tools-master/model-artifacts/besta/tempDir/228_tidl_io_.qunat_stats_config.txt 
     Freeing memory for user provided Net
     ----------------------- TIDL Process with REF_ONLY FLOW ------------------------
    
    #    0 . .. T    7120.21  .... ..... ... .... .....
    #    1 . .. T    7150.90  .... ..... ... .... .....
     
     
     *****************   Calibration iteration number 2 completed ************************ 
     
     
     
    
    ~~~~~Running TIDL in PC emulation mode to collect Activations range for each layer~~~~~
    
    Processing config file #0 : /home/leo/code/edgeai-tidl-tools-master/model-artifacts/besta/tempDir/228_tidl_io_.qunat_stats_config.txt 
     Freeing memory for user provided Net
     ----------------------- TIDL Process with REF_ONLY FLOW ------------------------
    
    #    0 . .. T    7168.20  .... ..... ... .... .....
    #    1 . .. T    7163.76  .... ..... ... .... .....
     
     
     *****************   Calibration iteration number 3 completed ************************ 
     
     
     
    
    ~~~~~Running TIDL in PC emulation mode to collect Activations range for each layer~~~~~
    
    Processing config file #0 : /home/leo/code/edgeai-tidl-tools-master/model-artifacts/besta/tempDir/228_tidl_io_.qunat_stats_config.txt 
     Freeing memory for user provided Net
     ----------------------- TIDL Process with REF_ONLY FLOW ------------------------
    
    #    0 . .. T    7127.88  .... ..... ... .... .....
    #    1 . .. T    7137.15  .... ..... ... .... .....
     
     
     *****************   Calibration iteration number 4 completed ************************ 
     
     
     
    
    ------------------ Network Compiler Traces -----------------------------
    NC running for device: 1
    Running with OTF buffer optimizations
    successful Memory allocation
    /home/leo/code/edgeai-tidl-tools-master/examples/osrt_python/ort/tidl_tools/tidl_graphVisualiser.out: error while loading shared libraries: libcgraph.so.6: cannot open shared object file: No such file or directory
    ****************************************************
    **                ALL MODEL CHECK PASSED          **
    ****************************************************
    
    
    **********  Frame Index 2 : Running fixed point mode for calibration **********
    
    ~~~~~Running TIDL in PC emulation mode to collect Activations range for each layer~~~~~
    
    Processing config file #0 : /home/leo/code/edgeai-tidl-tools-master/model-artifacts/besta/tempDir/326365404_tidl_io_.qunat_stats_config.txt 
     Freeing memory for user provided Net
     ----------------------- TIDL Process with REF_ONLY FLOW ------------------------
    
    #    0 . .. T    6665.58  .... ..... ... .... .....
    #    1 . .. T    6647.75  .... ..... ... .... .....
    ~~~~~Running TIDL in PC emulation mode to collect Activations range for each layer~~~~~
    
    Processing config file #0 : /home/leo/code/edgeai-tidl-tools-master/model-artifacts/besta/tempDir/326365404_tidl_io_.qunat_stats_config.txt 
     Freeing memory for user provided Net
     ----------------------- TIDL Process with REF_ONLY FLOW ------------------------
    
    #    0 . .. T    3502.79  .... ..... ... .... .....
    #    1 . .. T    3493.17  .... ..... ... .... .....
     
     
     *****************   Calibration iteration number 0 completed ************************ 
     
     
     
    
    ~~~~~Running TIDL in PC emulation mode to collect Activations range for each layer~~~~~
    
    Processing config file #0 : /home/leo/code/edgeai-tidl-tools-master/model-artifacts/besta/tempDir/326365404_tidl_io_.qunat_stats_config.txt 
     Freeing memory for user provided Net
     ----------------------- TIDL Process with REF_ONLY FLOW ------------------------
    
    #    0 . .. T    3507.26  .... ..... ... .... .....
    #    1 . .. T    3513.30  .... ..... ... .... .....
     
     
     *****************   Calibration iteration number 1 completed ************************ 
     
     
     
    
    ~~~~~Running TIDL in PC emulation mode to collect Activations range for each layer~~~~~
    
    Processing config file #0 : /home/leo/code/edgeai-tidl-tools-master/model-artifacts/besta/tempDir/326365404_tidl_io_.qunat_stats_config.txt 
     Freeing memory for user provided Net
     ----------------------- TIDL Process with REF_ONLY FLOW ------------------------
    
    #    0 . .. T    3498.75  .... ..... ... .... .....
    #    1 . .. T    3507.60  .... ..... ... .... .....
     
     
     *****************   Calibration iteration number 2 completed ************************ 
     
     
     
    
    ~~~~~Running TIDL in PC emulation mode to collect Activations range for each layer~~~~~
    
    Processing config file #0 : /home/leo/code/edgeai-tidl-tools-master/model-artifacts/besta/tempDir/326365404_tidl_io_.qunat_stats_config.txt 
     Freeing memory for user provided Net
     ----------------------- TIDL Process with REF_ONLY FLOW ------------------------
    
    #    0 . .. T    3488.07  .... ..... ... .... .....
    #    1 . .. T    3495.94  .... ..... ... .... .....
     
     
     *****************   Calibration iteration number 3 completed ************************ 
     
     
     
    
    ~~~~~Running TIDL in PC emulation mode to collect Activations range for each layer~~~~~
    
    Processing config file #0 : /home/leo/code/edgeai-tidl-tools-master/model-artifacts/besta/tempDir/326365404_tidl_io_.qunat_stats_config.txt 
     Freeing memory for user provided Net
     ----------------------- TIDL Process with REF_ONLY FLOW ------------------------
    
    #    0 . .. T    3499.58  .... ..... ... .... .....
    #    1 . .. T    3488.70  .... ..... ... .... .....
     
     
     *****************   Calibration iteration number 4 completed ************************ 
     
     
     
    
    ------------------ Network Compiler Traces -----------------------------
    NC running for device: 1
    Running with OTF buffer optimizations
    successful Memory allocation
    /home/leo/code/edgeai-tidl-tools-master/examples/osrt_python/ort/tidl_tools/tidl_graphVisualiser.out: error while loading shared libraries: libcgraph.so.6: cannot open shared object file: No such file or directory
    INFORMATION: [TIDL_ResizeLayer] Resize_118 Any resize ratio which is power of 2 and greater than 4 will be placed by combination of 4x4 resize layer and 2x2 resize layer. For example a 8x8 resize will be replaced by 4x4 resize followed by 2x2 resize.
    INFORMATION: [TIDL_ResizeLayer] Resize_140 Any resize ratio which is power of 2 and greater than 4 will be placed by combination of 4x4 resize layer and 2x2 resize layer. For example a 8x8 resize will be replaced by 4x4 resize followed by 2x2 resize.
    ****************************************************
    **          2 WARNINGS          0 ERRORS          **
    ****************************************************
    
    **********  Frame Index 2 : Running fixed point mode for calibration **********
    
    ~~~~~Running TIDL in PC emulation mode to collect Activations range for each layer~~~~~
    
    Processing config file #0 : /home/leo/code/edgeai-tidl-tools-master/model-artifacts/besta/tempDir/output0_tidl_io_.qunat_stats_config.txt 
     Freeing memory for user provided Net
     ----------------------- TIDL Process with REF_ONLY FLOW ------------------------
    
    #    0 . .. T      64.20  .... ..... ... .... .....
    #    1 . .. T      56.35  .... ..... ... .... .....
    ~~~~~Running TIDL in PC emulation mode to collect Activations range for each layer~~~~~
    
    Processing config file #0 : /home/leo/code/edgeai-tidl-tools-master/model-artifacts/besta/tempDir/output0_tidl_io_.qunat_stats_config.txt 
     Freeing memory for user provided Net
     ----------------------- TIDL Process with REF_ONLY FLOW ------------------------
    
    #    0 . .. T      68.55  .... ..... ... .... .....
    #    1 . .. T      64.69  .... ..... ... .... .....
     
     
     *****************   Calibration iteration number 0 completed ************************ 
     
     
     
    
    ~~~~~Running TIDL in PC emulation mode to collect Activations range for each layer~~~~~
    
    Processing config file #0 : /home/leo/code/edgeai-tidl-tools-master/model-artifacts/besta/tempDir/output0_tidl_io_.qunat_stats_config.txt 
     Freeing memory for user provided Net
     ----------------------- TIDL Process with REF_ONLY FLOW ------------------------
    
    #    0 . .. T      68.72  .... ..... ... .... .....
    #    1 . .. T      64.46  .... ..... ... .... .....
     
     
     *****************   Calibration iteration number 1 completed ************************ 
     
     
     
    
    ~~~~~Running TIDL in PC emulation mode to collect Activations range for each layer~~~~~
    
    Processing config file #0 : /home/leo/code/edgeai-tidl-tools-master/model-artifacts/besta/tempDir/output0_tidl_io_.qunat_stats_config.txt 
     Freeing memory for user provided Net
     ----------------------- TIDL Process with REF_ONLY FLOW ------------------------
    
    #    0 . .. T      70.52  .... ..... ... .... .....
    #    1 . .. T      64.40  .... ..... ... .... .....
     
     
     *****************   Calibration iteration number 2 completed ************************ 
     
     
     
    
    ~~~~~Running TIDL in PC emulation mode to collect Activations range for each layer~~~~~
    
    Processing config file #0 : /home/leo/code/edgeai-tidl-tools-master/model-artifacts/besta/tempDir/output0_tidl_io_.qunat_stats_config.txt 
     Freeing memory for user provided Net
     ----------------------- TIDL Process with REF_ONLY FLOW ------------------------
    
    #    0 . .. T      68.99  .... ..... ... .... .....
    #    1 . .. T      64.80  .... ..... ... .... .....
     
     
     *****************   Calibration iteration number 3 completed ************************ 
     
     
     
    
    ~~~~~Running TIDL in PC emulation mode to collect Activations range for each layer~~~~~
    
    Processing config file #0 : /home/leo/code/edgeai-tidl-tools-master/model-artifacts/besta/tempDir/output0_tidl_io_.qunat_stats_config.txt 
     Freeing memory for user provided Net
     ----------------------- TIDL Process with REF_ONLY FLOW ------------------------
    
    #    0 . .. T      68.09  .... ..... ... .... .....
    #    1 . .. T      64.64  .... ..... ... .... .....
     
     
     *****************   Calibration iteration number 4 completed ************************ 
     
     
     
    
    ------------------ Network Compiler Traces -----------------------------
    NC running for device: 1
    Running with OTF buffer optimizations
    successful Memory allocation
    /home/leo/code/edgeai-tidl-tools-master/examples/osrt_python/ort/tidl_tools/tidl_graphVisualiser.out: error while loading shared libraries: libcgraph.so.6: cannot open shared object file: No such file or directory
    ****************************************************
    **                ALL MODEL CHECK PASSED          **
    ****************************************************
    
    
     
    Completed_Model :     1, Name : besta                                             , Total time :   89329.31, Offload Time :    9685.48 , DDR RW MBs : 0, Output File : py_out_besta_2.jpg 
     
     
    MEM: Deinit ... !!!
    MEM: Alloc's: 89 alloc's of 1044781908 bytes 
    MEM: Free's : 89 free's  of 1044781908 bytes 
    MEM: Open's : 0 allocs  of 0 bytes 
    MEM: Deinit ... Done !!!
    
    
    
    这是编译时的log文件

  • 好的收到了,

    能否确认您的电路板具有与网络编译期间使用的 SDK 版本相同的版本?

    还得和您确认下,您在板上用的 SDK 版本是?以及您用于编译上述模型的 tidl-tools 的 SDK 版本是? 

  • 请问哪个命令可以查看板子上及编译模型的 tidl-tools sdk版本,在哪里可以查看版本?

  • 板子的SDK 版本应该是您在创建 Linux SDK 映像时使用的版本,您可以检查使用了哪个 SDK 映像版本进行闪存。

    关于 tidl tools版本,您可以检查 tidl 工具 git hub repo 的标签,理想情况下,应该会针对您的SDK 版本使用特定的分支。