[参考译文] SK-TDA4VM：模型部署错误

admin

请注意，本文内容源自机器翻译，可能存在语法或其它翻译错误，仅供参考。如需获取准确内容，请参阅链接中的英语原文或自行翻译。

https://e2e.ti.com/support/processors-group/processors/f/processors-forum/1242695/sk-tda4vm-model-deployment-error

器件型号：SK-TDA4VM

大家好、

运行编译的 yolov5s 时、会发生以下错误：

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

您能帮助检查这个问题吗？谢谢。

此致、

切里

2 年多前

0 admin 2 年多前

TI__Guru**** 2547030 points

请注意，本文内容源自机器翻译，可能存在语法或其它翻译错误，仅供参考。如需获取准确内容，请参阅链接中的英语原文或自行翻译。

您好！

您能否确认您的开发板与网络编译时使用的 SDK 版本相同？

您是否还可以共享您的网络编译日志？

普拉蒂克

0 admin 2 年多前

TI__Guru**** 2547030 points

请注意，本文内容源自机器翻译，可能存在语法或其它翻译错误，仅供参考。如需获取准确内容，请参阅链接中的英语原文或自行翻译。

Pratik、您好！

感谢您的支持。

运行后生成的日志文件如下所示：

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[1;67r[m[4l[?7h[H[J
 +--------------------------------------------------------------------------+
 | Lane Detection[3;77H|
 +--------------------------------------------------------------------------+
 +--------------------------------------------------------------------------+
 | Input Src: /opt/edge_ai_apps/data/videos/video_0000_h264.mp4[6;77H|
 | Model Name: yolov5s[7;77H|
 | Model Type: detection[8;77H|
 +--------------------------------------------------------------------------+
 +--------------------------------------------------------------------------+   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 !!!
[H[J
 +--------------------------------------------------------------------------+
 | Lane Detection[3;77H|
 +--------------------------------------------------------------------------+
 +--------------------------------------------------------------------------+
 | Input Src: /opt/edge_ai_apps/data/videos/video_0000_h264.mp4[6;77H|
 | Model Name: yolov5s[7;77H|
 | Model Type: detection[8;77H|
 +--------------------------------------------------------------------------+
 | dl-inference[10;37H:     [0;10;1m  181.26 ms[m   from   1    samples |
 +--------------------------------------------------------------------------+[H[J
 +--------------------------------------------------------------------------+
 | Lane Detection[3;77H|
 +--------------------------------------------------------------------------+
 +--------------------------------------------------------------------------+
 | Input Src: /opt/edge_ai_apps/data/videos/video_0000_h264.mp4[6;77H|
 | Model Name: yolov5s[7;77H|
 | Model Type: detection[8;77H|
 +--------------------------------------------------------------------------+
 | dl-inference[10;37H:     [0;10;1m  181.26 ms[m   from   1    samples |
 +--------------------------------------------------------------------------+[H[J
 +--------------------------------------------------------------------------+
 | Lane Detection[3;77H|
 +--------------------------------------------------------------------------+
 +--------------------------------------------------------------------------+
 | Input Src: /opt/edge_ai_apps/data/videos/video_0000_h264.mp4[6;77H|
 | Model Name: yolov5s[7;77H|
 | Model Type: detection[8;77H|
 +--------------------------------------------------------------------------+
 | dl-inference[10;37H:     [0;10;1m  181.26 ms[m   from   1    samples |
 +--------------------------------------------------------------------------+[H[J
 +--------------------------------------------------------------------------+
 | Lane Detection[3;77H|
 +--------------------------------------------------------------------------+
 +--------------------------------------------------------------------------+
 | Input Src: /opt/edge_ai_apps/data/videos/video_0000_h264.mp4[6;77H|
 | Model Name: yolov5s[7;77H|
 | Model Type: detection[8;77H|
 +--------------------------------------------------------------------------+
 | dl-inference[10;37H:     [0;10;1m  181.26 ms[m   from   1    samples |
 +--------------------------------------------------------------------------+[H[J
 +--------------------------------------------------------------------------+
 | Lane Detection[3;77H|
 +--------------------------------------------------------------------------+
 +--------------------------------------------------------------------------+
 | Input Src: /opt/edge_ai_apps/data/videos/video_0000_h264.mp4[6;77H|
 | Model Name: yolov5s[7;77H|
 | Model Type: detection[8;77H|
 +--------------------------------------------------------------------------+
 | dl-inference[10;37H:     [0;10;1m  181.26 ms[m   from   1    samples |
 +--------------------------------------------------------------------------+[H[J
 +--------------------------------------------------------------------------+
 | Lane Detection[3;77H|
 +--------------------------------------------------------------------------+
 +--------------------------------------------------------------------------+
 | Input Src: /opt/edge_ai_apps/data/videos/video_0000_h264.mp4[6;77H|
 | Model Name: yolov5s[7;77H|
 | Model Type: detection[8;77H|
 +--------------------------------------------------------------------------+
 | dl-inference[10;37H:     [0;10;1m  181.26 ms[m   from   1    samples |
 +--------------------------------------------------------------------------+[H[J
 +--------------------------------------------------------------------------+
 | Lane Detection[3;77H|
 +--------------------------------------------------------------------------+
 +--------------------------------------------------------------------------+
 | Input Src: /opt/edge_ai_apps/data/videos/video_0000_h264.mp4[6;77H|
 | Model Name: yolov5s[7;77H|
 | Model Type: detection[8;77H|
 +--------------------------------------------------------------------------+
 | dl-inference[10;37H:     [0;10;1m  181.26 ms[m   from   1    samples |
 +--------------------------------------------------------------------------+[H[J
 +--------------------------------------------------------------------------+
 | Lane Detection[3;77H|
 +--------------------------------------------------------------------------+
 +--------------------------------------------------------------------------+
 | Input Src: /opt/edge_ai_apps/data/videos/video_0000_h264.mp4[6;77H|
 | Model Name: yolov5s[7;77H|
 | Model Type: detection[8;77H|
 +--------------------------------------------------------------------------+
 | dl-inference[10;37H:     [0;10;1m  181.26 ms[m   from   1    samples |
 +--------------------------------------------------------------------------+[H[J
 +--------------------------------------------------------------------------+
 | Lane Detection[3;77H|
 +--------------------------------------------------------------------------+
 +--------------------------------------------------------------------------+
 | Input Src: /opt/edge_ai_apps/data/videos/video_0000_h264.mp4[6;77H|
 | Model Name: yolov5s[7;77H|
 | Model Type: detection[8;77H|
 +--------------------------------------------------------------------------+
 | dl-inference[10;37H:     [0;10;1m  181.26 ms[m   from   1    samples |
 +--------------------------------------------------------------------------+[H[J
 +--------------------------------------------------------------------------+
 | Lane Detection[3;77H|
 +--------------------------------------------------------------------------+
 +--------------------------------------------------------------------------+
 | Input Src: /opt/edge_ai_apps/data/videos/video_0000_h264.mp4[6;77H|
 | Model Name: yolov5s[7;77H|
 | Model Type: detection[8;77H|
 +--------------------------------------------------------------------------+
 | dl-inference[10;37H:     [0;10;1m  181.26 ms[m   from   1    samples |
 +--------------------------------------------------------------------------+[H[J
 +--------------------------------------------------------------------------+
 | Lane Detection[3;77H|
 +--------------------------------------------------------------------------+
 +--------------------------------------------------------------------------+
 | Input Src: /opt/edge_ai_apps/data/videos/video_0000_h264.mp4[6;77H|
 | Model Name: yolov5s[7;77H|
 | Model Type: detection[8;77H|
 +--------------------------------------------------------------------------+
 | dl-inference[10;37H:     [0;10;1m  181.26 ms[m   from   1    samples |
 +--------------------------------------------------------------------------+[H[J
 +--------------------------------------------------------------------------+
 | Lane Detection[3;77H|
 +--------------------------------------------------------------------------+
 +--------------------------------------------------------------------------+
 | Input Src: /opt/edge_ai_apps/data/videos/video_0000_h264.mp4[6;77H|
 | Model Name: yolov5s[7;77H|
 | Model Type: detection[8;77H|
 +--------------------------------------------------------------------------+
 | dl-inference[10;37H:     [0;10;1m  181.26 ms[m   from   1    samples |
 +--------------------------------------------------------------------------+[H[J
 +--------------------------------------------------------------------------+
 | Lane Detection[3;77H|
 +--------------------------------------------------------------------------+
 +--------------------------------------------------------------------------+
 | Input Src: /opt/edge_ai_apps/data/videos/video_0000_h264.mp4[6;77H|
 | Model Name: yolov5s[7;77H|
 | Model Type: detection[8;77H|
 +--------------------------------------------------------------------------+
 | dl-inference[10;37H:     [0;10;1m  181.26 ms[m   from   1    samples |
 +--------------------------------------------------------------------------+[H[J
 +--------------------------------------------------------------------------+
 | Lane Detection[3;77H|
 +--------------------------------------------------------------------------+
 +--------------------------------------------------------------------------+
 | Input Src: /opt/edge_ai_apps/data/videos/video_0000_h264.mp4[6;77H|
 | Model Name: yolov5s[7;77H|
 | Model Type: detection[8;77H|
 +--------------------------------------------------------------------------+
 | dl-inference[10;37H:     [0;10;1m  181.26 ms[m   from   1    samples |
 +--------------------------------------------------------------------------+[H[J
 +--------------------------------------------------------------------------+
 | Lane Detection[3;77H|
 +--------------------------------------------------------------------------+
 +--------------------------------------------------------------------------+
 | Input Src: /opt/edge_ai_apps/data/videos/video_0000_h264.mp4[6;77H|
 | Model Name: yolov5s[7;77H|
 | Model Type: detection[8;77H|
 +--------------------------------------------------------------------------+
 | dl-inference[10;37H:     [0;10;1m  181.26 ms[m   from   1    samples |
 +--------------------------------------------------------------------------+[H[J
 +--------------------------------------------------------------------------+
 | Lane Detection[3;77H|
 +--------------------------------------------------------------------------+
 +--------------------------------------------------------------------------+
 | Input Src: /opt/edge_ai_apps/data/videos/video_0000_h264.mp4[6;77H|
 | Model Name: yolov5s[7;77H|
 | Model Type: detection[8;77H|
 +--------------------------------------------------------------------------+
 | dl-inference[10;37H:     [0;10;1m  181.26 ms[m   from   1    samples |
 +--------------------------------------------------------------------------+[H[J
 +--------------------------------------------------------------------------+
 | Lane Detection[3;77H|
 +--------------------------------------------------------------------------+
 +--------------------------------------------------------------------------+
 | Input Src: /opt/edge_ai_apps/data/videos/video_0000_h264.mp4[6;77H|
 | Model Name: yolov5s[7;77H|
 | Model Type: detection[8;77H|
 +--------------------------------------------------------------------------+
 | dl-inference[10;37H:     [0;10;1m  181.26 ms[m   from   1    samples |
 +--------------------------------------------------------------------------+[H[J
 +--------------------------------------------------------------------------+
 | Lane Detection[3;77H|
 +--------------------------------------------------------------------------+
 +--------------------------------------------------------------------------+
 | Input Src: /opt/edge_ai_apps/data/videos/video_0000_h264.mp4[6;77H|
 | Model Name: yolov5s[7;77H|
 | Model Type: detection[8;77H|
 +--------------------------------------------------------------------------+
 | dl-inference[10;37H:     [0;10;1m  181.26 ms[m   from   1    samples |
 +--------------------------------------------------------------------------+[H[J
 +--------------------------------------------------------------------------+
 | Lane Detection[3;77H|
 +--------------------------------------------------------------------------+
 +--------------------------------------------------------------------------+
 | Input Src: /opt/edge_ai_apps/data/videos/video_0000_h264.mp4[6;77H|
 | Model Name: yolov5s[7;77H|
 | Model Type: detection[8;77H|
 +--------------------------------------------------------------------------+
 | dl-inference[10;37H:     [0;10;1m  181.26 ms[m   from   1    samples |
 +--------------------------------------------------------------------------+[H[J
 +--------------------------------------------------------------------------+
 | Lane Detection[3;77H|
 +--------------------------------------------------------------------------+
 +--------------------------------------------------------------------------+
 | Input Src: /opt/edge_ai_apps/data/videos/video_0000_h264.mp4[6;77H|
 | Model Name: yolov5s[7;77H|
 | Model Type: detection[8;77H|
 +--------------------------------------------------------------------------+
 | dl-inference[10;37H:     [0;10;1m  181.26 ms[m   from   1    samples |
 +--------------------------------------------------------------------------+[H[J
 +--------------------------------------------------------------------------+
 | Lane Detection[3;77H|
 +--------------------------------------------------------------------------+
 +--------------------------------------------------------------------------+
 | Input Src: /opt/edge_ai_apps/data/videos/video_0000_h264.mp4[6;77H|
 | Model Name: yolov5s[7;77H|
 | Model Type: detection[8;77H|
 +--------------------------------------------------------------------------+
 | dl-inference[10;37H:     [0;10;1m  181.26 ms[m   from   1    samples |
 +--------------------------------------------------------------------------+[H[J
 +--------------------------------------------------------------------------+
 | Lane Detection[3;77H|
 +--------------------------------------------------------------------------+
 +--------------------------------------------------------------------------+
 | Input Src: /opt/edge_ai_apps/data/videos/video_0000_h264.mp4[6;77H|
 | Model Name: yolov5s[7;77H|
 | Model Type: detection[8;77H|
 +--------------------------------------------------------------------------+
 | dl-inference[10;37H:     [0;10;1m  181.26 ms[m   from   1    samples |
 +--------------------------------------------------------------------------+[H[J
 +--------------------------------------------------------------------------+
 | Lane Detection[3;77H|
 +--------------------------------------------------------------------------+
 +--------------------------------------------------------------------------+
 | Input Src: /opt/edge_ai_apps/data/videos/video_0000_h264.mp4[6;77H|
 | Model Name: yolov5s[7;77H|
 | Model Type: detection[8;77H|
 +--------------------------------------------------------------------------+
 | dl-inference[10;37H:     [0;10;1m  181.26 ms[m   from   1    samples |
 +--------------------------------------------------------------------------+[H[J
 +--------------------------------------------------------------------------+
 | Lane Detection[3;77H|
 +--------------------------------------------------------------------------+
 +--------------------------------------------------------------------------+
 | Input Src: /opt/edge_ai_apps/data/videos/video_0000_h264.mp4[6;77H|
 | Model Name: yolov5s[7;77H|
 | Model Type: detection[8;77H|
 +--------------------------------------------------------------------------+
 | dl-inference[10;37H:     [0;10;1m  181.26 ms[m   from   1    samples |
 +--------------------------------------------------------------------------+[H[J
 +--------------------------------------------------------------------------+
 | Lane Detection[3;77H|
 +--------------------------------------------------------------------------+
 +--------------------------------------------------------------------------+
 | Input Src: /opt/edge_ai_apps/data/videos/video_0000_h264.mp4[6;77H|
 | Model Name: yolov5s[7;77H|
 | Model Type: detection[8;77H|
 +--------------------------------------------------------------------------+
 | dl-inference[10;37H:     [0;10;1m  181.26 ms[m   from   1    samples |
 +--------------------------------------------------------------------------+[H[J
 +--------------------------------------------------------------------------+
 | Lane Detection[3;77H|
 +--------------------------------------------------------------------------+
 +--------------------------------------------------------------------------+
 | Input Src: /opt/edge_ai_apps/data/videos/video_0000_h264.mp4[6;77H|
 | Model Name: yolov5s[7;77H|
 | Model Type: detection[8;77H|
 +--------------------------------------------------------------------------+
 | dl-inference[10;37H:     [0;10;1m  181.26 ms[m   from   1    samples |
 +--------------------------------------------------------------------------+[H[J
 +--------------------------------------------------------------------------+
 | Lane Detection[3;77H|
 +--------------------------------------------------------------------------+
 +--------------------------------------------------------------------------+
 | Input Src: /opt/edge_ai_apps/data/videos/video_0000_h264.mp4[6;77H|
 | Model Name: yolov5s[7;77H|
 | Model Type: detection[8;77H|
 +--------------------------------------------------------------------------+
 | dl-inference[10;37H:     [0;10;1m  181.26 ms[m   from   1    samples |
 +--------------------------------------------------------------------------+[H[J
 +--------------------------------------------------------------------------+
 | Lane Detection[3;77H|
 +--------------------------------------------------------------------------+
 +--------------------------------------------------------------------------+
 | Input Src: /opt/edge_ai_apps/data/videos/video_0000_h264.mp4[6;77H|
 | Model Name: yolov5s[7;77H|
 | Model Type: detection[8;77H|
 +--------------------------------------------------------------------------+
 | dl-inference[10;37H:     [0;10;1m  181.26 ms[m   from   1    samples |
 +--------------------------------------------------------------------------+[H[J
 +--------------------------------------------------------------------------+
 | Lane Detection[3;77H|
 +--------------------------------------------------------------------------+
 +--------------------------------------------------------------------------+
 | Input Src: /opt/edge_ai_apps/data/videos/video_0000_h264.mp4[6;77H|
 | Model Name: yolov5s[7;77H|
 | Model Type: detection[8;77H|
 +--------------------------------------------------------------------------+
 | dl-inference[10;37H:     [0;10;1m  181.26 ms[m   from   1    samples |
 +--------------------------------------------------------------------------+[H[J
 +--------------------------------------------------------------------------+
 | Lane Detection[3;77H|
 +--------------------------------------------------------------------------+
 +--------------------------------------------------------------------------+
 | Input Src: /opt/edge_ai_apps/data/videos/video_0000_h264.mp4[6;77H|
 | Model Name: yolov5s[7;77H|
 | Model Type: detection[8;77H|
 +--------------------------------------------------------------------------+
 | dl-inference[10;37H:     [0;10;1m  181.26 ms[m   from   1    samples |
 +--------------------------------------------------------------------------+[H[J
 +--------------------------------------------------------------------------+
 | Lane Detection[3;77H|
 +--------------------------------------------------------------------------+
 +--------------------------------------------------------------------------+
 | Input Src: /opt/edge_ai_apps/data/videos/video_0000_h264.mp4[6;77H|
 | Model Name: yolov5s[7;77H|
 | Model Type: detection[8;77H|
 +--------------------------------------------------------------------------+
 | dl-inference[10;37H:     [0;10;1m  181.26 ms[m   from   1    samples |
 +--------------------------------------------------------------------------+[H[J
 +--------------------------------------------------------------------------+
 | Lane Detection[3;77H|
 +--------------------------------------------------------------------------+
 +--------------------------------------------------------------------------+
 | Input Src: /opt/edge_ai_apps/data/videos/video_0000_h264.mp4[6;77H|
 | Model Name: yolov5s[7;77H|
 | Model Type: detection[8;77H|
 +--------------------------------------------------------------------------+
 | dl-inference[10;37H:     [0;10;1m  181.26 ms[m   from   1    samples |
 +--------------------------------------------------------------------------+[H[J
 +--------------------------------------------------------------------------+
 | Lane Detection[3;77H|
 +--------------------------------------------------------------------------+
 +--------------------------------------------------------------------------+
 | Input Src: /opt/edge_ai_apps/data/videos/video_0000_h264.mp4[6;77H|
 | Model Name: yolov5s[7;77H|
 | Model Type: detection[8;77H|
 +--------------------------------------------------------------------------+
 | dl-inference[10;37H:     [0;10;1m  181.26 ms[m   from   1    samples |
 +--------------------------------------------------------------------------+[H[J
 +--------------------------------------------------------------------------+
 | Lane Detection[3;77H|
 +--------------------------------------------------------------------------+
 +--------------------------------------------------------------------------+
 | Input Src: /opt/edge_ai_apps/data/videos/video_0000_h264.mp4[6;77H|
 | Model Name: yolov5s[7;77H|
 | Model Type: detection[8;77H|
 +--------------------------------------------------------------------------+
 | dl-inference[10;37H:     [0;10;1m  181.26 ms[m   from   1    samples |
 +--------------------------------------------------------------------------+[H[J
 +--------------------------------------------------------------------------+
 | Lane Detection[3;77H|
 +--------------------------------------------------------------------------+
 +--------------------------------------------------------------------------+
 | Input Src: /opt/edge_ai_apps/data/videos/video_0000_h264.mp4[6;77H|
 | Model Name: yolov5s[7;77H|
 | Model Type: detection[8;77H|
 +--------------------------------------------------------------------------+
 | dl-inference[10;37H:     [0;10;1m  181.26 ms[m   from   1    samples |
 +--------------------------------------------------------------------------+[H[J
 +--------------------------------------------------------------------------+
 | Lane Detection[3;77H|
 +--------------------------------------------------------------------------+
 +--------------------------------------------------------------------------+
 | Input Src: /opt/edge_ai_apps/data/videos/video_0000_h264.mp4[6;77H|
 | Model Name: yolov5s[7;77H|
 | Model Type: detection[8;77H|
 +--------------------------------------------------------------------------+
 | dl-inference[10;37H:     [0;10;1m  181.26 ms[m   from   1    samples |
 +--------------------------------------------------------------------------+[H[J
 +--------------------------------------------------------------------------+
 | Lane Detection[3;77H|
 +--------------------------------------------------------------------------+
 +--------------------------------------------------------------------------+
 | Input Src: /opt/edge_ai_apps/data/videos/video_0000_h264.mp4[6;77H|
 | Model Name: yolov5s[7;77H|
 | Model Type: detection[8;77H|
 +--------------------------------------------------------------------------+
 | dl-inference[10;37H:     [0;10;1m  181.26 ms[m   from   1    samples |
 +--------------------------------------------------------------------------+[H[J
 +--------------------------------------------------------------------------+
 | Lane Detection[3;77H|
 +--------------------------------------------------------------------------+
 +--------------------------------------------------------------------------+
 | Input Src: /opt/edge_ai_apps/data/videos/video_0000_h264.mp4[6;77H|
 | Model Name: yolov5s[7;77H|
 | Model Type: detection[8;77H|
 +--------------------------------------------------------------------------+
 | dl-inference[10;37H:     [0;10;1m  181.26 ms[m   from   1    samples |
 +--------------------------------------------------------------------------+[H[J
 +--------------------------------------------------------------------------+
 | Lane Detection[3;77H|
 +--------------------------------------------------------------------------+
 +--------------------------------------------------------------------------+
 | Input Src: /opt/edge_ai_apps/data/videos/video_0000_h264.mp4[6;77H|
 | Model Name: yolov5s[7;77H|
 | Model Type: detection[8;77H|
 +--------------------------------------------------------------------------+
 | dl-inference[10;37H:     [0;10;1m  181.26 ms[m   from   1    samples |
 +--------------------------------------------------------------------------+[H[J
 +--------------------------------------------------------------------------+
 | Lane Detection[3;77H|
 +--------------------------------------------------------------------------+
 +--------------------------------------------------------------------------+
 | Input Src: /opt/edge_ai_apps/data/videos/video_0000_h264.mp4[6;77H|
 | Model Name: yolov5s[7;77H|
 | Model Type: detection[8;77H|
 +--------------------------------------------------------------------------+
 | dl-inference[10;37H:     [0;10;1m  181.26 ms[m   from   1    samples |
 +--------------------------------------------------------------------------+[H[J
 +--------------------------------------------------------------------------+
 | Lane Detection[3;77H|
 +--------------------------------------------------------------------------+
 +--------------------------------------------------------------------------+
 | Input Src: /opt/edge_ai_apps/data/videos/video_0000_h264.mp4[6;77H|
 | Model Name: yolov5s[7;77H|
 | Model Type: detection[8;77H|
 +--------------------------------------------------------------------------+
 | dl-inference[10;37H:     [0;10;1m  181.26 ms[m   from   1    samples |
 +--------------------------------------------------------------------------+[H[J
 +--------------------------------------------------------------------------+
 | Lane Detection[3;77H|
 +--------------------------------------------------------------------------+
 +--------------------------------------------------------------------------+
 | Input Src: /opt/edge_ai_apps/data/videos/video_0000_h264.mp4[6;77H|
 | Model Name: yolov5s[7;77H|
 | Model Type: detection[8;77H|
 +--------------------------------------------------------------------------+
 | dl-inference[10;37H:     [0;10;1m  181.26 ms[m   from   1    samples |
 +--------------------------------------------------------------------------+[H[J
 +--------------------------------------------------------------------------+
 | Lane Detection[3;77H|
 +--------------------------------------------------------------------------+
 +--------------------------------------------------------------------------+
 | Input Src: /opt/edge_ai_apps/data/videos/video_0000_h264.mp4[6;77H|
 | Model Name: yolov5s[7;77H|
 | Model Type: detection[8;77H|
 +--------------------------------------------------------------------------+
 | dl-inference[10;37H:     [0;10;1m  181.26 ms[m   from   1    samples |
 +--------------------------------------------------------------------------+[H[J
 +--------------------------------------------------------------------------+
 | Lane Detection[3;77H|
 +--------------------------------------------------------------------------+
 +--------------------------------------------------------------------------+
 | Input Src: /opt/edge_ai_apps/data/videos/video_0000_h264.mp4[6;77H|
 | Model Name: yolov5s[7;77H|
 | Model Type: detection[8;77H|
 +--------------------------------------------------------------------------+
 | dl-inference[10;37H:     [0;10;1m  181.26 ms[m   from   1    samples |
 +--------------------------------------------------------------------------+[H[J
 +--------------------------------------------------------------------------+
 | Lane Detection[3;77H|
 +--------------------------------------------------------------------------+
 +--------------------------------------------------------------------------+
 | Input Src: /opt/edge_ai_apps/data/videos/video_0000_h264.mp4[6;77H|
 | Model Name: yolov5s[7;77H|
 | Model Type: detection[8;77H|
 +--------------------------------------------------------------------------+
 | dl-inference[10;37H:     [0;10;1m  181.26 ms[m   from   1    samples |
 +--------------------------------------------------------------------------+[H[J
 +--------------------------------------------------------------------------+
 | Lane Detection[3;77H|
 +--------------------------------------------------------------------------+
 +--------------------------------------------------------------------------+
 | Input Src: /opt/edge_ai_apps/data/videos/video_0000_h264.mp4[6;77H|
 | Model Name: yolov5s[7;77H|
 | Model Type: detection[8;77H|
 +--------------------------------------------------------------------------+
 | dl-inference[10;37H:     [0;10;1m  181.26 ms[m   from   1    samples |
 +--------------------------------------------------------------------------+[H[J
 +--------------------------------------------------------------------------+
 | Lane Detection[3;77H|
 +--------------------------------------------------------------------------+
 +--------------------------------------------------------------------------+
 | Input Src: /opt/edge_ai_apps/data/videos/video_0000_h264.mp4[6;77H|
 | Model Name: yolov5s[7;77H|
 | Model Type: detection[8;77H|
 +--------------------------------------------------------------------------+
 | dl-inference[10;37H:     [0;10;1m  181.26 ms[m   from   1    samples |
 +--------------------------------------------------------------------------+[H[J
 +--------------------------------------------------------------------------+
 | Lane Detection[3;77H|
 +--------------------------------------------------------------------------+
 +--------------------------------------------------------------------------+
 | Input Src: /opt/edge_ai_apps/data/videos/video_0000_h264.mp4[6;77H|
 | Model Name: yolov5s[7;77H|
 | Model Type: detection[8;77H|
 +--------------------------------------------------------------------------+
 | dl-inference[10;37H:     [0;10;1m  181.26 ms[m   from   1    samples |
 +--------------------------------------------------------------------------+[H[J
 +--------------------------------------------------------------------------+
 | Lane Detection[3;77H|
 +--------------------------------------------------------------------------+
 +--------------------------------------------------------------------------+
 | Input Src: /opt/edge_ai_apps/data/videos/video_0000_h264.mp4[6;77H|
 | Model Name: yolov5s[7;77H|
 | Model Type: detection[8;77H|
 +--------------------------------------------------------------------------+
 | dl-inference[10;37H:     [0;10;1m  181.26 ms[m   from   1    samples |
 +--------------------------------------------------------------------------+[H[J
 +--------------------------------------------------------------------------+
 | Lane Detection[3;77H|
 +--------------------------------------------------------------------------+
 +--------------------------------------------------------------------------+
 | Input Src: /opt/edge_ai_apps/data/videos/video_0000_h264.mp4[6;77H|
 | Model Name: yolov5s[7;77H|
 | Model Type: detection[8;77H|
 +--------------------------------------------------------------------------+
 | dl-inference[10;37H:     [0;10;1m  181.26 ms[m   from   1    samples |
 +--------------------------------------------------------------------------+[H[J
 +--------------------------------------------------------------------------+
 | Lane Detection[3;77H|
 +--------------------------------------------------------------------------+
 +--------------------------------------------------------------------------+
 | Input Src: /opt/edge_ai_apps/data/videos/video_0000_h264.mp4[6;77H|
 | Model Name: yolov5s[7;77H|
 | Model Type: detection[8;77H|
 +--------------------------------------------------------------------------+
 | dl-inference[10;37H:     [0;10;1m  181.26 ms[m   from   1    samples |
 +--------------------------------------------------------------------------+[H[J
 +--------------------------------------------------------------------------+
 | Lane Detection[3;77H|
 +--------------------------------------------------------------------------+
 +--------------------------------------------------------------------------+
 | Input Src: /opt/edge_ai_apps/data/videos/video_0000_h264.mp4[6;77H|
 | Model Name: yolov5s[7;77H|
 | Model Type: detection[8;77H|
 +--------------------------------------------------------------------------+
 | dl-inference[10;37H:     [0;10;1m  181.26 ms[m   from   1    samples |
 +--------------------------------------------------------------------------+[H[J
 +--------------------------------------------------------------------------+
 | Lane Detection[3;77H|
 +--------------------------------------------------------------------------+
 +--------------------------------------------------------------------------+
 | Input Src: /opt/edge_ai_apps/data/videos/video_0000_h264.mp4[6;77H|
 | Model Name: yolov5s[7;77H|
 | Model Type: detection[8;77H|
 +--------------------------------------------------------------------------+
 | dl-inference[10;37H:     [0;10;1m  181.26 ms[m   from   1    samples |
 +--------------------------------------------------------------------------+[H[J
 +--------------------------------------------------------------------------+
 | Lane Detection[3;77H|
 +--------------------------------------------------------------------------+
 +--------------------------------------------------------------------------+
 | Input Src: /opt/edge_ai_apps/data/videos/video_0000_h264.mp4[6;77H|
 | Model Name: yolov5s[7;77H|
 | Model Type: detection[8;77H|
 +--------------------------------------------------------------------------+
 | dl-inference[10;37H:     [0;10;1m  181.26 ms[m   from   1    samples |
 +--------------------------------------------------------------------------+[H[J
 +--------------------------------------------------------------------------+
 | Lane Detection[3;77H|
 +--------------------------------------------------------------------------+
 +--------------------------------------------------------------------------+
 | Input Src: /opt/edge_ai_apps/data/videos/video_0000_h264.mp4[6;77H|
 | Model Name: yolov5s[7;77H|
 | Model Type: detection[8;77H|
 +--------------------------------------------------------------------------+
 | dl-inference[10;37H:     [0;10;1m  181.26 ms[m   from   1    samples |
 +--------------------------------------------------------------------------+[H[J
 +--------------------------------------------------------------------------+
 | Lane Detection[3;77H|
 +--------------------------------------------------------------------------+
 +--------------------------------------------------------------------------+
 | Input Src: /opt/edge_ai_apps/data/videos/video_0000_h264.mp4[6;77H|
 | Model Name: yolov5s[7;77H|
 | Model Type: detection[8;77H|
 +--------------------------------------------------------------------------+
 | dl-inference[10;37H:     [0;10;1m  181.26 ms[m   from   1    samples |
 +--------------------------------------------------------------------------+[H[J
 +--------------------------------------------------------------------------+
 | Lane Detection[3;77H|
 +--------------------------------------------------------------------------+
 +--------------------------------------------------------------------------+
 | Input Src: /opt/edge_ai_apps/data/videos/video_0000_h264.mp4[6;77H|
 | Model Name: yolov5s[7;77H|
 | Model Type: detection[8;77H|
 +--------------------------------------------------------------------------+
 | dl-inference[10;37H:     [0;10;1m  181.26 ms[m   from   1    samples |
 +--------------------------------------------------------------------------+[H[J
 +--------------------------------------------------------------------------+
 | Lane Detection[3;77H|
 +--------------------------------------------------------------------------+
 +--------------------------------------------------------------------------+
 | Input Src: /opt/edge_ai_apps/data/videos/video_0000_h264.mp4[6;77H|
 | Model Name: yolov5s[7;77H|
 | Model Type: detection[8;77H|
 +--------------------------------------------------------------------------+
 | dl-inference[10;37H:     [0;10;1m  181.26 ms[m   from   1    samples |
 +--------------------------------------------------------------------------+

编译日志文件如下：

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 !!!

谢谢。此致、

切里

0 admin 2 年多前

TI__Guru**** 2547030 points

请注意，本文内容源自机器翻译，可能存在语法或其它翻译错误，仅供参考。如需获取准确内容，请参阅链接中的英语原文或自行翻译。

您好

感谢您共享编译日志。

Unknown 说：
您能否确认主板的 SDK 版本与网络编译期间使用的版本相同?

您电路板上有哪个 SDK 版本、以及您用于 Tidl-tools 来编译上述模型的 SDK 版本？

此致、

普拉蒂克

0 admin 2 年多前

TI__Guru**** 2547030 points

请注意，本文内容源自机器翻译，可能存在语法或其它翻译错误，仅供参考。如需获取准确内容，请参阅链接中的英语原文或自行翻译。

Pratik、您好！

谢谢、但客户不知道如何检查 SDK 版本、您能提供一些指导吗？

谢谢。此致、

切里

0 admin 2 年多前

TI__Guru**** 2547030 points

请注意，本文内容源自机器翻译，可能存在语法或其它翻译错误，仅供参考。如需获取准确内容，请参阅链接中的英语原文或自行翻译。

您好！

电路板 SDK 版本可以是客户在创建 Linux SDK 映像时使用的版本、您可以检查曾用于闪存的 SDK 映像版本。

关于 tidl 工具版本,可以检查 tidl 工具的标签 git 集线器 repo,理想情况下客户应该使用其 SDK 版本的特定分支。

普拉蒂克

处理器（参考译文帖）

处理器（参考译文帖）(Read Only)

[参考译文] SK-TDA4VM：模型部署错误