Other Parts Discussed in Thread: AM69A
模型转化时,设置numBatches = 6,为什么输入尺寸为288*512的resnet18模型可以正确转化,而输入尺寸为288*576的resnet18模型转化不成功。报以下错误:“ERROR: Batch processing is not supported with large feature map case 。”请问: 1、large feature map的阈值是多少;2、为什么会出现这种问题呢
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您好,您的问题我们需要升级到英文论坛寻求帮助,链接如下,有答复尽快给您:
您好,
请问您用的SDK版本是多少?从您分享的log来看似乎是8.2。
从9.0 SDK 起,对多核 DSP AM69A/TDA4VH 提供batch processing支持。
您好,
是否支持Ubuntu18.04
您可以通过以下方法来检查特定 SDK 的操作系统版本支持。
进入 TI.com 并搜索您正在处理/查找的 SoC,然后选择您感兴趣的相应 SDK 版本,如下所示。
https://www.ti.com/tool/PROCESSOR-SDK-J721E
确认以下字段部分:
请问有最新的TI Deep Learning Product User Guide吗?
用户可以通过以下方法了解如何获取有关 TIDL 产品的最新user guide。
按照以上流程操作,访问主产品页面https://www.ti.com/tool/PROCESSOR-SDK-J721E
选择正确的 SDK 版本,然后单击"SDK 文档" https://software-dl.ti.com/jacinto7/esd/processor-sdk-rtos-jacinto7/09_00_01_01/exports/docs/psdk_rtos/docs/user_guide/index.html
单击"SDK 组件"并选择TIDL,然后单击此处的User Guidehttps://software-dl.ti.com/jacinto7/esd/processor-sdk-rtos-jacinto7/09_00_01_01/exports/docs/psdk_rtos/docs/user_guide/sdk_components_j721e.html#ti-deep-learning-product-tidl
您好,
升级SDK到9.0后仍不支持大尺寸多batch(1024*576,batch4输入)模型在板端的推理吗?WARNING: [TIDL_E_DATAFLOW_INFO_NULL] Network compiler returned with error or didn't executed, this model can only be used on PC/Host emulation mode, it is not expected to work on target/EVM.
执行如下操作:
gmm@gmm:~/tda4/ti-processor-sdk-rtos-j721e-evm-09_00_00_02/c7x-mma-tidl/ti_dl/utils/tidlModelImport$ ./out/tidl_model_import.out /home/gmm/tda4/ti-processor-sdk-rtos-j721e-evm-09_00_00_02/c7x-mma-tidl/ti_dl/test/testvecs/config/import/public/onnx/tidl_import_batch4_resnet18_1024_576.txt
ONNX Model (Proto) File : ../../test/testvecs/models/public/onnx/resnet18-1024_576-sim.onnx
TIDL Network File : ../../test/testvecs/config/tidl_models/onnx/tidl_net_batch4_resnet18_1024.bin
TIDL IO Info File : ../../test/testvecs/config/tidl_models/onnx/tidl_io_batch4_resnet18_1024_
Current ONNX OpSet Version : 8
Empty prototxt path, running calibration
~~~~~Running TIDL in PC emulation mode to collect Activations range for each layer~~~~~
Processing config file #0 : /home/gmm/tda4/ti-processor-sdk-rtos-j721e-evm-09_00_00_02/c7x-mma-tidl/ti_dl/test/testvecs/config/tidl_models/onnx/tidl_import_batch4_resnet18_1024_576.txt.qunat_stats_config.txt
Freeing memory for user provided Net
----------------------- TIDL Process with REF_ONLY FLOW ------------------------
# 0 . .. T 264461.15 .... ..... ...
A : 895, 0.0000, 1.0000, 405 .... .....
# 1 . .. T 271820.34 .... ..... ...
A : 557, 0.0000, 1.0000, 733 .... .....
# 2 . .. T 264794.91 .... ..... ...
A : 442, 0.0000, 0.6667, 675 .... .....
# 3 . .. T 263599.49 .... ..... ...
A : 498, 0.0000, 0.5000, 456 .... .....
***************** Calibration iteration number 0 started ************************
~~~~~Running TIDL in PC emulation mode to collect Activations range for each layer~~~~~
Processing config file #0 : /home/gmm/tda4/ti-processor-sdk-rtos-j721e-evm-09_00_00_02/c7x-mma-tidl/ti_dl/test/testvecs/config/tidl_models/onnx/tidl_import_batch4_resnet18_1024_576.txt.qunat_stats_config.txt
Freeing memory for user provided Net
----------------------- TIDL Process with REF_ONLY FLOW ------------------------
# 0 . .. T 223584.37 .... ..... ...
A : 895, 0.0000, 1.0000, 405 .... .....
# 1 . .. T 222254.42 .... ..... ...
A : 557, 0.0000, 0.5000, 733 .... .....
# 2 . .. T 222516.39 .... ..... ...
A : 442, 0.0000, 0.3333, 656 .... .....
# 3 . .. T 221994.04 .... ..... ...
A : 498, 0.0000, 0.2500, 475 .... .....
***************** Calibration iteration number 0 completed ************************
------------------ Network Compiler Traces -----------------------------
successful Memory allocation
Floating point exception (core dumped)
Could not open /home/gmm/tda4/ti-processor-sdk-rtos-j721e-evm-09_00_00_02/c7x-mma-tidl/ti_dl/test/testvecs/config/tidl_models/onnx/batch4_resnet18_1024/perfSimInfo.bin
WARNING: [TIDL_E_DATAFLOW_INFO_NULL] Network compiler returned with error or didn't executed, this model can only be used on PC/Host emulation mode, it is not expected to work on target/EVM.
****************************************************
** 1 WARNINGS 0 ERRORS **
****************************************************
您好,
非常抱歉回复晚了。
您使用的是哪个特定于 SoC 的 SDK?
正如之前提到的,multicore器件(TDA4VH/AM69A)支持批batch processing,请确保使用了同样的。
此外请注意:
Number of batches <= Number of cores
对于 TDA4VH/AM69A,DSP 内核的最大数量为4个,因此支持batch processing大小为4的型号。 通过在4个批次模型上迭代运行推理,可以实现更多批次。