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I was able to train mobilenet, however I believe EVE cores are loaded too much so that there is no image. 1) I might be missing a step in configuring...

I installed NCCL to use more gpus to train model. install step: 1. git clone https://github.com/NVIDIA/nccl.git 2. cd nccl 3. sudo make install -j8 4. remove Makefile.config USE_NCCL comment When...

Hi, when I try to train my models, problems happened in the end of every stage. I mean 'initial'、'l1reg'、‘sparse’ and so on. The main work of every stage seems to...

Or change to the address of ti.com such as https://git.ti.com/cgit/jacinto-ai-devkit/caffe-jacinto-models/about/trained/object_detection/voc0712/JDetNet/ssd512x512_ds_PSP_dsFac_32_fc_0_hdDS8_1_kerMbox_3_1stHdSameOpCh_1/initial/deploy.prototxt https://git.ti.com/cgit/jacinto-ai-devkit/caffe-jacinto-models/about/trained/object_detection/voc0712/JDetNet/ssd512x512_ds_PSP_dsFac_32_fc_0_hdDS8_1_kerMbox_3_1stHdSameOpCh_1/initial/voc0712_ssdJacintoNetV2_iter_106000.caffemodel

Hi, While am trying to train the initial training am getting the below error. **I0302 02:22:22.283617 5159 common.cpp:528] NVML initialized, thread 5159 I0302 02:22:22.285171 5132 net.cpp:1071] Ignoring source layer mbox_loss...

I have gone through all the steps and this came out. I tried the symbolic link solution for libturbojpeg but did not change. CXX .build_release/src/caffe/proto/caffe.pb.cc ./3rdparty/half_float/half.hpp(1659): warning: calling a __host__...

Hi, When I tried with mobiledetnetv2, I got the following problem: solver_param: {'type': 'SGD', 'max_iter': 120000, 'stepvalue': [60000, 90000, 300000], 'base_lr': 0.01, 'lr_policy': 'multistep', 'power': 1.0, 'weight_decay': 0.0001} config_param: {'model_name':...

Dear, I try to build with: USE_CUDNN := 0 CPU_ONLY := 1 But always get error: CXX src/caffe/blob.cpp In file included from ./include/caffe/common.hpp:48:0, from ./include/caffe/blob.hpp:11, from src/caffe/blob.cpp:6: ./include/caffe/util/device_alternate.hpp:3:23: fatal error:...

hello, i run the imagenet classification demo, i find it is slower when setting quantize=ture, is it normal? [using quantization](https://github.com/tidsp/caffe-jacinto-models/blob/caffe-0.16/trained/image_classification/imagenet_jacintonet11v2/test_quantize/run.sh) [not using quantization](https://github.com/tidsp/caffe-jacinto-models/blob/caffe-0.16/trained/image_classification/imagenet_jacintonet11v2/test/run.sh)

is there any information about ssd ? like trained model and performance