SOWENKIN opened a new issue #13810: Assertion `pred_hnd' failed in MXPredCreate step URL: https://github.com/apache/incubator-mxnet/issues/13810 Note: Providing complete information in the most concise form is the best way to get help. This issue template serves as the checklist for essential information to most of the technical issues and bug reports. For non-technical issues and feature requests, feel free to present the information in what you believe is the best form. For Q & A and discussion, please start a discussion thread at https://discuss.mxnet.io ## Description (Brief description of the problem in no more than 2 sentences.) Assertion `pred_hnd' failed in MXPredCreate step ## Environment info (Required) mxnet==1.3.1, mxnet-cu90=1.3.1, gluonCV=0.4.0 using the pretrained coco models with json and params exported from the python script. ``` What to do: 1. Download the diagnosis script from https://raw.githubusercontent.com/apache/incubator-mxnet/master/tools/diagnose.py 2. Run the script using `python diagnose.py` and paste its output here. ``` Package used (Python/R/Scala/Julia): (I'm using ...) For Scala user, please provide: 1. Java version: (`java -version`) 2. Maven version: (`mvn -version`) 3. Scala runtime if applicable: (`scala -version`) For R user, please provide R `sessionInfo()`: ## Build info (Required if built from source) Compiler (gcc/clang/mingw/visual studio): MXNet commit hash: (Paste the output of `git rev-parse HEAD` here.) Build config: (Paste the content of config.mk, or the build command.) ## Error Message: (Paste the complete error message, including stack trace.) ../models/yolo3_darknet53_coco-symbol.json ... 218177 bytes ../models/yolo3_darknet53_coco-0000.params ... 248431467 bytes yolo_detect: /home/inuyasha/Develop/suyongjian/mxnet/yolo_detector/src/test_new.cpp:79: int main(int, char**): Assertion `pred_hnd' failed. Aborted (core dumped) ## Minimum reproducible example (If you are using your own code, please provide a short script that reproduces the error. Otherwise, please provide link to the existing example.) const std::string json_file = "../models/yolo3_darknet53_coco-symbol.json"; const std::string param_file = "../models/yolo3_darknet53_coco-0000.params"; BufferFile json_data(json_file); BufferFile param_data(param_file); // Parameters int dev_type = 1; // 1: cpu, 2: gpu int dev_id = 0; // arbitrary. mx_uint num_input_nodes = 1; // 1 for feedforward const char* input_key[1] = {"data"}; const char** input_keys = input_key; // Image size and channels int width = 512; int height = 512; int channels = 3; const mx_uint input_shape_indptr[2] = { 0, 4 }; const mx_uint input_shape_data[4] = { 1, static_cast<mx_uint>(channels), static_cast<mx_uint>(height), static_cast<mx_uint>(width)}; PredictorHandle pred_hnd = 0; if (json_data.GetLength() == 0 || param_data.GetLength() == 0) { return -1; } // Create Predictor MXPredCreate((const char*)json_data.GetBuffer(), (const char*)param_data.GetBuffer(), static_cast<size_t>(param_data.GetLength()), dev_type, dev_id, num_input_nodes, input_keys, input_shape_indptr, input_shape_data, &pred_hnd); assert(pred_hnd); ## Steps to reproduce (Paste the commands you ran that produced the error.) 1. 2. ## What have you tried to solve it? 1. 2.
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