Please provide complete information as applicable to your setup.
• Hardware Platform (Jetson / GPU)
Jetson Nano
• DeepStream Version
5.1
• JetPack Version (valid for Jetson only)
4.5.1
• Issue Type( questions, new requirements, bugs)
Bugs
• How to reproduce the issue ? (This is for bugs. Including which sample app is using, the configuration files content, the command line used and other details for reproducing)
Running the Yolov3_tiny file with the “deepstream-app -c deepstream_app_config_yoloV3_tiny.txt” command causes it to load the model, then fail with “nvinfer gstnvinfer.cpp:1111:get_converted_buffer:<primary_gie> cudaMemset2DAsync failed with error cudaErrorInvalidValue while converting buffer”.
Full log is below:
Unknown or legacy key specified 'is-classifier' for group [property] Warn: 'threshold' parameter has been deprecated. Use 'pre-cluster-threshold' instead. gstnvtracker: Loading low-level lib at /opt/nvidia/deepstream/deepstream-5.1/lib/libnvds_mot_klt.so gstnvtracker: Optional NvMOT_RemoveStreams not implemented gstnvtracker: Batch processing is OFF gstnvtracker: Past frame output is OFF 0:00:00.293626655 8499 0x31963200 INFO nvinfer gstnvinfer.cpp:619:gst_nvinfer_logger:<primary_gie> NvDsInferContext[UID 1]: Info from NvDsInferContextImpl::buildModel() <nvdsinfer_context_impl.cpp:1716> [UID = 1]: Trying to create engine from model files Loading pre-trained weights... Loading weights of yolov3-tiny complete! Total Number of weights read : 8858734 Loading pre-trained weights... Loading weights of yolov3-tiny complete! Total Number of weights read : 8858734 Building Yolo network... layer inp_size out_size weightPtr (0) conv-bn-leaky 3 x 416 x 416 16 x 416 x 416 496 (1) maxpool 16 x 416 x 416 16 x 208 x 208 496 (2) conv-bn-leaky 16 x 208 x 208 32 x 208 x 208 5232 (3) maxpool 32 x 208 x 208 32 x 104 x 104 5232 (4) conv-bn-leaky 32 x 104 x 104 64 x 104 x 104 23920 (5) maxpool 64 x 104 x 104 64 x 52 x 52 23920 (6) conv-bn-leaky 64 x 52 x 52 128 x 52 x 52 98160 (7) maxpool 128 x 52 x 52 128 x 26 x 26 98160 (8) conv-bn-leaky 128 x 26 x 26 256 x 26 x 26 394096 (9) maxpool 256 x 26 x 26 256 x 13 x 13 394096 (10) conv-bn-leaky 256 x 13 x 13 512 x 13 x 13 1575792 (11) maxpool 512 x 13 x 13 512 x 13 x 13 1575792 (12) conv-bn-leaky 512 x 13 x 13 1024 x 13 x 13 6298480 (13) conv-bn-leaky 1024 x 13 x 13 256 x 13 x 13 6561648 (14) conv-bn-leaky 256 x 13 x 13 512 x 13 x 13 7743344 (15) conv-linear 512 x 13 x 13 255 x 13 x 13 7874159 (16) yolo 255 x 13 x 13 255 x 13 x 13 7874159 (17) route - 256 x 13 x 13 7874159 (18) conv-bn-leaky 256 x 13 x 13 128 x 13 x 13 7907439 INFO: [TRT]: mm1_19: broadcasting input0 to make tensors conform, dims(input0)=[1,26,13][NONE] dims(input1)=[128,13,13][NONE]. INFO: [TRT]: mm2_19: broadcasting input1 to make tensors conform, dims(input0)=[128,26,13][NONE] dims(input1)=[1,13,26][NONE]. (19) upsample 128 x 13 x 13 128 x 26 x 26 - (20) route - 384 x 26 x 26 7907439 (21) conv-bn-leaky 384 x 26 x 26 256 x 26 x 26 8793199 (22) conv-linear 256 x 26 x 26 255 x 26 x 26 8858734 (23) yolo 255 x 26 x 26 255 x 26 x 26 8858734 Output yolo blob names : yolo_17 yolo_24 Total number of yolo layers: 49 Building yolo network complete! Building the TensorRT Engine... INFO: [TRT]: mm1_19: broadcasting input0 to make tensors conform, dims(input0)=[1,26,13][NONE] dims(input1)=[128,13,13][NONE]. INFO: [TRT]: mm2_19: broadcasting input1 to make tensors conform, dims(input0)=[128,26,13][NONE] dims(input1)=[1,13,26][NONE]. INFO: [TRT]: INFO: [TRT]: --------------- Layers running on DLA: INFO: [TRT]: INFO: [TRT]: --------------- Layers running on GPU: INFO: [TRT]: conv_1, leaky_1, maxpool_2, conv_3, leaky_3, maxpool_4, conv_5, leaky_5, maxpool_6, conv_7, leaky_7, maxpool_8, conv_9, leaky_9, maxpool_10, conv_11, leaky_11, maxpool_12, conv_13, leaky_13, conv_14, leaky_14, conv_19, conv_15, postMul_19, leaky_19, preMul_19, mm1_19, mm2_19, (Unnamed Layer* 42) [Matrix Multiply]_output copy, leaky_15, conv_16, yolo_17, conv_22, leaky_22, conv_23, yolo_24, INFO: [TRT]: Some tactics do not have sufficient workspace memory to run. Increasing workspace size may increase performance, please check verbose output. INFO: [TRT]: Detected 1 inputs and 2 output network tensors. Building complete! 0:01:03.844424604 8499 0x31963200 INFO nvinfer gstnvinfer.cpp:619:gst_nvinfer_logger:<primary_gie> NvDsInferContext[UID 1]: Info from NvDsInferContextImpl::buildModel() <nvdsinfer_context_impl.cpp:1749> [UID = 1]: serialize cuda engine to file: /opt/nvidia/deepstream/deepstream-5.1/sources/objectDetector_Yolo/model_b1_gpu0_fp32.engine successfully INFO: [Implicit Engine Info]: layers num: 3 0 INPUT kFLOAT data 3x416x416 1 OUTPUT kFLOAT yolo_17 255x13x13 2 OUTPUT kFLOAT yolo_24 255x26x26 0:01:03.860735227 8499 0x31963200 INFO nvinfer gstnvinfer_impl.cpp:313:notifyLoadModelStatus:<primary_gie> [UID 1]: Load new model:/opt/nvidia/deepstream/deepstream-5.1/sources/objectDetector_Yolo/config_infer_primary_yoloV3_tiny.txt sucessfully Runtime commands: h: Print this help q: Quit p: Pause r: Resume NOTE: To expand a source in the 2D tiled display and view object details, left-click on the source. To go back to the tiled display, right-click anywhere on the window. **PERF: FPS 0 (Avg) **PERF: 0.00 (0.00) ** INFO: <bus_callback:181>: Pipeline ready Opening in BLOCKING MODE NvMMLiteOpen : Block : BlockType = 261 NVMEDIA: Reading vendor.tegra.display-size : status: 6 NvMMLiteBlockCreate : Block : BlockType = 261 ** INFO: <bus_callback:167>: Pipeline running 0:01:06.380942236 8499 0x311b4370 ERROR nvinfer gstnvinfer.cpp:1111:get_converted_buffer:<primary_gie> cudaMemset2DAsync failed with error cudaErrorInvalidValue while converting buffer 0:01:06.381060732 8499 0x311b4370 WARN nvinfer gstnvinfer.cpp:1372:gst_nvinfer_process_full_frame:<primary_gie> error: Buffer conversion failed ERROR from primary_gie: Buffer conversion failed Debug info: /dvs/git/dirty/git-master_linux/deepstream/sdk/src/gst-plugins/gst-nvinfer/gstnvinfer.cpp(1372): gst_nvinfer_process_full_frame (): /GstPipeline:pipeline/GstBin:primary_gie_bin/GstNvInfer:primary_gie ERROR from qtdemux0: Internal data stream error. Debug info: qtdemux.c(6073): gst_qtdemux_loop (): /GstPipeline:pipeline/GstBin:multi_src_bin/GstBin:src_sub_bin0/GstURIDecodeBin:src_elem/GstDecodeBin:decodebin0/GstQTDemux:qtdemux0: streaming stopped, reason error (-5) Quitting App run failed