/builder/cudnnBuilderGraph.cpp (780) - Assertion Error in checkDimsSanity: 0

I’ve been trying to create a YOLO trt engine. But I keep getting

../builder/cudnnBuilderGraph.cpp:780
Aborting...

../builder/cudnnBuilderGraph.cpp (780) - Assertion Error in checkDimsSanity: 0 (dims.d[i] >= 1)

Running builder as;

 engine_ = unique_ptr<nvinfer1::ICudaEngine>(builder->buildEngineWithConfig(*network, *config)); 

My code is from AutowareArchitectureProposal.iv/perception/object_recognition/detection/tensorrt_yolo at ros2 · tier4/AutowareArchitectureProposal.iv · GitHub. It is a ros package but parts for TRT is pretty isolated from ROS. The onnx i use is also here.

Hi @orcdnz,

We recommend you to share complete error logs. Please try trtexec and share us verbose logs for better debugging.
Also please share environment details you’re using.
TensorRT Version :
GPU Type :
Nvidia Driver Version :
CUDA Version :
CUDNN Version :
Operating System + Version :
Python Version (if applicable) :
TensorFlow Version (if applicable) :
PyTorch Version (if applicable) :
Baremetal or Container (if container which image + tag) :

For your reference,

Thank you.

Trtexec manages to run model succesfully with ./trtexec --onnx=yolov3.onnx command.

TRT Version: 7.0.0.11
GPU Type: RTX 2070 Mobile
Nvidia Driver: 450.119.03
CUDA: 10
CUDNN: 7.6.5

@orcdnz, looks like you’ve not shared error logs. We request you to please share error logs for better assistance.

Thank you.

There is no log about the error. However whole output to terminal is as below.

ImporterContext.hpp:97: Registering tensor: 091_convolutional for ONNX tensor: 091_convolutional
ModelImporter.cpp:180: 091_convolutional [Conv] outputs: [091_convolutional -> (1, 512, 38, 38)], 
ModelImporter.cpp:107: Parsing node: 091_convolutional_bn [BatchNormalization]
ModelImporter.cpp:123: Searching for input: 091_convolutional
ModelImporter.cpp:123: Searching for input: 091_convolutional_bn_scale
ModelImporter.cpp:123: Searching for input: 091_convolutional_bn_bias
ModelImporter.cpp:123: Searching for input: 091_convolutional_bn_mean
ModelImporter.cpp:123: Searching for input: 091_convolutional_bn_var
ModelImporter.cpp:129: 091_convolutional_bn [BatchNormalization] inputs: [091_convolutional -> (1, 512, 38, 38)], [091_convolutional_bn_scale -> (512)], [091_convolutional_bn_bias -> (512)], [091_convolutional_bn_mean -> (512)], [091_convolutional_bn_var -> (512)], 
ImporterContext.hpp:122: Registering layer: 091_convolutional_bn for ONNX node: 091_convolutional_bn
ImporterContext.hpp:97: Registering tensor: 091_convolutional_bn for ONNX tensor: 091_convolutional_bn
ModelImporter.cpp:180: 091_convolutional_bn [BatchNormalization] outputs: [091_convolutional_bn -> (1, 512, 38, 38)], 
ModelImporter.cpp:107: Parsing node: 091_convolutional_lrelu [LeakyRelu]
ModelImporter.cpp:123: Searching for input: 091_convolutional_bn
ModelImporter.cpp:129: 091_convolutional_lrelu [LeakyRelu] inputs: [091_convolutional_bn -> (1, 512, 38, 38)], 
ImporterContext.hpp:122: Registering layer: 091_convolutional_lrelu for ONNX node: 091_convolutional_lrelu
ImporterContext.hpp:97: Registering tensor: 091_convolutional_lrelu for ONNX tensor: 091_convolutional_lrelu
ModelImporter.cpp:180: 091_convolutional_lrelu [LeakyRelu] outputs: [091_convolutional_lrelu -> (1, 512, 38, 38)], 
ModelImporter.cpp:107: Parsing node: 092_convolutional [Conv]
ModelImporter.cpp:123: Searching for input: 091_convolutional_lrelu
ModelImporter.cpp:123: Searching for input: 092_convolutional_conv_weights
ModelImporter.cpp:129: 092_convolutional [Conv] inputs: [091_convolutional_lrelu -> (1, 512, 38, 38)], [092_convolutional_conv_weights -> (256, 512, 1, 1)], 
builtin_op_importers.cpp:442: Convolution input dimensions: (1, 512, 38, 38)
Bias weights are not set yet. Bias weights can be set using setInput(2, bias_tensor) API call.
builtin_op_importers.cpp:524: Using kernel: (1, 1), strides: (1, 1), padding: (0, 0), dilations: (1, 1), numOutputs: 256
builtin_op_importers.cpp:525: Convolution output dimensions: (1, 256, 38, 38)
ImporterContext.hpp:122: Registering layer: 092_convolutional for ONNX node: 092_convolutional
ImporterContext.hpp:97: Registering tensor: 092_convolutional for ONNX tensor: 092_convolutional
ModelImporter.cpp:180: 092_convolutional [Conv] outputs: [092_convolutional -> (1, 256, 38, 38)], 
ModelImporter.cpp:107: Parsing node: 092_convolutional_bn [BatchNormalization]
ModelImporter.cpp:123: Searching for input: 092_convolutional
ModelImporter.cpp:123: Searching for input: 092_convolutional_bn_scale
ModelImporter.cpp:123: Searching for input: 092_convolutional_bn_bias
ModelImporter.cpp:123: Searching for input: 092_convolutional_bn_mean
ModelImporter.cpp:123: Searching for input: 092_convolutional_bn_var
ModelImporter.cpp:129: 092_convolutional_bn [BatchNormalization] inputs: [092_convolutional -> (1, 256, 38, 38)], [092_convolutional_bn_scale -> (256)], [092_convolutional_bn_bias -> (256)], [092_convolutional_bn_mean -> (256)], [092_convolutional_bn_var -> (256)], 
ImporterContext.hpp:122: Registering layer: 092_convolutional_bn for ONNX node: 092_convolutional_bn
ImporterContext.hpp:97: Registering tensor: 092_convolutional_bn for ONNX tensor: 092_convolutional_bn
ModelImporter.cpp:180: 092_convolutional_bn [BatchNormalization] outputs: [092_convolutional_bn -> (1, 256, 38, 38)], 
ModelImporter.cpp:107: Parsing node: 092_convolutional_lrelu [LeakyRelu]
ModelImporter.cpp:123: Searching for input: 092_convolutional_bn
ModelImporter.cpp:129: 092_convolutional_lrelu [LeakyRelu] inputs: [092_convolutional_bn -> (1, 256, 38, 38)], 
ImporterContext.hpp:122: Registering layer: 092_convolutional_lrelu for ONNX node: 092_convolutional_lrelu
ImporterContext.hpp:97: Registering tensor: 092_convolutional_lrelu for ONNX tensor: 092_convolutional_lrelu
ModelImporter.cpp:180: 092_convolutional_lrelu [LeakyRelu] outputs: [092_convolutional_lrelu -> (1, 256, 38, 38)], 
ModelImporter.cpp:107: Parsing node: 093_convolutional [Conv]
ModelImporter.cpp:123: Searching for input: 092_convolutional_lrelu
ModelImporter.cpp:123: Searching for input: 093_convolutional_conv_weights
ModelImporter.cpp:129: 093_convolutional [Conv] inputs: [092_convolutional_lrelu -> (1, 256, 38, 38)], [093_convolutional_conv_weights -> (512, 256, 3, 3)], 
builtin_op_importers.cpp:442: Convolution input dimensions: (1, 256, 38, 38)
Bias weights are not set yet. Bias weights can be set using setInput(2, bias_tensor) API call.
builtin_op_importers.cpp:524: Using kernel: (3, 3), strides: (1, 1), padding: (0, 0), dilations: (1, 1), numOutputs: 512
builtin_op_importers.cpp:525: Convolution output dimensions: (1, 512, 38, 38)
ImporterContext.hpp:122: Registering layer: 093_convolutional for ONNX node: 093_convolutional
ImporterContext.hpp:97: Registering tensor: 093_convolutional for ONNX tensor: 093_convolutional
ModelImporter.cpp:180: 093_convolutional [Conv] outputs: [093_convolutional -> (1, 512, 38, 38)], 
ModelImporter.cpp:107: Parsing node: 093_convolutional_bn [BatchNormalization]
ModelImporter.cpp:123: Searching for input: 093_convolutional
ModelImporter.cpp:123: Searching for input: 093_convolutional_bn_scale
ModelImporter.cpp:123: Searching for input: 093_convolutional_bn_bias
ModelImporter.cpp:123: Searching for input: 093_convolutional_bn_mean
ModelImporter.cpp:123: Searching for input: 093_convolutional_bn_var
ModelImporter.cpp:129: 093_convolutional_bn [BatchNormalization] inputs: [093_convolutional -> (1, 512, 38, 38)], [093_convolutional_bn_scale -> (512)], [093_convolutional_bn_bias -> (512)], [093_convolutional_bn_mean -> (512)], [093_convolutional_bn_var -> (512)], 
ImporterContext.hpp:122: Registering layer: 093_convolutional_bn for ONNX node: 093_convolutional_bn
ImporterContext.hpp:97: Registering tensor: 093_convolutional_bn for ONNX tensor: 093_convolutional_bn
ModelImporter.cpp:180: 093_convolutional_bn [BatchNormalization] outputs: [093_convolutional_bn -> (1, 512, 38, 38)], 
ModelImporter.cpp:107: Parsing node: 093_convolutional_lrelu [LeakyRelu]
ModelImporter.cpp:123: Searching for input: 093_convolutional_bn
ModelImporter.cpp:129: 093_convolutional_lrelu [LeakyRelu] inputs: [093_convolutional_bn -> (1, 512, 38, 38)], 
ImporterContext.hpp:122: Registering layer: 093_convolutional_lrelu for ONNX node: 093_convolutional_lrelu
ImporterContext.hpp:97: Registering tensor: 093_convolutional_lrelu for ONNX tensor: 093_convolutional_lrelu
ModelImporter.cpp:180: 093_convolutional_lrelu [LeakyRelu] outputs: [093_convolutional_lrelu -> (1, 512, 38, 38)], 
ModelImporter.cpp:107: Parsing node: 094_convolutional [Conv]
ModelImporter.cpp:123: Searching for input: 093_convolutional_lrelu
ModelImporter.cpp:123: Searching for input: 094_convolutional_conv_weights
ModelImporter.cpp:123: Searching for input: 094_convolutional_conv_bias
ModelImporter.cpp:129: 094_convolutional [Conv] inputs: [093_convolutional_lrelu -> (1, 512, 38, 38)], [094_convolutional_conv_weights -> (255, 512, 1, 1)], [094_convolutional_conv_bias -> (255)], 
builtin_op_importers.cpp:442: Convolution input dimensions: (1, 512, 38, 38)
builtin_op_importers.cpp:524: Using kernel: (1, 1), strides: (1, 1), padding: (0, 0), dilations: (1, 1), numOutputs: 255
builtin_op_importers.cpp:525: Convolution output dimensions: (1, 255, 38, 38)
ImporterContext.hpp:122: Registering layer: 094_convolutional for ONNX node: 094_convolutional
ImporterContext.hpp:97: Registering tensor: 094_convolutional_1 for ONNX tensor: 094_convolutional
ModelImporter.cpp:180: 094_convolutional [Conv] outputs: [094_convolutional -> (1, 255, 38, 38)], 
ModelImporter.cpp:107: Parsing node: 097_convolutional [Conv]
ModelImporter.cpp:123: Searching for input: 092_convolutional_lrelu
ModelImporter.cpp:123: Searching for input: 097_convolutional_conv_weights
ModelImporter.cpp:129: 097_convolutional [Conv] inputs: [092_convolutional_lrelu -> (1, 256, 38, 38)], [097_convolutional_conv_weights -> (128, 256, 1, 1)], 
builtin_op_importers.cpp:442: Convolution input dimensions: (1, 256, 38, 38)
Bias weights are not set yet. Bias weights can be set using setInput(2, bias_tensor) API call.
builtin_op_importers.cpp:524: Using kernel: (1, 1), strides: (1, 1), padding: (0, 0), dilations: (1, 1), numOutputs: 128
builtin_op_importers.cpp:525: Convolution output dimensions: (1, 128, 38, 38)
ImporterContext.hpp:122: Registering layer: 097_convolutional for ONNX node: 097_convolutional
ImporterContext.hpp:97: Registering tensor: 097_convolutional for ONNX tensor: 097_convolutional
ModelImporter.cpp:180: 097_convolutional [Conv] outputs: [097_convolutional -> (1, 128, 38, 38)], 
ModelImporter.cpp:107: Parsing node: 097_convolutional_bn [BatchNormalization]
ModelImporter.cpp:123: Searching for input: 097_convolutional
ModelImporter.cpp:123: Searching for input: 097_convolutional_bn_scale
ModelImporter.cpp:123: Searching for input: 097_convolutional_bn_bias
ModelImporter.cpp:123: Searching for input: 097_convolutional_bn_mean
ModelImporter.cpp:123: Searching for input: 097_convolutional_bn_var
ModelImporter.cpp:129: 097_convolutional_bn [BatchNormalization] inputs: [097_convolutional -> (1, 128, 38, 38)], [097_convolutional_bn_scale -> (128)], [097_convolutional_bn_bias -> (128)], [097_convolutional_bn_mean -> (128)], [097_convolutional_bn_var -> (128)], 
ImporterContext.hpp:122: Registering layer: 097_convolutional_bn for ONNX node: 097_convolutional_bn
ImporterContext.hpp:97: Registering tensor: 097_convolutional_bn for ONNX tensor: 097_convolutional_bn
ModelImporter.cpp:180: 097_convolutional_bn [BatchNormalization] outputs: [097_convolutional_bn -> (1, 128, 38, 38)], 
ModelImporter.cpp:107: Parsing node: 097_convolutional_lrelu [LeakyRelu]
ModelImporter.cpp:123: Searching for input: 097_convolutional_bn
ModelImporter.cpp:129: 097_convolutional_lrelu [LeakyRelu] inputs: [097_convolutional_bn -> (1, 128, 38, 38)], 
ImporterContext.hpp:122: Registering layer: 097_convolutional_lrelu for ONNX node: 097_convolutional_lrelu
ImporterContext.hpp:97: Registering tensor: 097_convolutional_lrelu for ONNX tensor: 097_convolutional_lrelu
ModelImporter.cpp:180: 097_convolutional_lrelu [LeakyRelu] outputs: [097_convolutional_lrelu -> (1, 128, 38, 38)], 
ModelImporter.cpp:107: Parsing node: 098_upsample [Resize]
ModelImporter.cpp:123: Searching for input: 097_convolutional_lrelu
ModelImporter.cpp:123: Searching for input: 098_upsample_roi
ModelImporter.cpp:123: Searching for input: 098_upsample_scale
ModelImporter.cpp:129: 098_upsample [Resize] inputs: [097_convolutional_lrelu -> (1, 128, 38, 38)], [098_upsample_roi -> (4)], [098_upsample_scale -> (4)], 
ImporterContext.hpp:122: Registering layer: 098_upsample for ONNX node: 098_upsample
ImporterContext.hpp:97: Registering tensor: 098_upsample for ONNX tensor: 098_upsample
ModelImporter.cpp:180: 098_upsample [Resize] outputs: [098_upsample -> (1, 128, 76, 76)], 
ModelImporter.cpp:107: Parsing node: 099_route [Concat]
ModelImporter.cpp:123: Searching for input: 098_upsample
ModelImporter.cpp:123: Searching for input: 037_shortcut
ModelImporter.cpp:129: 099_route [Concat] inputs: [098_upsample -> (1, 128, 76, 76)], [037_shortcut -> (1, 256, 76, 76)], 
ImporterContext.hpp:122: Registering layer: 099_route for ONNX node: 099_route
ImporterContext.hpp:97: Registering tensor: 099_route for ONNX tensor: 099_route
ModelImporter.cpp:180: 099_route [Concat] outputs: [099_route -> (1, 384, 76, 76)], 
ModelImporter.cpp:107: Parsing node: 100_convolutional [Conv]
ModelImporter.cpp:123: Searching for input: 099_route
ModelImporter.cpp:123: Searching for input: 100_convolutional_conv_weights
ModelImporter.cpp:129: 100_convolutional [Conv] inputs: [099_route -> (1, 384, 76, 76)], [100_convolutional_conv_weights -> (128, 384, 1, 1)], 
builtin_op_importers.cpp:442: Convolution input dimensions: (1, 384, 76, 76)
Bias weights are not set yet. Bias weights can be set using setInput(2, bias_tensor) API call.
builtin_op_importers.cpp:524: Using kernel: (1, 1), strides: (1, 1), padding: (0, 0), dilations: (1, 1), numOutputs: 128
builtin_op_importers.cpp:525: Convolution output dimensions: (1, 128, 76, 76)
ImporterContext.hpp:122: Registering layer: 100_convolutional for ONNX node: 100_convolutional
ImporterContext.hpp:97: Registering tensor: 100_convolutional for ONNX tensor: 100_convolutional
ModelImporter.cpp:180: 100_convolutional [Conv] outputs: [100_convolutional -> (1, 128, 76, 76)], 
ModelImporter.cpp:107: Parsing node: 100_convolutional_bn [BatchNormalization]
ModelImporter.cpp:123: Searching for input: 100_convolutional
ModelImporter.cpp:123: Searching for input: 100_convolutional_bn_scale
ModelImporter.cpp:123: Searching for input: 100_convolutional_bn_bias
ModelImporter.cpp:123: Searching for input: 100_convolutional_bn_mean
ModelImporter.cpp:123: Searching for input: 100_convolutional_bn_var
ModelImporter.cpp:129: 100_convolutional_bn [BatchNormalization] inputs: [100_convolutional -> (1, 128, 76, 76)], [100_convolutional_bn_scale -> (128)], [100_convolutional_bn_bias -> (128)], [100_convolutional_bn_mean -> (128)], [100_convolutional_bn_var -> (128)], 
ImporterContext.hpp:122: Registering layer: 100_convolutional_bn for ONNX node: 100_convolutional_bn
ImporterContext.hpp:97: Registering tensor: 100_convolutional_bn for ONNX tensor: 100_convolutional_bn
ModelImporter.cpp:180: 100_convolutional_bn [BatchNormalization] outputs: [100_convolutional_bn -> (1, 128, 76, 76)], 
ModelImporter.cpp:107: Parsing node: 100_convolutional_lrelu [LeakyRelu]
ModelImporter.cpp:123: Searching for input: 100_convolutional_bn
ModelImporter.cpp:129: 100_convolutional_lrelu [LeakyRelu] inputs: [100_convolutional_bn -> (1, 128, 76, 76)], 
ImporterContext.hpp:122: Registering layer: 100_convolutional_lrelu for ONNX node: 100_convolutional_lrelu
ImporterContext.hpp:97: Registering tensor: 100_convolutional_lrelu for ONNX tensor: 100_convolutional_lrelu
ModelImporter.cpp:180: 100_convolutional_lrelu [LeakyRelu] outputs: [100_convolutional_lrelu -> (1, 128, 76, 76)], 
ModelImporter.cpp:107: Parsing node: 101_convolutional [Conv]
ModelImporter.cpp:123: Searching for input: 100_convolutional_lrelu
ModelImporter.cpp:123: Searching for input: 101_convolutional_conv_weights
ModelImporter.cpp:129: 101_convolutional [Conv] inputs: [100_convolutional_lrelu -> (1, 128, 76, 76)], [101_convolutional_conv_weights -> (256, 128, 3, 3)], 
builtin_op_importers.cpp:442: Convolution input dimensions: (1, 128, 76, 76)
Bias weights are not set yet. Bias weights can be set using setInput(2, bias_tensor) API call.
builtin_op_importers.cpp:524: Using kernel: (3, 3), strides: (1, 1), padding: (0, 0), dilations: (1, 1), numOutputs: 256
builtin_op_importers.cpp:525: Convolution output dimensions: (1, 256, 76, 76)
ImporterContext.hpp:122: Registering layer: 101_convolutional for ONNX node: 101_convolutional
ImporterContext.hpp:97: Registering tensor: 101_convolutional for ONNX tensor: 101_convolutional
ModelImporter.cpp:180: 101_convolutional [Conv] outputs: [101_convolutional -> (1, 256, 76, 76)], 
ModelImporter.cpp:107: Parsing node: 101_convolutional_bn [BatchNormalization]
ModelImporter.cpp:123: Searching for input: 101_convolutional
ModelImporter.cpp:123: Searching for input: 101_convolutional_bn_scale
ModelImporter.cpp:123: Searching for input: 101_convolutional_bn_bias
ModelImporter.cpp:123: Searching for input: 101_convolutional_bn_mean
ModelImporter.cpp:123: Searching for input: 101_convolutional_bn_var
ModelImporter.cpp:129: 101_convolutional_bn [BatchNormalization] inputs: [101_convolutional -> (1, 256, 76, 76)], [101_convolutional_bn_scale -> (256)], [101_convolutional_bn_bias -> (256)], [101_convolutional_bn_mean -> (256)], [101_convolutional_bn_var -> (256)], 
ImporterContext.hpp:122: Registering layer: 101_convolutional_bn for ONNX node: 101_convolutional_bn
ImporterContext.hpp:97: Registering tensor: 101_convolutional_bn for ONNX tensor: 101_convolutional_bn
ModelImporter.cpp:180: 101_convolutional_bn [BatchNormalization] outputs: [101_convolutional_bn -> (1, 256, 76, 76)], 
ModelImporter.cpp:107: Parsing node: 101_convolutional_lrelu [LeakyRelu]
ModelImporter.cpp:123: Searching for input: 101_convolutional_bn
ModelImporter.cpp:129: 101_convolutional_lrelu [LeakyRelu] inputs: [101_convolutional_bn -> (1, 256, 76, 76)], 
ImporterContext.hpp:122: Registering layer: 101_convolutional_lrelu for ONNX node: 101_convolutional_lrelu
ImporterContext.hpp:97: Registering tensor: 101_convolutional_lrelu for ONNX tensor: 101_convolutional_lrelu
ModelImporter.cpp:180: 101_convolutional_lrelu [LeakyRelu] outputs: [101_convolutional_lrelu -> (1, 256, 76, 76)], 
ModelImporter.cpp:107: Parsing node: 102_convolutional [Conv]
ModelImporter.cpp:123: Searching for input: 101_convolutional_lrelu
ModelImporter.cpp:123: Searching for input: 102_convolutional_conv_weights
ModelImporter.cpp:129: 102_convolutional [Conv] inputs: [101_convolutional_lrelu -> (1, 256, 76, 76)], [102_convolutional_conv_weights -> (128, 256, 1, 1)], 
builtin_op_importers.cpp:442: Convolution input dimensions: (1, 256, 76, 76)
Bias weights are not set yet. Bias weights can be set using setInput(2, bias_tensor) API call.
builtin_op_importers.cpp:524: Using kernel: (1, 1), strides: (1, 1), padding: (0, 0), dilations: (1, 1), numOutputs: 128
builtin_op_importers.cpp:525: Convolution output dimensions: (1, 128, 76, 76)
ImporterContext.hpp:122: Registering layer: 102_convolutional for ONNX node: 102_convolutional
ImporterContext.hpp:97: Registering tensor: 102_convolutional for ONNX tensor: 102_convolutional
ModelImporter.cpp:180: 102_convolutional [Conv] outputs: [102_convolutional -> (1, 128, 76, 76)], 
ModelImporter.cpp:107: Parsing node: 102_convolutional_bn [BatchNormalization]
ModelImporter.cpp:123: Searching for input: 102_convolutional
ModelImporter.cpp:123: Searching for input: 102_convolutional_bn_scale
ModelImporter.cpp:123: Searching for input: 102_convolutional_bn_bias
ModelImporter.cpp:123: Searching for input: 102_convolutional_bn_mean
ModelImporter.cpp:123: Searching for input: 102_convolutional_bn_var
ModelImporter.cpp:129: 102_convolutional_bn [BatchNormalization] inputs: [102_convolutional -> (1, 128, 76, 76)], [102_convolutional_bn_scale -> (128)], [102_convolutional_bn_bias -> (128)], [102_convolutional_bn_mean -> (128)], [102_convolutional_bn_var -> (128)], 
ImporterContext.hpp:122: Registering layer: 102_convolutional_bn for ONNX node: 102_convolutional_bn
ImporterContext.hpp:97: Registering tensor: 102_convolutional_bn for ONNX tensor: 102_convolutional_bn
ModelImporter.cpp:180: 102_convolutional_bn [BatchNormalization] outputs: [102_convolutional_bn -> (1, 128, 76, 76)], 
ModelImporter.cpp:107: Parsing node: 102_convolutional_lrelu [LeakyRelu]
ModelImporter.cpp:123: Searching for input: 102_convolutional_bn
ModelImporter.cpp:129: 102_convolutional_lrelu [LeakyRelu] inputs: [102_convolutional_bn -> (1, 128, 76, 76)], 
ImporterContext.hpp:122: Registering layer: 102_convolutional_lrelu for ONNX node: 102_convolutional_lrelu
ImporterContext.hpp:97: Registering tensor: 102_convolutional_lrelu for ONNX tensor: 102_convolutional_lrelu
ModelImporter.cpp:180: 102_convolutional_lrelu [LeakyRelu] outputs: [102_convolutional_lrelu -> (1, 128, 76, 76)], 
ModelImporter.cpp:107: Parsing node: 103_convolutional [Conv]
ModelImporter.cpp:123: Searching for input: 102_convolutional_lrelu
ModelImporter.cpp:123: Searching for input: 103_convolutional_conv_weights
ModelImporter.cpp:129: 103_convolutional [Conv] inputs: [102_convolutional_lrelu -> (1, 128, 76, 76)], [103_convolutional_conv_weights -> (256, 128, 3, 3)], 
builtin_op_importers.cpp:442: Convolution input dimensions: (1, 128, 76, 76)
Bias weights are not set yet. Bias weights can be set using setInput(2, bias_tensor) API call.
builtin_op_importers.cpp:524: Using kernel: (3, 3), strides: (1, 1), padding: (0, 0), dilations: (1, 1), numOutputs: 256
builtin_op_importers.cpp:525: Convolution output dimensions: (1, 256, 76, 76)
ImporterContext.hpp:122: Registering layer: 103_convolutional for ONNX node: 103_convolutional
ImporterContext.hpp:97: Registering tensor: 103_convolutional for ONNX tensor: 103_convolutional
ModelImporter.cpp:180: 103_convolutional [Conv] outputs: [103_convolutional -> (1, 256, 76, 76)], 
ModelImporter.cpp:107: Parsing node: 103_convolutional_bn [BatchNormalization]
ModelImporter.cpp:123: Searching for input: 103_convolutional
ModelImporter.cpp:123: Searching for input: 103_convolutional_bn_scale
ModelImporter.cpp:123: Searching for input: 103_convolutional_bn_bias
ModelImporter.cpp:123: Searching for input: 103_convolutional_bn_mean
ModelImporter.cpp:123: Searching for input: 103_convolutional_bn_var
ModelImporter.cpp:129: 103_convolutional_bn [BatchNormalization] inputs: [103_convolutional -> (1, 256, 76, 76)], [103_convolutional_bn_scale -> (256)], [103_convolutional_bn_bias -> (256)], [103_convolutional_bn_mean -> (256)], [103_convolutional_bn_var -> (256)], 
ImporterContext.hpp:122: Registering layer: 103_convolutional_bn for ONNX node: 103_convolutional_bn
ImporterContext.hpp:97: Registering tensor: 103_convolutional_bn for ONNX tensor: 103_convolutional_bn
ModelImporter.cpp:180: 103_convolutional_bn [BatchNormalization] outputs: [103_convolutional_bn -> (1, 256, 76, 76)], 
ModelImporter.cpp:107: Parsing node: 103_convolutional_lrelu [LeakyRelu]
ModelImporter.cpp:123: Searching for input: 103_convolutional_bn
ModelImporter.cpp:129: 103_convolutional_lrelu [LeakyRelu] inputs: [103_convolutional_bn -> (1, 256, 76, 76)], 
ImporterContext.hpp:122: Registering layer: 103_convolutional_lrelu for ONNX node: 103_convolutional_lrelu
ImporterContext.hpp:97: Registering tensor: 103_convolutional_lrelu for ONNX tensor: 103_convolutional_lrelu
ModelImporter.cpp:180: 103_convolutional_lrelu [LeakyRelu] outputs: [103_convolutional_lrelu -> (1, 256, 76, 76)], 
ModelImporter.cpp:107: Parsing node: 104_convolutional [Conv]
ModelImporter.cpp:123: Searching for input: 103_convolutional_lrelu
ModelImporter.cpp:123: Searching for input: 104_convolutional_conv_weights
ModelImporter.cpp:129: 104_convolutional [Conv] inputs: [103_convolutional_lrelu -> (1, 256, 76, 76)], [104_convolutional_conv_weights -> (128, 256, 1, 1)], 
builtin_op_importers.cpp:442: Convolution input dimensions: (1, 256, 76, 76)
Bias weights are not set yet. Bias weights can be set using setInput(2, bias_tensor) API call.
builtin_op_importers.cpp:524: Using kernel: (1, 1), strides: (1, 1), padding: (0, 0), dilations: (1, 1), numOutputs: 128
builtin_op_importers.cpp:525: Convolution output dimensions: (1, 128, 76, 76)
ImporterContext.hpp:122: Registering layer: 104_convolutional for ONNX node: 104_convolutional
ImporterContext.hpp:97: Registering tensor: 104_convolutional for ONNX tensor: 104_convolutional
ModelImporter.cpp:180: 104_convolutional [Conv] outputs: [104_convolutional -> (1, 128, 76, 76)], 
ModelImporter.cpp:107: Parsing node: 104_convolutional_bn [BatchNormalization]
ModelImporter.cpp:123: Searching for input: 104_convolutional
ModelImporter.cpp:123: Searching for input: 104_convolutional_bn_scale
ModelImporter.cpp:123: Searching for input: 104_convolutional_bn_bias
ModelImporter.cpp:123: Searching for input: 104_convolutional_bn_mean
ModelImporter.cpp:123: Searching for input: 104_convolutional_bn_var
ModelImporter.cpp:129: 104_convolutional_bn [BatchNormalization] inputs: [104_convolutional -> (1, 128, 76, 76)], [104_convolutional_bn_scale -> (128)], [104_convolutional_bn_bias -> (128)], [104_convolutional_bn_mean -> (128)], [104_convolutional_bn_var -> (128)], 
ImporterContext.hpp:122: Registering layer: 104_convolutional_bn for ONNX node: 104_convolutional_bn
ImporterContext.hpp:97: Registering tensor: 104_convolutional_bn for ONNX tensor: 104_convolutional_bn
ModelImporter.cpp:180: 104_convolutional_bn [BatchNormalization] outputs: [104_convolutional_bn -> (1, 128, 76, 76)], 
ModelImporter.cpp:107: Parsing node: 104_convolutional_lrelu [LeakyRelu]
ModelImporter.cpp:123: Searching for input: 104_convolutional_bn
ModelImporter.cpp:129: 104_convolutional_lrelu [LeakyRelu] inputs: [104_convolutional_bn -> (1, 128, 76, 76)], 
ImporterContext.hpp:122: Registering layer: 104_convolutional_lrelu for ONNX node: 104_convolutional_lrelu
ImporterContext.hpp:97: Registering tensor: 104_convolutional_lrelu for ONNX tensor: 104_convolutional_lrelu
ModelImporter.cpp:180: 104_convolutional_lrelu [LeakyRelu] outputs: [104_convolutional_lrelu -> (1, 128, 76, 76)], 
ModelImporter.cpp:107: Parsing node: 105_convolutional [Conv]
ModelImporter.cpp:123: Searching for input: 104_convolutional_lrelu
ModelImporter.cpp:123: Searching for input: 105_convolutional_conv_weights
ModelImporter.cpp:129: 105_convolutional [Conv] inputs: [104_convolutional_lrelu -> (1, 128, 76, 76)], [105_convolutional_conv_weights -> (256, 128, 3, 3)], 
builtin_op_importers.cpp:442: Convolution input dimensions: (1, 128, 76, 76)
Bias weights are not set yet. Bias weights can be set using setInput(2, bias_tensor) API call.
builtin_op_importers.cpp:524: Using kernel: (3, 3), strides: (1, 1), padding: (0, 0), dilations: (1, 1), numOutputs: 256
builtin_op_importers.cpp:525: Convolution output dimensions: (1, 256, 76, 76)
ImporterContext.hpp:122: Registering layer: 105_convolutional for ONNX node: 105_convolutional
ImporterContext.hpp:97: Registering tensor: 105_convolutional for ONNX tensor: 105_convolutional
ModelImporter.cpp:180: 105_convolutional [Conv] outputs: [105_convolutional -> (1, 256, 76, 76)], 
ModelImporter.cpp:107: Parsing node: 105_convolutional_bn [BatchNormalization]
ModelImporter.cpp:123: Searching for input: 105_convolutional
ModelImporter.cpp:123: Searching for input: 105_convolutional_bn_scale
ModelImporter.cpp:123: Searching for input: 105_convolutional_bn_bias
ModelImporter.cpp:123: Searching for input: 105_convolutional_bn_mean
ModelImporter.cpp:123: Searching for input: 105_convolutional_bn_var
ModelImporter.cpp:129: 105_convolutional_bn [BatchNormalization] inputs: [105_convolutional -> (1, 256, 76, 76)], [105_convolutional_bn_scale -> (256)], [105_convolutional_bn_bias -> (256)], [105_convolutional_bn_mean -> (256)], [105_convolutional_bn_var -> (256)], 
ImporterContext.hpp:122: Registering layer: 105_convolutional_bn for ONNX node: 105_convolutional_bn
ImporterContext.hpp:97: Registering tensor: 105_convolutional_bn for ONNX tensor: 105_convolutional_bn
ModelImporter.cpp:180: 105_convolutional_bn [BatchNormalization] outputs: [105_convolutional_bn -> (1, 256, 76, 76)], 
ModelImporter.cpp:107: Parsing node: 105_convolutional_lrelu [LeakyRelu]
ModelImporter.cpp:123: Searching for input: 105_convolutional_bn
ModelImporter.cpp:129: 105_convolutional_lrelu [LeakyRelu] inputs: [105_convolutional_bn -> (1, 256, 76, 76)], 
ImporterContext.hpp:122: Registering layer: 105_convolutional_lrelu for ONNX node: 105_convolutional_lrelu
ImporterContext.hpp:97: Registering tensor: 105_convolutional_lrelu for ONNX tensor: 105_convolutional_lrelu
ModelImporter.cpp:180: 105_convolutional_lrelu [LeakyRelu] outputs: [105_convolutional_lrelu -> (1, 256, 76, 76)], 
ModelImporter.cpp:107: Parsing node: 106_convolutional [Conv]
ModelImporter.cpp:123: Searching for input: 105_convolutional_lrelu
ModelImporter.cpp:123: Searching for input: 106_convolutional_conv_weights
ModelImporter.cpp:123: Searching for input: 106_convolutional_conv_bias
ModelImporter.cpp:129: 106_convolutional [Conv] inputs: [105_convolutional_lrelu -> (1, 256, 76, 76)], [106_convolutional_conv_weights -> (255, 256, 1, 1)], [106_convolutional_conv_bias -> (255)], 
builtin_op_importers.cpp:442: Convolution input dimensions: (1, 256, 76, 76)
builtin_op_importers.cpp:524: Using kernel: (1, 1), strides: (1, 1), padding: (0, 0), dilations: (1, 1), numOutputs: 255
builtin_op_importers.cpp:525: Convolution output dimensions: (1, 255, 76, 76)
ImporterContext.hpp:122: Registering layer: 106_convolutional for ONNX node: 106_convolutional
ImporterContext.hpp:97: Registering tensor: 106_convolutional_1 for ONNX tensor: 106_convolutional
ModelImporter.cpp:180: 106_convolutional [Conv] outputs: [106_convolutional -> (1, 255, 76, 76)], 
ModelImporter.cpp:494: Marking 082_convolutional_1 as output: 082_convolutional
ModelImporter.cpp:494: Marking 094_convolutional_1 as output: 094_convolutional
ModelImporter.cpp:494: Marking 106_convolutional_1 as output: 106_convolutional
 ----- Parsing of ONNX model /home/orcun/Main.Drive/src/perception/object_recognition/detection/tensorrt_yolo/data/yolov3.onnx is Done ---- 
Applying optimizations and building TRT CUDA engine...
Assertion failed: dims.d[i] >= 1
../builder/cudnnBuilderGraph.cpp:780
Aborting...

../builder/cudnnBuilderGraph.cpp (780) - Assertion Error in checkDimsSanity: 0 (dims.d[i] >= 1)

builder->buildEngineWithConfig does not log anyting even though it is using the same logger as networkParser and etc.

Hi @orcdnz.

We are unable to reproduce this error on TensorRT version 8.0.0 EA. We recommend you to please use latest version.

&&&& PASSED TensorRT.trtexec [TensorRT v8000] # trtexec --onnx=yolov3.onnx --verbose
[06/03/2021-17:17:18] [I] [TRT] [MemUsageChange] Init cuBLAS/cuBLASLt: CPU +0, GPU +0, now: CPU 1439, GPU 1366 (MiB)

Thank you.

Version 7.2.1.6 solved the problem.

1 Like