I have trained yolov4 with resnet 18, then etlt file converted successfully, but when i tried to convert etlt to trt, i face error.
Code
!tlt-converter -k $KEY \
-d 3,240,320 \
-o BatchedNMS \
-e $USER_EXPERIMENT_DIR/export/trt.engine \
-m 4 \
-t fp32 \
-i nchw \
$USER_EXPERIMENT_DIR/export/yolov4_resnet18_epoch_$EPOCH.etlt
Error
[ERROR] encoded_bg/concat: all concat input tensors must have the same dimensions except on the concatenation axis (1), but dimensions mismatched at index 0. Input 0 shape: [210,6,1], Input 1 shape: [240,6,1]
[ERROR] encoded_bg/concat: all concat input tensors must have the same dimensions except on the concatenation axis (1), but dimensions mismatched at index 0. Input 0 shape: [210,6,1], Input 1 shape: [240,6,1]
[ERROR] encoded_bg/concat: all concat input tensors must have the same dimensions except on the concatenation axis (1), but dimensions mismatched at index 0. Input 0 shape: [210,6,1], Input 1 shape: [240,6,1]
[ERROR] encoded_bg/concat: all concat input tensors must have the same dimensions except on the concatenation axis (1), but dimensions mismatched at index 0. Input 0 shape: [210,6,1], Input 1 shape: [240,6,1]
[ERROR] encoded_bg/concat: all concat input tensors must have the same dimensions except on the concatenation axis (1), but dimensions mismatched at index 0. Input 0 shape: [210,6,1], Input 1 shape: [240,6,1]
[ERROR] encoded_bg/concat: all concat input tensors must have the same dimensions except on the concatenation axis (1), but dimensions mismatched at index 0. Input 0 shape: [210,6,1], Input 1 shape: [240,6,1]
[ERROR] encoded_bg/concat: all concat input tensors must have the same dimensions except on the concatenation axis (1), but dimensions mismatched at index 0. Input 0 shape: [210,6,1], Input 1 shape: [240,6,1]
[ERROR] encoded_bg/concat: all concat input tensors must have the same dimensions except on the concatenation axis (1), but dimensions mismatched at index 0. Input 0 shape: [210,6,1], Input 1 shape: [240,6,1]
[ERROR] encoded_bg/concat: all concat input tensors must have the same dimensions except on the concatenation axis (1), but dimensions mismatched at index 0. Input 0 shape: [210,6,1], Input 1 shape: [240,6,1]
[ERROR] UffParser: Parser error: yolo_conv2_bn/batchnorm/mul_1: The input to the Scale Layer is required to have a minimum of 3 dimensions.
[ERROR] Failed to parse the model, please check the encoding key to make sure it’s correct
[ERROR] Network must have at least one output
[ERROR] Network validation failed.
[ERROR] Unable to create engine
Segmentation fault (core dumped)
I know, from this we can say that key is incorrect, but i checked inference with that key, its working fine.