Hello, I am following https://github.com/midasklr/yolov5prune and trained yolov5s. After that I converted best.pt to best.onnx and also simplified best.onnx to best_sim.onnx.
Using ncnn ncnn2onnx I was able to convert best_sim.onnx. After replacing crop layers into YoloV5Focus layer, I used ncnnoptimize to clean up the ncnn.param and ncnn.bin files.
Problem is first few conv layers' w/b tensor values are uint8 as shown below figure (ncnn.param: first conv layers' weight tensor values are captured, also onnx tensor type says it is float16).

I did not add anything in conversion code. DEfault conversion should be float32 right?
So I dont know what the problem is.
here is part of original ncnn.param:

7767517
234 267
Input            images                   0 1 images
Split            splitncnn_input0         1 4 images images_splitncnn_0 images_splitncnn_1 images_splitncnn_2 images_splitncnn_3
MemoryData       1039                     0 1 1039
MemoryData       1045                     0 1 1045
MemoryData       1051                     0 1 1051
MemoryData       703                      0 1 703
MemoryData       764                      0 1 764
MemoryData       825                      0 1 825
Crop             Slice_4                  1 1 images_splitncnn_3 367 -23309=1,0 -23310=1,2147483647 -23311=1,1
Crop             Slice_9                  1 1 367 372 -23309=1,0 -23310=1,2147483647 -23311=1,2
Crop             Slice_14                 1 1 images_splitncnn_2 377 -23309=1,1 -23310=1,2147483647 -23311=1,1
Crop             Slice_19                 1 1 377 382 -23309=1,0 -23310=1,2147483647 -23311=1,2
Crop             Slice_24                 1 1 images_splitncnn_1 387 -23309=1,0 -23310=1,2147483647 -23311=1,1
Crop             Slice_29                 1 1 387 392 -23309=1,1 -23310=1,2147483647 -23311=1,2
Crop             Slice_34                 1 1 images_splitncnn_0 397 -23309=1,1 -23310=1,2147483647 -23311=1,1
Crop             Slice_39                 1 1 397 402 -23309=1,1 -23310=1,2147483647 -23311=1,2
Concat           Concat_40                4 1 372 382 392 402 403 0=0
Convolution      Conv_41                  1 1 403 857 0=32 1=3 11=3 2=1 12=1 3=1 13=1 4=1 14=1 15=1 16=1 5=1 6=3456

here is modified part of ncnn.param:

7767517
225 267
Input            images                   0 1 images
YoloV5Focus      focus                    1 1 images 403
MemoryData       1039                     0 1 1039
MemoryData       1045                     0 1 1045
MemoryData       1051                     0 1 1051
MemoryData       703                      0 1 703
MemoryData       764                      0 1 764
MemoryData       825                      0 1 825
Convolution      Conv_41                  1 1 403 857 0=32 1=3 11=3 2=1 12=1 3=1 13=1 4=1 14=1 15=1 16=1 5=1 6=3456

first 8 conv layers' tensor values are look like above and rest of conv layers' tensor values are normal float values.
Any idea what is the problem? thanks