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yolov5_tensorrt_int8's Issues

QAT量化

请问QAT量化部分的代码和train.py一样，是如何进行量化的呀

ptq 量化报错

I0312 11:07:43.887332 140542321780544 tensor_quantizer.py:180] Enable MaxCalibrator Enable MaxCalibrator I0312 11:07:43.887368 140542321780544 tensor_quantizer.py:184] Disable quantstage. Disablequantstage. I0312 11:07:43.887401 140542321780544 tensor_quantizer.py:180] Enable MaxCalibrator Enable MaxCalibrator I0312 11:07:43.887435 140542321780544 tensor_quantizer.py:184] Disablequantstage. Disablequantstage. I0312 11:07:43.887468 140542321780544 tensor_quantizer.py:180] Enable MaxCalibrator Enable MaxCalibrator I0312 11:07:43.887503 140542321780544 tensor_quantizer.py:184] Disablequantstage. Disablequantstage. I0312 11:07:43.887536 140542321780544 tensor_quantizer.py:180] Enable MaxCalibrator Enable MaxCalibrator I0312 11:07:43.887570 140542321780544 tensor_quantizer.py:184] Disablequantstage. Disablequantstage. I0312 11:07:43.887603 140542321780544 tensor_quantizer.py:180] Enable MaxCalibrator Enable MaxCalibrator I0312 11:07:43.887638 140542321780544 tensor_quantizer.py:184] Disablequantstage. Disablequantstage. I0312 11:07:43.887670 140542321780544 tensor_quantizer.py:180] Enable MaxCalibrator Enable MaxCalibrator I0312 11:07:43.887704 140542321780544 tensor_quantizer.py:184] Disablequantstage. Disablequantstage. I0312 11:07:43.887737 140542321780544 tensor_quantizer.py:180] Enable MaxCalibrator Enable MaxCalibrator 0it [00:00, ?it/s] Traceback (most recent call last): File "pytorch_yolov5_ptq.py", line 135, in <module> collect_stats(q_model, dataloader) File "pytorch_yolov5_ptq.py", line 51, in collect_stats for i, image in tqdm(enumerate(data_loader)): File "/root/anaconda3/envs/mjj_py377/lib/python3.7/site-packages/tqdm/std.py", line 1178, in __iter__ for obj in iterable: File "/root/anaconda3/envs/mjj_py377/lib/python3.7/site-packages/torch/utils/data/dataloader.py", line 521, in __next__ data = self._next_data() File "/root/anaconda3/envs/mjj_py377/lib/python3.7/site-packages/torch/utils/data/dataloader.py", line 561, in _next_data data = self._dataset_fetcher.fetch(index) # may raise StopIteration File "/root/anaconda3/envs/mjj_py377/lib/python3.7/site-packages/torch/utils/data/_utils/fetch.py", line 52, in fetch return self.collate_fn(data) File "/root/anaconda3/envs/mjj_py377/lib/python3.7/site-packages/torch/utils/data/_utils/collate.py", line 64, in default_collate return default_collate([torch.as_tensor(b) for b in batch]) File "/root/anaconda3/envs/mjj_py377/lib/python3.7/site-packages/torch/utils/data/_utils/collate.py", line 56, in default_collate return torch.stack(batch, 0, out=out) RuntimeError: stack expects each tensor to be equal size, but got [3, 426, 640] at entry 0 and [3, 640, 615] at entry 1
这个报错我太理解

Why does the nms operator you provide contain no logic code about nms？ 

def forward(
    ctx,
    boxes,
    scores,
    background_class=-1,
    box_coding=1,
    iou_threshold=0.45,
    max_output_boxes=100,
    plugin_version="1",
    score_activation=0,
    score_threshold=0.25,
):
    batch_size, num_boxes, num_classes = scores.shape
    num_det = torch.randint(0, max_output_boxes, (batch_size, 1), dtype=torch.int32)
    det_boxes = torch.randn(batch_size, max_output_boxes, 4)
    det_scores = torch.randn(batch_size, max_output_boxes)
    det_classes = torch.randint(0, num_classes, (batch_size, max_output_boxes), dtype=torch.int32)
    return num_det, det_boxes, det_scores, det_classes

Segmentation fault (core dumped)

使用官方 yolov5s.onnx
运行 python onnx2trt_ptq.py
出现
engine = builder.build_engine(network,config)
Segmentation fault (core dumped)
错误

qat量化无法启动

我安装了pytorch-quantization后，执行
python pytorch_yolov5_qat.py --weights yolov5s.pt --cfg models/yolov5s.yaml --data data/coco.yaml --img 640
会自动下载yolov5n.pt ， AMP check也没有通过。

我就改成了yolov5n.pt
python pytorch_yolov5_qat.py --weights yolov5n.pt --cfg models/yolov5n.yaml --data data/coco.yaml --img 640

AMP check 通过了，但是训练并没有开始，进度条不动。

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