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Error in pip install -r requirements.txt

ERROR: Could not find a version that satisfies the requirement torch==1.7.0 (from versions: 0.1.2, 0.1.2.post1, 0.1.2.post2, 1.7.1, 1.8.0, 1.8.1, 1.9.0)
ERROR: No matching distribution found for torch==1.7.0

Error in python test.py --data data/coco.yaml --img 1280 --batch 32 --conf 0.001 --iou 0.65 --device 0 --cfg cfg/yolor_p6.cfg --weights yolor_p6.pt --name yolor_p6_val

Traceback (most recent call last):
  File "/home/satoharu/yolor/test.py", line 319, in <module>
    test(opt.data,
  File "/home/satoharu/yolor/test.py", line 226, in test
    plot_images(img, output_to_target(output, width, height), paths, f, names)  # predictions
  File "/home/satoharu/yolor/utils/plots.py", line 106, in output_to_target
    return np.array(targets)
  File "/home/satoharu/.pyenv/versions/3.9.6_yolor/lib/python3.9/site-packages/torch/_tensor.py", line 643, in __array__
    return self.numpy()
TypeError: can't convert cuda:0 device type tensor to numpy. Use Tensor.cpu() to copy the tensor to host memory first.

RuntimeError: CUDA out of memory. Tried to allocate 390.00 MiB (GPU 0; 10.76 GiB total capacity; 8.79 GiB already allocated; 323.44 MiB free; 9.10 GiB reserved in total by PyTorch)

ERROR: pycocotools unable to run: 'numpy.float64' object cannot be interpreted as an integer
Results saved to runs/test/yolor_p6_val11

pycocotoolsのバグで最新版で対応されていた。

ccumulating evaluation results...
DONE (t=8.95s).
 Average Precision  (AP) @[ IoU=0.50:0.95 | area=   all | maxDets=100 ] = 0.525
 Average Precision  (AP) @[ IoU=0.50      | area=   all | maxDets=100 ] = 0.707
 Average Precision  (AP) @[ IoU=0.75      | area=   all | maxDets=100 ] = 0.575
 Average Precision  (AP) @[ IoU=0.50:0.95 | area= small | maxDets=100 ] = 0.370
 Average Precision  (AP) @[ IoU=0.50:0.95 | area=medium | maxDets=100 ] = 0.569
 Average Precision  (AP) @[ IoU=0.50:0.95 | area= large | maxDets=100 ] = 0.660
 Average Recall     (AR) @[ IoU=0.50:0.95 | area=   all | maxDets=  1 ] = 0.392
 Average Recall     (AR) @[ IoU=0.50:0.95 | area=   all | maxDets= 10 ] = 0.652
 Average Recall     (AR) @[ IoU=0.50:0.95 | area=   all | maxDets=100 ] = 0.714
 Average Recall     (AR) @[ IoU=0.50:0.95 | area= small | maxDets=100 ] = 0.578
 Average Recall     (AR) @[ IoU=0.50:0.95 | area=medium | maxDets=100 ] = 0.753
 Average Recall     (AR) @[ IoU=0.50:0.95 | area= large | maxDets=100 ] = 0.839
Results saved to runs/test/yolor_p6_val16