Getting an error while evaluating pretrained models

[mehulshankhapal2000]

DLL 2022-09-01 18:12:47.545736 - PARAMETER dataset path : ./coco epochs : 65 batch size : 32 eval batch size : 32 no cuda : False seed : None checkpoint path : ./models/epoch_*.pt mode : evaluation eval on epochs : [21, 31, 37, 42, 48, 53, 59, 64] lr decay epochs : [43, 54] learning rate : 0.0026 momentum : 0.9 weight decay : 0.0005 lr warmup : None backbone : resnet50 backbone path : None num workers : 4 AMP : False precision : fp32 Using seed = 5073 loading annotations into memory... Done (t=0.46s) creating index... index created! /data4/home/mehuls/Project/DeepLearningExamples/PyTorch/Detection/SSD/ssd/coco_pipeline.py:248: Warning: Calling '.dtype()' is deprecated, please use '.dtype' instead images_torch_type = to_torch_type[np.dtype(images[0].dtype())] /data4/home/mehuls/Project/DeepLearningExamples/PyTorch/Detection/SSD/ssd/coco_pipeline.py:249: Warning: Calling '.dtype()' is deprecated, please use '.dtype' instead bboxes_torch_type = to_torch_type[np.dtype(bboxes[0][0].dtype())] /data4/home/mehuls/Project/DeepLearningExamples/PyTorch/Detection/SSD/ssd/coco_pipeline.py:250: Warning: Calling '.dtype()' is deprecated, please use '.dtype' instead labels_torch_type = to_torch_type[np.dtype(labels[0][0].dtype())] Provided checkpoint is not path to a file

### This was the output when I tried evaluating. Also I replace .dtype() with .dtype and it showed me following error.

DLL 2022-09-01 18:16:30.168690 - PARAMETER dataset path : ./coco epochs : 65 batch size : 32 eval batch size : 32 no cuda : False seed : None checkpoint path : ./models/epoch_*.pt mode : evaluation eval on epochs : [21, 31, 37, 42, 48, 53, 59, 64] lr decay epochs : [43, 54] learning rate : 0.0026 momentum : 0.9 weight decay : 0.0005 lr warmup : None backbone : resnet50 backbone path : None num workers : 4 AMP : False precision : fp32 Using seed = 396 loading annotations into memory... Done (t=0.43s) creating index... index created! Traceback (most recent call last): File "./main.py", line 286, in train(train_loop_func, logger, args) File "./main.py", line 148, in train train_loader = get_train_loader(args, args.seed - 2**31) File "/data4/home/mehuls/Project/DeepLearningExamples/PyTorch/Detection/SSD/ssd/data.py", line 42, in get_train_loader train_loader = DALICOCOIterator(train_pipe, 118287 / args.N_gpu) File "/data4/home/mehuls/Project/DeepLearningExamples/PyTorch/Detection/SSD/ssd/coco_pipeline.py", line 190, in init self._first_batch = self.next() File "/data4/home/mehuls/Project/DeepLearningExamples/PyTorch/Detection/SSD/ssd/coco_pipeline.py", line 297, in next return self.next(); File "/data4/home/mehuls/Project/DeepLearningExamples/PyTorch/Detection/SSD/ssd/coco_pipeline.py", line 245, in next images_torch_type = to_torch_type[np.dtype(images[0].dtype)] TypeError: Cannot interpret '<DALIDataType.FLOAT: 9>' as a data type