Thanks for the reply.
Workstation
Model is saved in my workstation-computer as
 torch.save(model_fast_r_cnn.state_dict(), "./data/myModels/car_truck_proai.pth") # Saving the model

The torchvision and torchvision versions on workstation are
torch                   1.7.0
torchvision             0.8.1

This model is then copied to the Nvidia-hardware.
Nvidia hardware
The below shown step loads the model successfully on the Nvidia-ProAI hardware
model.load_state_dict(torch.load(data['Model']['path']))  # model loaded using yaml file
model.eval()  # put the model in evaluation mode

The problem occurs when the “video frame or Image” is passed to the model for object detection
    results = model([frame]) # Passing frame inside model

The torch and torchvision on the Nvidia-hardware is
torch              1.7.0a0
torchvision        0.8.0a0+2f40a48

Error
Traceback (most recent call last):
  File "/home/nvidia/Desktop/test_env/python_programs/pytorch_cnn/1.obj_det/detection_car_truck/main_det.py", line 82, in <module>
    results = score_frame(frame, model,device=device)  
  File "/home/nvidia/Desktop/test_env/python_programs/pytorch_cnn/1.obj_det/detection_car_truck/obj_det_functions.py", line 118, in score_frame
    results = model([frame])
  File "/home/nvidia/Softwares/miniconda3/envs/torch_cp37/lib/python3.7/site-packages/torch/nn/modules/module.py", line 727, in _call_impl
    result = self.forward(*input, **kwargs)
  File "/home/nvidia/Softwares/miniconda3/envs/torch_cp37/lib/python3.7/site-packages/torchvision/models/detection/generalized_rcnn.py", line 100, in forward
    detections, detector_losses = self.roi_heads(features, proposals, images.image_sizes, targets)
  File "/home/nvidia/Softwares/miniconda3/envs/torch_cp37/lib/python3.7/site-packages/torch/nn/modules/module.py", line 727, in _call_impl
    result = self.forward(*input, **kwargs)
  File "/home/nvidia/Softwares/miniconda3/envs/torch_cp37/lib/python3.7/site-packages/torchvision/models/detection/roi_heads.py", line 752, in forward
    box_features = self.box_roi_pool(features, proposals, image_shapes)
  File "/home/nvidia/Softwares/miniconda3/envs/torch_cp37/lib/python3.7/site-packages/torch/nn/modules/module.py", line 727, in _call_impl
    result = self.forward(*input, **kwargs)
  File "/home/nvidia/Softwares/miniconda3/envs/torch_cp37/lib/python3.7/site-packages/torchvision/ops/poolers.py", line 213, in forward
    self.setup_scales(x_filtered, image_shapes)
  File "/home/nvidia/Softwares/miniconda3/envs/torch_cp37/lib/python3.7/site-packages/torchvision/ops/poolers.py", line 174, in setup_scales
    scales = [self.infer_scale(feat, original_input_shape) for feat in features]
  File "/home/nvidia/Softwares/miniconda3/envs/torch_cp37/lib/python3.7/site-packages/torchvision/ops/poolers.py", line 174, in <listcomp>
    scales = [self.infer_scale(feat, original_input_shape) for feat in features]
  File "/home/nvidia/Softwares/miniconda3/envs/torch_cp37/lib/python3.7/site-packages/torchvision/ops/poolers.py", line 158, in infer_scale
    assert possible_scales[0] == possible_scales[1]
AssertionError

Please let me know if further information is needed. Thank you in advance.