Open sathisha-beltech opened 2 years ago
When I executed the following usage code given in the README file, I found that the code is consuming 25% of RAM.
import torch from torch import nn from torchvision.models.resnet import resnet50 # create some regular pytorch model... model = resnet50().cuda().eval() # create example data x = torch.ones((1, 3, 224, 224)).cuda() # convert to TensorRT feeding sample data as input opt_shape_param = [ [ [1, 3, 128, 128], # min [1, 3, 256, 256], # opt [1, 3, 512, 512] # max ] ] model_trt = torch2trt_dynamic(model, [x], fp16_mode=False, opt_shape_param=opt_shape_param)
When I executed the following usage code given in the README file, I found that the code is consuming 25% of RAM.