Float16 does not halve existing compared to Float32 ?


I am currently using the TensorRT accelerated Yolov5s model and find that the parameter acceleration based on Float16 does not halve the image memory of the model compared to the parameter float32? Is this normal?


TensorRT Version*: 7.0
GPU Type: 2080Ti
Nvidia Driver Version: 440
CUDA Version: 10.2
CUDNN Version: 7.6.5
Operating System + Version: Centos7
Python Version (if applicable): python3.6
TensorFlow Version (if applicable):
PyTorch Version (if applicable):
Baremetal or Container (if container which image + tag):

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Hi @1965281904,
Image memory won’t be half right if you switch from float 32 to 16.
Are you using float 16 in strict mode? Also are you facing any issue or no performance improvement?