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Inference of PyTorch Model when mapped to Elastic Inference Accelarator is 15 times slow as compared to the CPU inference #3243

@Bilal-Yousaf

Description

@Bilal-Yousaf

Describe the bug
Inference of PyTorch Model when mapped to Elastic Inference Accelarator is 15 times slow as compared to the CPU inference

To reproduce
I am loading CLIP model in Elasitic Accelerator. I had to make some changes in CLIP code, and I am getting same exact output with EIA call as I am getting on CPU call but EIA inference is 15 times slow

Expected behavior
EIA Call should be faster than CPU call

System information

  • Framework name (eg. PyTorch) or algorithm (eg. KMeans): PyTorch
  • Framework version: 1.5.1
  • Python version: 3.6
  • CPU or GPU: eia2.xlarge
  • Custom Docker image (Y/N): N using 763104351884.dkr.ecr.us-east-1.amazonaws.com/pytorch-inference-eia

Additional context
I am running the model using Docker Container

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