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narendasan opened this issue Apr 23, 2020 · 0 comments · Fixed by #48
Closed

Version Bumps #42

narendasan opened this issue Apr 23, 2020 · 0 comments · Fixed by #48
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@narendasan
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feature request New feature or request
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v0.1.0

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@narendasan
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With Libtorch 1.5.0 out we are going to be updating soon:

  • Libtorch 1.5.0
  • CUDA 10.2
  • cuDNN 7.6
  • TensorRT 7.0
@narendasan narendasan added the feature request New feature or request label Apr 23, 2020
@narendasan narendasan added this to the v0.1.0 milestone Apr 23, 2020
@narendasan narendasan self-assigned this Apr 23, 2020
narendasan added a commit that referenced this issue Apr 29, 2020
@narendasan
refactor: Upgrading to LibTorch 1.5.0 (CUDA 10.2, cuDNN 7.6.5, TensorRT
a51c7b6 
7.0.0)

- Closes #42
- Issue #1 is back, unknown root cause, will follow up with the PyTorch
Team
- Closes #14: The default build now requires users to grab the tarballs
from the NVIDIA website to support hermetic builds, may look at some
methods to smooth this out later. The old method is still available
- New operators need to be implemented to support MobileNet in 1.5.0
(blocks merge into master)

Signed-off-by: Naren Dasan <[email protected]>
Signed-off-by: Naren Dasan <[email protected]>
@narendasan narendasan mentioned this issue Apr 29, 2020
Merged
frank-wei pushed a commit that referenced this issue Jun 4, 2022
@jackm321
Use fba_enablement and gpu_enablement oncall names instead of aiacc e…
4510e1a 
…xcept for NNPI-related items (#42)

Summary: Pull Request resolved: pytorch/fx2trt#42

Reviewed By: scottxu0730, houseroad, wushirong

Differential Revision: D35266329

fbshipit-source-id: a1fcb04dfacce03d9b7d3fff7758f1956631166f
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Upgrading to LibTorch 1.5.0 (CUDA 10.2, cuDNN 7.6.5, TensorRT 7.0.0) pytorch/TensorRT
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@narendasan