Add this suggestion to a batch that can be applied as a single commit.
This suggestion is invalid because no changes were made to the code.
Suggestions cannot be applied while the pull request is closed.
Suggestions cannot be applied while viewing a subset of changes.
Only one suggestion per line can be applied in a batch.
Add this suggestion to a batch that can be applied as a single commit.
Applying suggestions on deleted lines is not supported.
You must change the existing code in this line in order to create a valid suggestion.
Outdated suggestions cannot be applied.
This suggestion has been applied or marked resolved.
Suggestions cannot be applied from pending reviews.
Suggestions cannot be applied on multi-line comments.
Suggestions cannot be applied while the pull request is queued to merge.
Suggestion cannot be applied right now. Please check back later.
New issue
Have a question about this project? Sign up for a free GitHub account to open an issue and contact its maintainers and the community.
By clicking “Sign up for GitHub”, you agree to our terms of service and privacy statement. We’ll occasionally send you account related emails.
Already on GitHub? Sign in to your account
Bring back Python backend based PyTorch backend #6518
Bring back Python backend based PyTorch backend #6518
Changes from 8 commits
4ed5f21
ec777d5
b674ea4
b52159d
e3fc774
b59f7d7
50670f6
dde5b33
1f4607a
cc6b256
8d2f155
282b2e5
c368f47
e1d82df
530a6f0
File filter
Filter by extension
Conversations
Jump to
There are no files selected for viewing
There was a problem hiding this comment.
Choose a reason for hiding this comment
The reason will be displayed to describe this comment to others. Learn more.
should auto-complete fill in this field with correct value as well (i.e., this would be
/opt/tritonserver/backends/onnxruntime/libtriton_onnxruntime.so
)?There was a problem hiding this comment.
Choose a reason for hiding this comment
The reason will be displayed to describe this comment to others. Learn more.
That was my original thought, but the issue is how does auto-complete determine if the model uses C++ or Python runtime? A simple solution is to have backend specific auto-complete implementation. For example, if it the model uses PyTorch backend and a
*.pt
model file is provided without any*.py
file, then use C++. If a*.py
file is provided, then use Python. See this commit. From previous discussions with @nnshah1 and @rmccorm4, we want to stop adding more backend specific logic into auto-complete and opt for a generic implementation, which Python runtime falls into the category of custom backend on auto-complete. Backends can implement either C++ or Python runtime (or both), we do not want to auto-complete into Python runtime on a C++ only backend, which requires checking the backend installation directory. The current structure limits auto-complete to only see model directory, but not backend directory, because the latter is resolved only when the model is loaded, which happens after auto-complete. A easier approach is to resolve runtime, if not already filled, when the model is loaded, which has both the model and backend directory information.Going back to the original question, auto-complete does not touch the runtime field, it is determined/filled when the model is loaded, if it is not already filled.