[xnnpack][on-device] executor class #88778
Closed
Conversation
This file contains hidden or bidirectional Unicode text that may be interpreted or compiled differently than what appears below. To review, open the file in an editor that reveals hidden Unicode characters.
Learn more about bidirectional Unicode characters
# Executor Class Executor object used to wrap our xnn_runtime object. The ideal flow of this object looks as such: ``` executor.set_inputs(vector<tensor> inputs, vector<tensor> outputs) executor.forward() ``` This will likely be returned by our delegate compile and given over to execute in order to run inference using the xnn runtime ##### Executorch Considerations ``` #include <ATen/Functions.h> #include <ATen/Utils.h> ``` These Aten functions are included in order to use at::Tensor when setting the inputs, this will change when used for Executorch because we will be switching from at::Tensor to whatever tensor abstraction is used for ET. Seems like they have the same call for `.data_ptr<float>()`, so realistically all logic here will be the same. ATen/Utils is used for TORCH_CHECK. We will switch to ET_CHECK_MESSAGE for executorch. Differential Revision: [D40733121](https://our.internmc.facebook.com/intern/diff/D40733121/) [ghstack-poisoned]
🔗 Helpful Links🧪 See artifacts and rendered test results at hud.pytorch.org/pr/88778
Note: Links to docs will display an error until the docs builds have been completed. ❌ 1 FailuresAs of commit 3dc5bea: This comment was automatically generated by Dr. CI and updates every 15 minutes. |
# Executor Class Executor object used to wrap our xnn_runtime object. The ideal flow of this object looks as such: ``` executor.set_inputs(vector<tensor> inputs, vector<tensor> outputs) executor.forward() ``` This will likely be returned by our delegate compile and given over to execute in order to run inference using the xnn runtime ##### Executorch Considerations ``` #include <ATen/Functions.h> #include <ATen/Utils.h> ``` These Aten functions are included in order to use at::Tensor when setting the inputs, this will change when used for Executorch because we will be switching from at::Tensor to whatever tensor abstraction is used for ET. Seems like they have the same call for `.data_ptr<float>()`, so realistically all logic here will be the same. ATen/Utils is used for TORCH_CHECK. We will switch to ET_CHECK_MESSAGE for executorch. Differential Revision: [D40733121](https://our.internmc.facebook.com/intern/diff/D40733121/) [ghstack-poisoned]
mcr229
added a commit
that referenced
this pull request
Nov 9, 2022
Pull Request resolved: #88778 # Executor Class Executor object used to wrap our xnn_runtime object. The ideal flow of this object looks as such: ``` executor.set_inputs(vector<tensor> inputs, vector<tensor> outputs) executor.forward() ``` This will likely be returned by our delegate compile and given over to execute in order to run inference using the xnn runtime ##### Executorch Considerations ``` #include <ATen/Functions.h> #include <ATen/Utils.h> ``` These Aten functions are included in order to use at::Tensor when setting the inputs, this will change when used for Executorch because we will be switching from at::Tensor to whatever tensor abstraction is used for ET. Seems like they have the same call for `.data_ptr<float>()`, so realistically all logic here will be the same. ATen/Utils is used for TORCH_CHECK. We will switch to ET_CHECK_MESSAGE for executorch. ghstack-source-id: 173215553 Differential Revision: [D40733121](https://our.internmc.facebook.com/intern/diff/D40733121/)
This was referenced Nov 9, 2022
Contributor
|
@pytorchbot merge (Initiating merge automatically since Phabricator Diff has merged) |
Collaborator
Merge startedYour change will be merged once all checks pass (ETA 0-4 Hours). Learn more about merging in the wiki. Questions? Feedback? Please reach out to the PyTorch DevX Team |
kulinseth
pushed a commit
to kulinseth/pytorch
that referenced
this pull request
Dec 10, 2022
# Executor Class Executor object used to wrap our xnn_runtime object. The ideal flow of this object looks as such: ``` executor.set_inputs(vector<tensor> inputs, vector<tensor> outputs) executor.forward() ``` This will likely be returned by our delegate compile and given over to execute in order to run inference using the xnn runtime ##### Executorch Considerations ``` #include <ATen/Functions.h> #include <ATen/Utils.h> ``` These Aten functions are included in order to use at::Tensor when setting the inputs, this will change when used for Executorch because we will be switching from at::Tensor to whatever tensor abstraction is used for ET. Seems like they have the same call for `.data_ptr<float>()`, so realistically all logic here will be the same. ATen/Utils is used for TORCH_CHECK. We will switch to ET_CHECK_MESSAGE for executorch. Differential Revision: [D40733121](https://our.internmc.facebook.com/intern/diff/D40733121/) Pull Request resolved: pytorch#88778 Approved by: https://github.com/digantdesai
Sign up for free
to join this conversation on GitHub.
Already have an account?
Sign in to comment
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.
Stack from ghstack (oldest at bottom):
Executor Class
Executor object used to wrap our xnn_runtime object. The ideal flow of this object looks as such:
This will likely be returned by our delegate compile and given over to execute in order to run inference using the xnn runtime
Executorch Considerations
These Aten functions are included in order to use at::Tensor when setting the inputs, this will change when used for Executorch because we will be switching from at::Tensor to whatever tensor abstraction is used for ET. Seems like they have the same call for
.data_ptr<float>(), so realistically all logic here will be the same.ATen/Utils is used for TORCH_CHECK. We will switch to ET_CHECK_MESSAGE for executorch.
Differential Revision: D40733121