Skip to content

Fix broken links in README #527

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.

Sign up for GitHub

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

Merged
dan-garvey merged 2 commits into from
Mar 14, 2024
Merged

Fix broken links in README #527

Changes from all commits
Commits
Show all changes
2 commits
Select commit Hold shift + click to select a range
c76c5fb
Fix broken links in README
penguin-wwy Mar 12, 2024
4d7646c
Merge branch 'main' into fix_doc
dan-garvey Mar 14, 2024
File filter

Filter by extension

Filter by extension
Conversations
Failed to load comments.
Loading
Jump to
Jump to file
Failed to load files.
Loading
Diff view
Diff view
10 changes: 5 additions & 5 deletions README.md
View file
Open in desktop
Original file line number Diff line number Diff line change
Expand Up @@ -10,8 +10,8 @@ is intended to be a general purpose model compilation and execution tool.
Turbine provides three primary tools:

* *AOT Export*: For compiling one or more `nn.Module`s to compiled, deployment
ready artifacts. This operates via both a [simple one-shot export API](https://github.com/nod-ai/SHARK-Turbine/blob/main/python/shark_turbine/aot/exporter.py)
for simple models and an underlying [advanced API](https://github.com/nod-ai/SHARK-Turbine/blob/main/python/shark_turbine/aot/compiled_module.py) for complicated models
ready artifacts. This operates via both a simple one-shot export API (Already upstreamed to [torch-mlir](https://github.com/llvm/torch-mlir/blob/main/python/torch_mlir/extras/fx_importer.py))
for simple models and an underlying [advanced API](https://github.com/nod-ai/SHARK-Turbine/blob/main/core/shark_turbine/aot/compiled_module.py) for complicated models
and accessing the full features of the runtime.
* *Eager Execution*: A `torch.compile` backend is provided and a Turbine Tensor/Device
is available for more native, interactive use within a PyTorch session.
Expand Down Expand Up @@ -62,11 +62,11 @@ compiler, these should be compilable via IREE with `--iree-input-type=torch` for
end to end execution. Dynamic shape support in torch-mlir is a work in progress,
and not everything works at head with release binaries at present.

* [AOT MLP With Static Shapes](https://github.com/nod-ai/SHARK-Turbine/blob/main/examples/aot_mlp/mlp_export_simple.py)
* [AOT MLP with a dynamic batch size](https://github.com/nod-ai/SHARK-Turbine/blob/main/examples/aot_mlp/mlp_export_dynamic.py)
* [AOT MLP With Static Shapes](https://github.com/nod-ai/SHARK-Turbine/blob/main/core/examples/aot_mlp/mlp_export_simple.py)
* [AOT MLP with a dynamic batch size](https://github.com/nod-ai/SHARK-Turbine/blob/main/core/examples/aot_mlp/mlp_export_dynamic.py)
* [AOT llama2](https://github.com/nod-ai/SHARK-Turbine/blob/main/core/examples/llama2_inference/llama2.ipynb):
Dynamic sequence length custom compiled module with state management internal to the model.
* [Eager MNIST with `torch.compile`](https://github.com/nod-ai/SHARK-Turbine/blob/main/examples/eager_mlp/mlp_eager_simple.py)
* [Eager MNIST with `torch.compile`](https://github.com/nod-ai/SHARK-Turbine/blob/main/core/examples/eager_mlp/mlp_eager_simple.py)

## Developers

Expand Down