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6 changes: 3 additions & 3 deletions docs/source/backends-vulkan.md
Original file line number Diff line number Diff line change
Expand Up @@ -32,7 +32,7 @@ The ExecuTorch Vulkan Delegate is a wrapper around a standalone runtime known as
the **Vulkan Compute Library**. The aim of the Vulkan Compute Library is to
provide GPU implementations for PyTorch operators via GLSL compute shaders.

The Vulkan Compute Library is a fork/iteration of the [PyTorch Vulkan Backend](https://pytorch.org/tutorials/prototype/vulkan_workflow.html).
The Vulkan Compute Library is a fork/iteration of the [PyTorch Vulkan Backend](https://docs.pytorch.org/tutorials/unstable/vulkan_workflow.html).
The core components of the PyTorch Vulkan backend were forked into ExecuTorch
and adapted for an AOT graph-mode style of model inference (as opposed to
PyTorch which adopted an eager execution style of model inference).
Expand Down Expand Up @@ -127,7 +127,7 @@ using the `to_backend()` API. The Vulkan Delegate implements the
that are supported by the Vulkan delegate, and separates compatible sections of
the model to be executed on the GPU.

This means the a model can be lowered to the Vulkan delegate even if it contains
This means a model can be lowered to the Vulkan delegate even if it contains
some unsupported operators. This will just mean that only parts of the graph
will be executed on the GPU.

Expand All @@ -152,7 +152,7 @@ First, make sure that you have the Android NDK installed; any NDK version past
NDK r19c should work. Note that the examples in this doc have been validated with
NDK r27b. The Android SDK should also be installed so that you have access to `adb`.

The instructions in this page assumes that the following environment variables
The instructions in this page assume that the following environment variables
are set.

```shell
Expand Down
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