You signed in with another tab or window. Reload to refresh your session.You signed out in another tab or window. Reload to refresh your session.You switched accounts on another tab or window. Reload to refresh your session.Dismiss alert
Copy file name to clipboardExpand all lines: backends/mediatek/README.md
+13-8Lines changed: 13 additions & 8 deletions
Display the source diff
Display the rich diff
Original file line number
Diff line number
Diff line change
@@ -6,6 +6,7 @@ MediaTek backend empowers ExecuTorch to speed up PyTorch models on edge devices
6
6
The examples provided in this repository are tested and supported on the following MediaTek chip:
7
7
8
8
- MediaTek Dimensity 9300 (D9300)
9
+
- MediaTek Dimensity 9400 (D9400)
9
10
10
11
## Build Instructions
11
12
@@ -31,13 +32,17 @@ Before you begin, ensure you have the following prerequisites installed and conf
31
32
32
33
#### 3. MediaTek ExecuTorch Libraries
33
34
34
-
Download [NeuroPilot Express SDK](https://neuropilot.mediatek.com/resources/public/npexpress/en/docs/npexpress) from MediaTek's NeuroPilot portal:
35
+
To get started with MediaTek's ExecuTorch libraries, download the [NeuroPilot Express SDK](https://neuropilot.mediatek.com/resources/public/npexpress/en/docs/npexpress) from MediaTek's NeuroPilot portal. The SDK includes the following components:
35
36
36
-
-`libneuronusdk_adapter.mtk.so`: This universal SDK contains the implementation required for executing target-dependent code on the MediaTek chip.
37
-
-`libneuron_buffer_allocator.so`: This utility library is designed for allocating DMA buffers necessary for model inference.
38
-
-`mtk_converter-8.8.0.dev20240723+public.d1467db9-cp310-cp310-manylinux_2_17_x86_64.manylinux2014_x86_64.whl`: This library preprocess the model into a MediaTek representation.
39
-
-`mtk_neuron-8.2.2-py3-none-linux_x86_64.whl`: This library converts the model to binaries.
40
-
- Copy `NeuronAdapter.h` under `backends/mediatek/runtime/include/api/`.
37
+
-**`libneuronusdk_adapter.mtk.so`**: This universal SDK contains the implementation required for executing target-dependent code on the MediaTek chip.
38
+
39
+
-**`libneuron_buffer_allocator.so`**: This utility library is designed for allocating DMA buffers necessary for model inference.
40
+
41
+
-**`mtk_converter-8.13.0+public-cp310-cp310-manylinux_2_17_x86_64.manylinux2014_x86_64.whl`**: This library preprocesses the model into a MediaTek representation.
42
+
43
+
-**`mtk_neuron-8.2.19-py3-none-linux_x86_64.whl`**: This library converts the model to binaries.
44
+
45
+
Additionally, make sure to copy `NeuronAdapter.h` to the following directory: `backends/mediatek/runtime/include/api/`.
41
46
42
47
### Setup
43
48
@@ -52,8 +57,8 @@ Follow the steps below to setup your build environment:
52
57
```
53
58
- Install the two .whl downloaded from NeuroPilot Portal
Copy file name to clipboardExpand all lines: docs/source/backends-mediatek.md
+5-4Lines changed: 5 additions & 4 deletions
Display the source diff
Display the rich diff
Original file line number
Diff line number
Diff line change
@@ -25,6 +25,7 @@ MediaTek backend empowers ExecuTorch to speed up PyTorch models on edge devices
25
25
26
26
### Supported Chips:
27
27
- MediaTek Dimensity 9300 (D9300)
28
+
- MediaTek Dimensity 9400 (D9400)
28
29
29
30
### Software:
30
31
@@ -37,19 +38,19 @@ Follow the steps below to setup your build environment:
37
38
1.**Setup ExecuTorch Environment**: Refer to the [Getting Started](getting-started.md) guide for detailed instructions on setting up the ExecuTorch environment.
38
39
39
40
2.**Setup MediaTek Backend Environment**
40
-
- Install the dependent libs. Ensure that you are inside `backends/mediatek/` directory
41
41
```bash
42
42
pip3 install -r requirements.txt
43
43
```
44
44
- Install the two .whl downloaded from NeuroPilot Portal
0 commit comments