Skip to content
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

[docs] Updates PyTorch engine README for 2.4.0 #3472

Merged
merged 1 commit into from
Sep 13, 2024
Merged

[docs] Updates PyTorch engine README for 2.4.0 #3472

Changes from all commits
Commits
Show all changes
1 commit
Select commit
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
62 changes: 31 additions & 31 deletions engines/pytorch/pytorch-engine/README.md
View file
Open in desktop
Original file line number Diff line number Diff line change
Expand Up @@ -133,22 +133,22 @@ export PYTORCH_FLAVOR=cpu

For macOS M1, you can use the following library:

- ai.djl.pytorch:pytorch-jni:2.3.1-0.29.0
- ai.djl.pytorch:pytorch-native-cpu:2.3.1:osx-aarch64
- ai.djl.pytorch:pytorch-jni:2.4.0-0.30.0
- ai.djl.pytorch:pytorch-native-cpu:2.4.0:osx-aarch64

```xml

<dependency>
<groupId>ai.djl.pytorch</groupId>
<artifactId>pytorch-native-cpu</artifactId>
<classifier>osx-aarch64</classifier>
<version>2.3.1</version>
<version>2.4.0</version>
<scope>runtime</scope>
</dependency>
<dependency>
<groupId>ai.djl.pytorch</groupId>
<artifactId>pytorch-jni</artifactId>
<version>2.3.1-0.29.0</version>
<version>2.4.0-0.30.0</version>
<scope>runtime</scope>
</dependency>
```
Expand All @@ -160,30 +160,30 @@ installed on your GPU machine, you can use one of the following library:

#### Linux GPU

- ai.djl.pytorch:pytorch-jni:2.3.1-0.29.0
- ai.djl.pytorch:pytorch-native-cu121:2.3.1:linux-x86_64 - CUDA 12.1
- ai.djl.pytorch:pytorch-jni:2.4.0-0.30.0
- ai.djl.pytorch:pytorch-native-cu124:2.4.0:linux-x86_64 - CUDA 12.4

```xml

<dependency>
<groupId>ai.djl.pytorch</groupId>
<artifactId>pytorch-native-cu121</artifactId>
<artifactId>pytorch-native-cu124</artifactId>
<classifier>linux-x86_64</classifier>
<version>2.3.1</version>
<version>2.4.0</version>
<scope>runtime</scope>
</dependency>
<dependency>
<groupId>ai.djl.pytorch</groupId>
<artifactId>pytorch-jni</artifactId>
<version>2.3.1-0.29.0</version>
<version>2.4.0-0.30.0</version>
<scope>runtime</scope>
</dependency>
```

### Linux CPU

- ai.djl.pytorch:pytorch-jni:2.3.1-0.29.0
- ai.djl.pytorch:pytorch-native-cpu:2.3.1:linux-x86_64
- ai.djl.pytorch:pytorch-jni:2.4.0-0.30.0
- ai.djl.pytorch:pytorch-native-cpu:2.4.0:linux-x86_64

```xml

Expand All @@ -192,20 +192,20 @@ installed on your GPU machine, you can use one of the following library:
<artifactId>pytorch-native-cpu</artifactId>
<classifier>linux-x86_64</classifier>
<scope>runtime</scope>
<version>2.3.1</version>
<version>2.4.0</version>
</dependency>
<dependency>
<groupId>ai.djl.pytorch</groupId>
<artifactId>pytorch-jni</artifactId>
<version>2.3.1-0.29.0</version>
<version>2.4.0-0.30.0</version>
<scope>runtime</scope>
</dependency>
```

### For aarch64 build

- ai.djl.pytorch:pytorch-jni:2.3.1-0.29.0
- ai.djl.pytorch:pytorch-native-cpu-precxx11:2.3.1:linux-aarch64
- ai.djl.pytorch:pytorch-jni:2.4.0-0.30.0
- ai.djl.pytorch:pytorch-native-cpu-precxx11:2.4.0:linux-aarch64

```xml

Expand All @@ -214,12 +214,12 @@ installed on your GPU machine, you can use one of the following library:
<artifactId>pytorch-native-cpu-precxx11</artifactId>
<classifier>linux-aarch64</classifier>
<scope>runtime</scope>
<version>2.3.1</version>
<version>2.4.0</version>
</dependency>
<dependency>
<groupId>ai.djl.pytorch</groupId>
<artifactId>pytorch-jni</artifactId>
<version>2.3.1-0.29.0</version>
<version>2.4.0-0.30.0</version>
<scope>runtime</scope>
</dependency>
```
Expand All @@ -232,15 +232,15 @@ We also provide packages for the system like Amazonliunx 2 with GLIBC >= 2.17.
All the package were built with GCC 7, we provided a newer `libstdc++.so.6.24` in the package that
contains `CXXABI_1.3.9` to use the package successfully.

- ai.djl.pytorch:pytorch-jni:2.3.1-0.29.0
- ai.djl.pytorch:pytorch-native-cpu-precxx11:2.3.1:linux-x86_64 - CPU
- ai.djl.pytorch:pytorch-jni:2.4.0-0.30.0
- ai.djl.pytorch:pytorch-native-cpu-precxx11:2.4.0:linux-x86_64 - CPU

```xml

<dependency>
<groupId>ai.djl.pytorch</groupId>
<artifactId>pytorch-jni</artifactId>
<version>2.3.1-0.29.0</version>
<version>2.4.0-0.30.0</version>
<scope>runtime</scope>
</dependency>
```
Expand All @@ -251,13 +251,13 @@ contains `CXXABI_1.3.9` to use the package successfully.
<groupId>ai.djl.pytorch</groupId>
<artifactId>pytorch-native-cpu-precxx11</artifactId>
<classifier>linux-x86_64</classifier>
<version>2.3.1</version>
<version>2.4.0</version>
<scope>runtime</scope>
</dependency>
<dependency>
<groupId>ai.djl.pytorch</groupId>
<artifactId>pytorch-jni</artifactId>
<version>2.3.1-0.29.0</version>
<version>2.4.0-0.30.0</version>
<scope>runtime</scope>
</dependency>
```
Expand All @@ -273,30 +273,30 @@ For the Windows platform, you can choose between CPU and GPU.

#### Windows GPU

- ai.djl.pytorch:pytorch-jni:2.3.1-0.29.0
- ai.djl.pytorch:pytorch-native-cu121:2.3.1:win-x86_64 - CUDA 12.1
- ai.djl.pytorch:pytorch-jni:2.4.0-0.30.0
- ai.djl.pytorch:pytorch-native-cu124:2.4.0:win-x86_64 - CUDA 12.4

```xml

<dependency>
<groupId>ai.djl.pytorch</groupId>
<artifactId>pytorch-native-cu121</artifactId>
<artifactId>pytorch-native-cu124</artifactId>
<classifier>win-x86_64</classifier>
<version>2.3.1</version>
<version>2.4.0</version>
<scope>runtime</scope>
</dependency>
<dependency>
<groupId>ai.djl.pytorch</groupId>
<artifactId>pytorch-jni</artifactId>
<version>2.3.1-0.29.0</version>
<version>2.4.0-0.30.0</version>
<scope>runtime</scope>
</dependency>
```

### Windows CPU

- ai.djl.pytorch:pytorch-jni:2.3.1-0.29.0
- ai.djl.pytorch:pytorch-native-cpu:2.3.1:win-x86_64
- ai.djl.pytorch:pytorch-jni:2.4.0-0.30.0
- ai.djl.pytorch:pytorch-native-cpu:2.4.0:win-x86_64

```xml

Expand All @@ -305,12 +305,12 @@ For the Windows platform, you can choose between CPU and GPU.
<artifactId>pytorch-native-cpu</artifactId>
<classifier>win-x86_64</classifier>
<scope>runtime</scope>
<version>2.3.1</version>
<version>2.4.0</version>
</dependency>
<dependency>
<groupId>ai.djl.pytorch</groupId>
<artifactId>pytorch-jni</artifactId>
<version>2.3.1-0.29.0</version>
<version>2.4.0-0.30.0</version>
<scope>runtime</scope>
</dependency>
```
Loading