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removing pytorch 2.0.1 from 0.27.0 #2940

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Jan 11, 2024
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removing pytorch 2.0.1 from 0.27.0 #2940

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2 changes: 0 additions & 2 deletions .github/workflows/nightly_publish.yml
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Original file line number Diff line number Diff line change
Expand Up @@ -185,7 +185,6 @@ jobs:
if: ${{ github.event.inputs.mode == '' || github.event.inputs.mode == 'snapshot' }}
run: |
./gradlew clean engines:pytorch:pytorch-jni:publish -Ppt_version=1.13.1 -Psnapshot
./gradlew clean engines:pytorch:pytorch-jni:publish -Ppt_version=2.0.1 -Psnapshot
./gradlew clean engines:pytorch:pytorch-jni:publish -Ppt_version=2.1.1 -Psnapshot
./gradlew clean engines:ml:xgboost:publish -Pgpu -Psnapshot
./gradlew clean publish -Psnapshot
Expand All @@ -200,7 +199,6 @@ jobs:
if: ${{ github.event.inputs.mode == 'staging' }}
run: |
./gradlew clean engines:pytorch:pytorch-jni:publish -Ppt_version=1.13.1 -P${{ github.event.inputs.mode }}
./gradlew clean engines:pytorch:pytorch-jni:publish -Ppt_version=2.0.1 -P${{ github.event.inputs.mode }}
./gradlew clean engines:pytorch:pytorch-jni:publish -Ppt_version=2.1.1 -P${{ github.event.inputs.mode }}
./gradlew clean engines:ml:xgboost:publish -Pgpu -P${{ github.event.inputs.mode }}
./gradlew clean publish -P${{ github.event.inputs.mode }}
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3 changes: 0 additions & 3 deletions bom/build.gradle
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Expand Up @@ -122,9 +122,6 @@ publishing {
addDependency(dependencies, "ai.djl.pytorch", "pytorch-native-cu117", "linux-x86_64", "1.13.1")
addDependency(dependencies, "ai.djl.pytorch", "pytorch-native-cu117", "win-x86_64", "1.13.1")
addDependency(dependencies, "ai.djl.pytorch", "pytorch-native-cu117-precxx11", "linux-x86_64", "1.13.1")
addDependency(dependencies, "ai.djl.pytorch", "pytorch-native-cu118", "linux-x86_64", "2.0.1")
addDependency(dependencies, "ai.djl.pytorch", "pytorch-native-cu118", "win-x86_64", "2.0.1")
addDependency(dependencies, "ai.djl.pytorch", "pytorch-native-cu118-precxx11", "linux-x86_64", "2.0.1")
addDependency(dependencies, "ai.djl.tensorflow", "tensorflow-native-cpu", "osx-x86_64", "${tensorflow_version}")
addDependency(dependencies, "ai.djl.tensorflow", "tensorflow-native-cpu", "linux-x86_64", "${tensorflow_version}")
addDependency(dependencies, "ai.djl.tensorflow", "tensorflow-native-cpu", "win-x86_64", "${tensorflow_version}")
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70 changes: 35 additions & 35 deletions engines/pytorch/pytorch-engine/README.md
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Expand Up @@ -113,21 +113,21 @@ export PYTORCH_FLAVOR=cpu
### macOS
For macOS, you can use the following library:

- ai.djl.pytorch:pytorch-jni:2.0.1-0.26.0
- ai.djl.pytorch:pytorch-native-cpu:2.0.1:osx-x86_64
- ai.djl.pytorch:pytorch-jni:2.1.1-0.26.0
- ai.djl.pytorch:pytorch-native-cpu:2.1.1:osx-x86_64

```xml
<dependency>
<groupId>ai.djl.pytorch</groupId>
<artifactId>pytorch-native-cpu</artifactId>
<classifier>osx-x86_64</classifier>
<version>2.0.1</version>
<version>2.1.1</version>
<scope>runtime</scope>
</dependency>
<dependency>
<groupId>ai.djl.pytorch</groupId>
<artifactId>pytorch-jni</artifactId>
<version>2.0.1-0.26.0</version>
<version>2.1.1-0.26.0</version>
<scope>runtime</scope>
</dependency>
```
Expand All @@ -137,21 +137,21 @@ For macOS, you can use the following library:
### macOS M1
For macOS M1, you can use the following library:

- ai.djl.pytorch:pytorch-jni:2.0.1-0.26.0
- ai.djl.pytorch:pytorch-native-cpu:2.0.1:osx-aarch64
- ai.djl.pytorch:pytorch-jni:2.1.1-0.26.0
- ai.djl.pytorch:pytorch-native-cpu:2.1.1:osx-aarch64

```xml
<dependency>
<groupId>ai.djl.pytorch</groupId>
<artifactId>pytorch-native-cpu</artifactId>
<classifier>osx-aarch64</classifier>
<version>2.0.1</version>
<version>2.1.1</version>
<scope>runtime</scope>
</dependency>
<dependency>
<groupId>ai.djl.pytorch</groupId>
<artifactId>pytorch-jni</artifactId>
<version>2.0.1-0.26.0</version>
<version>2.1.1-0.26.0</version>
<scope>runtime</scope>
</dependency>
```
Expand All @@ -162,63 +162,63 @@ installed on your GPU machine, you can use one of the following library:

#### Linux GPU

- ai.djl.pytorch:pytorch-jni:2.0.1-0.26.0
- ai.djl.pytorch:pytorch-native-cu118:2.0.1:linux-x86_64 - CUDA 11.8
- ai.djl.pytorch:pytorch-jni:2.1.1-0.26.0
- ai.djl.pytorch:pytorch-native-cu118:2.1.1:linux-x86_64 - CUDA 11.8

```xml
<dependency>
<groupId>ai.djl.pytorch</groupId>
<artifactId>pytorch-native-cu118</artifactId>
<classifier>linux-x86_64</classifier>
<version>2.0.1</version>
<version>2.1.1</version>
<scope>runtime</scope>
</dependency>
<dependency>
<groupId>ai.djl.pytorch</groupId>
<artifactId>pytorch-jni</artifactId>
<version>2.0.1-0.26.0</version>
<version>2.1.1-0.26.0</version>
<scope>runtime</scope>
</dependency>
```

### Linux CPU

- ai.djl.pytorch:pytorch-jni:2.0.1-0.26.0
- ai.djl.pytorch:pytorch-native-cpu:2.0.1:linux-x86_64
- ai.djl.pytorch:pytorch-jni:2.1.1-0.26.0
- ai.djl.pytorch:pytorch-native-cpu:2.1.1:linux-x86_64

```xml
<dependency>
<groupId>ai.djl.pytorch</groupId>
<artifactId>pytorch-native-cpu</artifactId>
<classifier>linux-x86_64</classifier>
<scope>runtime</scope>
<version>2.0.1</version>
<version>2.1.1</version>
</dependency>
<dependency>
<groupId>ai.djl.pytorch</groupId>
<artifactId>pytorch-jni</artifactId>
<version>2.0.1-0.26.0</version>
<version>2.1.1-0.26.0</version>
<scope>runtime</scope>
</dependency>
```

### For aarch64 build

- ai.djl.pytorch:pytorch-jni:2.0.1-0.26.0
- ai.djl.pytorch:pytorch-native-cpu-precxx11:2.0.1:linux-aarch64
- ai.djl.pytorch:pytorch-jni:2.1.1-0.26.0
- ai.djl.pytorch:pytorch-native-cpu-precxx11:2.1.1:linux-aarch64

```xml
<dependency>
<groupId>ai.djl.pytorch</groupId>
<artifactId>pytorch-native-cpu-precxx11</artifactId>
<classifier>linux-aarch64</classifier>
<scope>runtime</scope>
<version>2.0.1</version>
<version>2.1.1</version>
</dependency>
<dependency>
<groupId>ai.djl.pytorch</groupId>
<artifactId>pytorch-jni</artifactId>
<version>2.0.1-0.26.0</version>
<version>2.1.1-0.26.0</version>
<scope>runtime</scope>
</dependency>
```
Expand All @@ -228,22 +228,22 @@ installed on your GPU machine, you can use one of the following library:
We also provide packages for the system like CentOS 7/Ubuntu 14.04 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:2.0.1-0.26.0
- ai.djl.pytorch:pytorch-native-cu118-precxx11:2.0.1:linux-x86_64 - CUDA 11.8
- ai.djl.pytorch:pytorch-native-cpu-precxx11:2.0.1:linux-x86_64 - CPU
- ai.djl.pytorch:pytorch-jni:2.1.1-0.26.0
- ai.djl.pytorch:pytorch-native-cu118-precxx11:2.1.1:linux-x86_64 - CUDA 11.8
- ai.djl.pytorch:pytorch-native-cpu-precxx11:2.1.1:linux-x86_64 - CPU

```xml
<dependency>
<groupId>ai.djl.pytorch</groupId>
<artifactId>pytorch-native-cu118-precxx11</artifactId>
<classifier>linux-x86_64</classifier>
<version>2.0.1</version>
<version>2.1.1</version>
<scope>runtime</scope>
</dependency>
<dependency>
<groupId>ai.djl.pytorch</groupId>
<artifactId>pytorch-jni</artifactId>
<version>2.0.1-0.26.0</version>
<version>2.1.1-0.26.0</version>
<scope>runtime</scope>
</dependency>
```
Expand All @@ -253,13 +253,13 @@ All the package were built with GCC 7, we provided a newer `libstdc++.so.6.24` i
<groupId>ai.djl.pytorch</groupId>
<artifactId>pytorch-native-cpu-precxx11</artifactId>
<classifier>linux-x86_64</classifier>
<version>2.0.1</version>
<version>2.1.1</version>
<scope>runtime</scope>
</dependency>
<dependency>
<groupId>ai.djl.pytorch</groupId>
<artifactId>pytorch-jni</artifactId>
<version>2.0.1-0.26.0</version>
<version>2.1.1-0.26.0</version>
<scope>runtime</scope>
</dependency>
```
Expand All @@ -274,42 +274,42 @@ For the Windows platform, you can choose between CPU and GPU.

#### Windows GPU

- ai.djl.pytorch:pytorch-jni:2.0.1-0.26.0
- ai.djl.pytorch:pytorch-native-cu118:2.0.1:win-x86_64 - CUDA 11.8
- ai.djl.pytorch:pytorch-jni:2.1.1-0.26.0
- ai.djl.pytorch:pytorch-native-cu118:2.1.1:win-x86_64 - CUDA 11.8

```xml
<dependency>
<groupId>ai.djl.pytorch</groupId>
<artifactId>pytorch-native-cu118</artifactId>
<classifier>win-x86_64</classifier>
<version>2.0.1</version>
<version>2.1.1</version>
<scope>runtime</scope>
</dependency>
<dependency>
<groupId>ai.djl.pytorch</groupId>
<artifactId>pytorch-jni</artifactId>
<version>2.0.1-0.26.0</version>
<version>2.1.1-0.26.0</version>
<scope>runtime</scope>
</dependency>
```

### Windows CPU

- ai.djl.pytorch:pytorch-jni:2.0.1-0.26.0
- ai.djl.pytorch:pytorch-native-cpu:2.0.1:win-x86_64
- ai.djl.pytorch:pytorch-jni:2.1.1-0.26.0
- ai.djl.pytorch:pytorch-native-cpu:2.1.1:win-x86_64

```xml
<dependency>
<groupId>ai.djl.pytorch</groupId>
<artifactId>pytorch-native-cpu</artifactId>
<classifier>win-x86_64</classifier>
<scope>runtime</scope>
<version>2.0.1</version>
<version>2.1.1</version>
</dependency>
<dependency>
<groupId>ai.djl.pytorch</groupId>
<artifactId>pytorch-jni</artifactId>
<version>2.0.1-0.26.0</version>
<version>2.1.1-0.26.0</version>
<scope>runtime</scope>
</dependency>
```