diff --git a/.github/workflows/nightly_publish.yml b/.github/workflows/nightly_publish.yml
index e98de442cf0..b5078ef892d 100644
--- a/.github/workflows/nightly_publish.yml
+++ b/.github/workflows/nightly_publish.yml
@@ -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
@@ -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 }}
diff --git a/bom/build.gradle b/bom/build.gradle
index 8485b714107..31317316138 100644
--- a/bom/build.gradle
+++ b/bom/build.gradle
@@ -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}")
diff --git a/engines/pytorch/pytorch-engine/README.md b/engines/pytorch/pytorch-engine/README.md
index 2bb210f572e..988429f6811 100644
--- a/engines/pytorch/pytorch-engine/README.md
+++ b/engines/pytorch/pytorch-engine/README.md
@@ -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
ai.djl.pytorch
pytorch-native-cpu
osx-x86_64
- 2.0.1
+ 2.1.1
runtime
ai.djl.pytorch
pytorch-jni
- 2.0.1-0.26.0
+ 2.1.1-0.26.0
runtime
```
@@ -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
ai.djl.pytorch
pytorch-native-cpu
osx-aarch64
- 2.0.1
+ 2.1.1
runtime
ai.djl.pytorch
pytorch-jni
- 2.0.1-0.26.0
+ 2.1.1-0.26.0
runtime
```
@@ -162,29 +162,29 @@ 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
ai.djl.pytorch
pytorch-native-cu118
linux-x86_64
- 2.0.1
+ 2.1.1
runtime
ai.djl.pytorch
pytorch-jni
- 2.0.1-0.26.0
+ 2.1.1-0.26.0
runtime
```
### 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
@@ -192,20 +192,20 @@ installed on your GPU machine, you can use one of the following library:
pytorch-native-cpu
linux-x86_64
runtime
- 2.0.1
+ 2.1.1
ai.djl.pytorch
pytorch-jni
- 2.0.1-0.26.0
+ 2.1.1-0.26.0
runtime
```
### 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
@@ -213,12 +213,12 @@ installed on your GPU machine, you can use one of the following library:
pytorch-native-cpu-precxx11
linux-aarch64
runtime
- 2.0.1
+ 2.1.1
ai.djl.pytorch
pytorch-jni
- 2.0.1-0.26.0
+ 2.1.1-0.26.0
runtime
```
@@ -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
ai.djl.pytorch
pytorch-native-cu118-precxx11
linux-x86_64
- 2.0.1
+ 2.1.1
runtime
ai.djl.pytorch
pytorch-jni
- 2.0.1-0.26.0
+ 2.1.1-0.26.0
runtime
```
@@ -253,13 +253,13 @@ All the package were built with GCC 7, we provided a newer `libstdc++.so.6.24` i
ai.djl.pytorch
pytorch-native-cpu-precxx11
linux-x86_64
- 2.0.1
+ 2.1.1
runtime
ai.djl.pytorch
pytorch-jni
- 2.0.1-0.26.0
+ 2.1.1-0.26.0
runtime
```
@@ -274,29 +274,29 @@ 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
ai.djl.pytorch
pytorch-native-cu118
win-x86_64
- 2.0.1
+ 2.1.1
runtime
ai.djl.pytorch
pytorch-jni
- 2.0.1-0.26.0
+ 2.1.1-0.26.0
runtime
```
### 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
@@ -304,12 +304,12 @@ For the Windows platform, you can choose between CPU and GPU.
pytorch-native-cpu
win-x86_64
runtime
- 2.0.1
+ 2.1.1
ai.djl.pytorch
pytorch-jni
- 2.0.1-0.26.0
+ 2.1.1-0.26.0
runtime
```