Repository: deepjavalibrary/djl
Pull request #1459 (2022-01-13 03:53:35)

[docs] Update engine documents to remove -auto package
Change-Id: Ia4188c0cd8af7e549e8a7bd1cf6b3c760c8ffdad

## Description ##

Brief description of what this PR is about

- If this change is a backward incompatible change, why must this change be made?
- Interesting edge cases to note here



Patch:
diff --git a/bom/build.gradle b/bom/build.gradle
index 382058cf4..a8000ccf4 100644
--- a/bom/build.gradle
+++ b/bom/build.gradle
@@ -98,15 +98,15 @@ publishing {
                     addDependency(dependencies, "ai.djl.mxnet", "mxnet-native-mkl", "win-x86_64", "${mxnet_version}")
                     addDependency(dependencies, "ai.djl.mxnet", "mxnet-native-cu102mkl", "linux-x86_64", "${mxnet_version}")
                     addDependency(dependencies, "ai.djl.mxnet", "mxnet-native-cu110mkl", "linux-x86_64", "${mxnet_version}")
-                    addDependency(dependencies, "ai.djl.pytorch", "pytorch-native-cpu", "osx-x86_64", "${pytorch_version}-SNAPSHOT")
-                    addDependency(dependencies, "ai.djl.pytorch", "pytorch-native-cpu", "linux-x86_64", "${pytorch_version}-SNAPSHOT")
-                    addDependency(dependencies, "ai.djl.pytorch", "pytorch-native-cpu", "win-x86_64", "${pytorch_version}-SNAPSHOT")
-                    addDependency(dependencies, "ai.djl.pytorch", "pytorch-native-cpu-precxx11", "linux-x86_64", "${pytorch_version}-SNAPSHOT")
-                    addDependency(dependencies, "ai.djl.pytorch", "pytorch-native-cu102", "linux-x86_64", "${pytorch_version}-SNAPSHOT")
-                    addDependency(dependencies, "ai.djl.pytorch", "pytorch-native-cu102", "win-x86_64", "${pytorch_version}-SNAPSHOT")
-                    addDependency(dependencies, "ai.djl.pytorch", "pytorch-native-cu113", "linux-x86_64", "${pytorch_version}-SNAPSHOT")
-                    addDependency(dependencies, "ai.djl.pytorch", "pytorch-native-cu113", "win-x86_64", "${pytorch_version}-SNAPSHOT")
-                    addDependency(dependencies, "ai.djl.pytorch", "pytorch-native-cu113-precxx11", "linux-x86_64", "${pytorch_version}-SNAPSHOT")
+                    addDependency(dependencies, "ai.djl.pytorch", "pytorch-native-cpu", "osx-x86_64", "${pytorch_version}")
+                    addDependency(dependencies, "ai.djl.pytorch", "pytorch-native-cpu", "linux-x86_64", "${pytorch_version}")
+                    addDependency(dependencies, "ai.djl.pytorch", "pytorch-native-cpu", "win-x86_64", "${pytorch_version}")
+                    addDependency(dependencies, "ai.djl.pytorch", "pytorch-native-cpu-precxx11", "linux-x86_64", "${pytorch_version}")
+                    addDependency(dependencies, "ai.djl.pytorch", "pytorch-native-cu102", "linux-x86_64", "${pytorch_version}")
+                    addDependency(dependencies, "ai.djl.pytorch", "pytorch-native-cu102", "win-x86_64", "${pytorch_version}")
+                    addDependency(dependencies, "ai.djl.pytorch", "pytorch-native-cu113", "linux-x86_64", "${pytorch_version}")
+                    addDependency(dependencies, "ai.djl.pytorch", "pytorch-native-cu113", "win-x86_64", "${pytorch_version}")
+                    addDependency(dependencies, "ai.djl.pytorch", "pytorch-native-cu113-precxx11", "linux-x86_64", "${pytorch_version}")
                     addDependency(dependencies, "ai.djl.tensorflow", "tensorflow-native-cpu", "osx-x86_64", "${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/docs/development/dependency_management.md b/docs/development/dependency_management.md
index 58f626afd..7e0cb8db8 100644
--- a/docs/development/dependency_management.md
+++ b/docs/development/dependency_management.md
@@ -43,26 +43,30 @@ See [How to use DJL's BOM](../../bom/README.md#how-to-use-djls-bom) for detail.
 | | | |
 | [ai.djl.mxnet](https://search.maven.org/search?q=g:ai.djl.mxnet) | [mxnet-engine](../../engines/mxnet/mxnet-engine/README.md#installation) | Apache MXNet engine adapter |
 | | [mxnet-model-zoo](../../engines/mxnet/mxnet-model-zoo/README.md#installation) | Contains state of the art Apache MXNet symbolic models |
-| | [mxnet-native-auto](../../engines/mxnet/mxnet-engine/README.md#automatic-recommended) | A placeholder package to automatically download native libraries for your platform |
 | | [mxnet-native-mkl(osx-x86_64)](../../engines/mxnet/mxnet-engine/README.md#macos) | Contains Apache MXNet native library for macOS |
 | | [mxnet-native-mkl(win-x86_64)](../../engines/mxnet/mxnet-engine/README.md#windows-cpu) | Contains Apache MXNet native library for Windows |
 | | [mxnet-native-mkl(linux-x86_64)](../../engines/mxnet/mxnet-engine/README.md#linux-cpu) | Contains Apache MXNet native library for Linux |
 | | [mxnet-native-cu110(linux-x86_64)](../../engines/mxnet/mxnet-engine/README.md#linux-gpu) | Contains Apache MXNet native library for Linux with CUDA 11.0|
 | | [mxnet-native-cu102(linux-x86_64)](../../engines/mxnet/mxnet-engine/README.md#linux-gpu) | Contains Apache MXNet native library for Linux with CUDA 10.2|
+| | mxnet-native-auto (deprecated) | No longer needed since DJL 0.15.0 |
 | | mxnet-native-cu101(linux-x86_64) (deprecated) | Contains Apache MXNet native library <= 1.7.0 for Linux with CUDA 10.1 |
 | | mxnet-native-cu92(linux-x86_64) (deprecated) | Contains Apache MXNet native library <= 1.6.0 for Linux with CUDA 9.2 |
 | | | |
 | [ai.djl.pytorch](https://search.maven.org/search?q=g:ai.djl.pytorch) | [pytorch-engine](../../engines/pytorch/pytorch-engine/README.md#installation) | PyTorch engine adapter |
 | | [pytorch-model-zoo](../../engines/pytorch/pytorch-model-zoo/README.md#installation) | Contains state of the art PyTorch torch script models |
-| | [pytorch-native-auto](../../engines/pytorch/pytorch-engine/README.md#automatic-recommended) | A placeholder package to automatically download native libraries for your platform |
 | | [pytorch-native-cpu(osx-x86_64)](../../engines/pytorch/pytorch-engine/README.md#macos) | Contains PyTorch native library for macOS |
 | | [pytorch-native-cpu(win-x86_64)](../../engines/pytorch/pytorch-engine/README.md#windows-cpu) | Contains PyTorch native library for Windows |
 | | [pytorch-native-cpu(linux-x86_64)](../../engines/pytorch/pytorch-engine/README.md#linux-cpu) | Contains PyTorch native library for Linux |
-| | [pytorch-native-cu111(linux-x86_64)](../../engines/pytorch/pytorch-engine/README.md#linux-gpu) | Contains PyTorch native library for Linux with CUDA 11.1 |
-| | [pytorch-native-cu111(win-x86_64)](../../engines/pytorch/pytorch-engine/README.md#windows-gpu) | Contains PyTorch native library for Windows with CUDA 11.1 |
+| | [pytorch-native-cu113(linux-x86_64)](../../engines/pytorch/pytorch-engine/README.md#linux-gpu) | Contains PyTorch native library for Linux with CUDA 11.3 |
+| | [pytorch-native-cu113(win-x86_64)](../../engines/pytorch/pytorch-engine/README.md#windows-gpu) | Contains PyTorch native library for Windows with CUDA 11.3 |
 | | [pytorch-native-cu102(linux-x86_64)](../../engines/pytorch/pytorch-engine/README.md#linux-gpu) | Contains PyTorch native library for Linux with CUDA 10.2 |
 | | [pytorch-native-cu102(win-x86_64)](../../engines/pytorch/pytorch-engine/README.md#windows-gpu) | Contains PyTorch native library for Windows with CUDA 10.2 |
-| | [pytorch-native-cpu-precxx11 (linux-x86_64)](../../engines/pytorch/pytorch-engine/README.md#for-pre-cxx11-build) | Contains PyTorch native library for centOS 7 and Ubuntu 14.04 |
+| | [pytorch-native-cu113-precxx11(linux-x86_64)](../../engines/pytorch/pytorch-engine/README.md#for-pre-cxx11-build) | Contains PyTorch native library for Linux with CUDA 11.3 |
+| | [pytorch-native-cu102-precxx11(linux-x86_64)](../../engines/pytorch/pytorch-engine/README.md#for-pre-cxx11-build) | Contains PyTorch native library for Windows with CUDA 10.2 |
+| | [pytorch-native-cpu-precxx11(linux-x86_64)](../../engines/pytorch/pytorch-engine/README.md#for-pre-cxx11-build) | Contains PyTorch native library for centOS 7 and Ubuntu 14.04 |
+| | pytorch-native-auto (deprecated) | No longer needed since DJL 0.15.0 |
+| | pytorch-native-cu111(linux-x86_64) (deprecated) | Contains PyTorch native library for Linux with CUDA 11.1 |
+| | pytorch-native-cu111(win-x86_64) (deprecated) | Contains PyTorch native library for Windows with CUDA 11.1 |
 | | pytorch-native-cu101(linux-x86_64) (deprecated) | Contains PyTorch native library <= 1.7.1 for Linux with CUDA 10.1 |
 | | pytorch-native-cu101(win-x86_64) (deprecated) | Contains PyTorch native library <= 1.7.1 for Windows with CUDA 10.1 |
 | | pytorch-native-cu92(linux-x86_64) (deprecated) | Contains PyTorch native library <= 1.6.0 for Linux with CUDA 9.2 |
@@ -72,21 +76,21 @@ See [How to use DJL's BOM](../../bom/README.md#how-to-use-djls-bom) for detail.
 | [ai.djl.tensorflow](https://search.maven.org/search?q=g:ai.djl.tensorflow) | [tensorflow-engine](../../engines/tensorflow/tensorflow-engine/README.md#installation) | TensorFlow engine adapter |
 | | [tensorflow-api](../../engines/tensorflow/tensorflow-api/README.md#installation) | A redistribution of tensorFlow core java API 2.x |
 | | [tensorflow-model-zoo](../../engines/tensorflow/tensorflow-model-zoo/README.md#installation) | Contains state of the art TensorFlow saved bundle models |
-| | [tensorflow-native-auto](../../engines/tensorflow/tensorflow-engine/README.md#automatic-recommended) | A placeholder package to automatically download native libraries for your platform |
 | | [tensorflow-native-cpu(osx-x86_64)](../../engines/tensorflow/tensorflow-engine/README.md#macos) | Contains TensorFlow native library for macOS |
 | | [tensorflow-native-cpu(linux-x86_64)](../../engines/tensorflow/tensorflow-engine/README.md#linux-cpu) | Contains TensorFlow native library for Linux |
 | | [tensorflow-native-cpu(win-x86_64)](../../engines/tensorflow/tensorflow-engine/README.md#windows-cpu) | Contains TensorFlow native library for Windows |
 | | [tensorflow-native-cu110(linux-x86_84)](../../engines/tensorflow/tensorflow-engine/README.md#linux-gpu) | Contains TensorFlow native library for Linux with CUDA 11.0 |
+| | tensorflow-native-auto (deprecated) | No longer needed since DJL 0.15.0 |
 | | tensorflow-native-cu101(linux-x86_84) (deprecated) | Contains TensorFlow native library <= 2.3.0 for Linux with CUDA 10.1 |
 | | | |
 | [ai.djl.paddlepaddle](https://search.maven.org/search?q=g:ai.djl.paddlepaddle) | [paddlepaddle-engine](../../engines/paddlepaddle/paddlepaddle-engine/README.md#installation) | PaddlePaddle engine adapter |
 | | [paddlepaddle-model-zoo](../../engines/paddlepaddle/paddlepaddle-model-zoo/README.md#installation) | Contains state of the art PaddlePaddle models |
-| | [paddlepaddle-native-auto](../../engines/paddlepaddle/paddlepaddle-engine/README.md#automatic-recommended) | A placeholder package to automatically download native libraries for your platform |
 | | [paddlepaddle-native-cpu(osx-x86_64)](../../engines/paddlepaddle/paddlepaddle-engine/README.md#macos) | Contains PaddlePaddle native library for macOS |
 | | [paddlepaddle-native-cpu(linux-x86_64)](../../engines/paddlepaddle/paddlepaddle-engine/README.md#linux) | Contains PaddlePaddle native library for Linux |
 | | [paddlepaddle-native-cpu(win-x86_64)](../../engines/paddlepaddle/paddlepaddle-engine/README.md#windows) | Contains PaddlePaddle native library for Windows |
 | | [paddlepaddle-native-cu102(linux-x86_64)](../../engines/paddlepaddle/paddlepaddle-engine/README.md#Linux-GPU) | Contains PaddlePaddle native library for Linux with CUDA 10.2 |
 | | [paddlepaddle-native-cu101(linux-x86_64)](../../engines/paddlepaddle/paddlepaddle-engine/README.md#Linux-GPU) | Contains PaddlePaddle native library for Linux with CUDA 10.1 |
+| | paddlepaddle-native-auto (deprecated) | No longer needed since DJL 0.15.0 |
 | | | |
 | [ai.djl.onnxruntime](https://search.maven.org/search?q=g:ai.djl.onnxruntime) | [onnxruntime-engine](../../engines/onnxruntime/onnxruntime-engine/README.md#installation) | ONNX Runtime engine adapter |
 | | onnxruntime-api(deprecated) | Please use com.microsoft.onnxruntime:onnxruntime instead |
@@ -94,14 +98,14 @@ See [How to use DJL's BOM](../../bom/README.md#how-to-use-djls-bom) for detail.
 | | onnxruntime-native-cpu(deprecated) | Please use com.microsoft.onnxruntime:onnxruntime instead |
 | | | |
 | [ai.djl.dlr](https://search.maven.org/search?q=g:ai.djl.dlr) | [dlr-engine](../../engines/dlr/dlr-engine/README.md#installation) | Neo DLR engine adapter |
-| | [dlr-native-auto](../../engines/dlr/dlr-engine/README.md#automatic-recommended) | A placeholder package to automatically download native libraries for your platform |
 | | [dlr-native-cpu(osx-x86_64)](../../engines/dlr/dlr-engine/README.md#macos) | Contains Neo LR native library for macOS |
 | | [dlr-native-cpu(linux-x86_64)](../../engines/dlr/dlr-engine/README.md#linux) | Contains Neo DLR native library for Linux |
+| | dlr-native-auto (deprecated) | No longer needed since DJL 0.15.0 |
 | | | |
 | [ai.djl.tflite](https://search.maven.org/search?q=g:ai.djl.tflite) | [tflite-engine](../../engines/tflite/tflite-engine/README.md#installation) | TensorFlow Lite engine adapter |
-| | [tflite-native-auto (optional)](../../engines/tflite/tflite-engine/README.md#Installation) | A placeholder package to automatically download native libraries for your platform |
 | | [tflite-native-cpu(osx-x86_64)](../../engines/tflite/tflite-engine/README.md#macos) | Contains TensorFlow Lite native library for macOS |
 | | [tflite-native-cpu(linux-x86_64)](../../engines/tflite/tflite-engine/README.md#linux) | Contains TensorFlow Lite native library for Linux |
+| | tflite-native-auto (deprecated) | No longer needed since DJL 0.15.0 |
 | | | |
 | [ai.djl.tensorrt](https://search.maven.org/search?q=g:ai.djl.tensorrt) | [tensorrt](../../engines/tensorrt/README.md#installation) | TensorRT engine adapter |
 | | | |
@@ -122,4 +126,6 @@ See [How to use DJL's BOM](../../bom/README.md#how-to-use-djls-bom) for detail.
 | | | |
 | [ai.djl.opencv](https://search.maven.org/search?q=g:ai.djl.opencv) | [opencv](../../extensions/opencv/README.md#installation) | DJL OpenCV extension for high performance image processing |
 | | | |
+| [ai.djl.tokenizers](https://search.maven.org/search?q=g:ai.djl.tokenizers) | [tokenizers](../../extensions/tokenizers/README.md#installation) | DJL Huggingface tokenizers extension for NLP tokenize processing |
+| | | |
 | [ai.djl.serving](https://search.maven.org/search?q=g:ai.djl.serving) | [wlm](https://github.com/deepjavalibrary/djl-serving/tree/master/wlm) | DJL Serving WorkLoadManager |
diff --git a/engines/dlr/dlr-engine/README.md b/engines/dlr/dlr-engine/README.md
index 8717f1e1c..0ed416227 100644
--- a/engines/dlr/dlr-engine/README.md
+++ b/engines/dlr/dlr-engine/README.md
@@ -29,34 +29,21 @@ The javadocs output is generated in the `build/doc/javadoc` folder.
 ## Installation
 You can pull the DLR engine from the central Maven repository by including the following dependency:
 
-- ai.djl.dlr:dlr-engine:0.14.0
+- ai.djl.dlr:dlr-engine:0.15.0
 
 ```xml
 <dependency>
     <groupId>ai.djl.dlr</groupId>
     <artifactId>dlr-engine</artifactId>
-    <version>0.14.0</version>
+    <version>0.15.0</version>
     <scope>runtime</scope>
 </dependency>
 ```
 
-Besides the `dlr-engine` library, you may also need to include the Neo DLR native library in your project.
-
-Choose a native library based on your platform and needs:
-
-### Automatic (Recommended)
-
-We offer an automatic option that will download the native libraries into [cache folder](../../../docs/development/cache_management.md) the first time you run DJL.
+By default, DJL will download the DLR native libraries into [cache folder](../../../docs/development/cache_management.md) the first time you run DJL.
 It will automatically determine the appropriate jars for your system based on the platform and GPU support.
 
-```xml
-<dependency>
-    <groupId>ai.djl.dlr</groupId>
-    <artifactId>dlr-native-auto</artifactId>
-    <version>1.6.0</version>
-    <scope>runtime</scope>
-</dependency>
-```
+You can choose a native library based on your platform if you don't have network access at runtime.
 
 ### macOS
 For macOS, you can use the following library:
diff --git a/engines/ml/xgboost/README.md b/engines/ml/xgboost/README.md
index f61c52610..e879b793b 100644
--- a/engines/ml/xgboost/README.md
+++ b/engines/ml/xgboost/README.md
@@ -37,13 +37,13 @@ XGBoost can only run on top of the Linux/Mac machine. User can build from source
 ## Installation
 You can pull the XGBoost engine from the central Maven repository by including the following dependency:
 
-- ai.djl.ml.xgboost:xgboost:0.14.0
+- ai.djl.ml.xgboost:xgboost:0.15.0
 
 ```xml
 <dependency>
     <groupId>ai.djl.ml.xgboost</groupId>
     <artifactId>xgboost</artifactId>
-    <version>0.14.0</version>
+    <version>0.15.0</version>
     <scope>runtime</scope>
 </dependency>
 ```
diff --git a/engines/mxnet/mxnet-engine/README.md b/engines/mxnet/mxnet-engine/README.md
index 1b924b911..196bce287 100644
--- a/engines/mxnet/mxnet-engine/README.md
+++ b/engines/mxnet/mxnet-engine/README.md
@@ -32,29 +32,15 @@ You can pull the MXNet engine from the central Maven repository by including the
 <dependency>
     <groupId>ai.djl.mxnet</groupId>
     <artifactId>mxnet-engine</artifactId>
-    <version>0.14.0</version>
+    <version>0.15.0</version>
     <scope>runtime</scope>
 </dependency>
 ```
 
-Besides the `mxnet-engine` library, you may also need to include the MXNet native library in your project.
-All current provided MXNet native libraries are built with [MKLDNN](https://github.com/intel/mkl-dnn).
-
-Choose a native library based on your platform and needs:
-
-### Automatic (Recommended)
-
-We offer an automatic option that will download the native libraries into [cache folder](../../../docs/development/cache_management.md) the first time you run DJL.
+By default, DJL will download the Apache MXNet native libraries into [cache folder](../../../docs/development/cache_management.md) the first time you run DJL.
 It will automatically determine the appropriate jars for your system based on the platform and GPU support.
 
-```xml
-<dependency>
-    <groupId>ai.djl.mxnet</groupId>
-    <artifactId>mxnet-native-auto</artifactId>
-    <version>1.8.0</version>
-    <scope>runtime</scope>
-</dependency>
-```
+You can choose a native library based on your platform if you don't have network access at runtime.
 
 ### macOS
 For macOS, you can use the following library:
diff --git a/engines/mxnet/mxnet-model-zoo/README.md b/engines/mxnet/mxnet-model-zoo/README.md
index 80a6301a5..395fce34e 100644
--- a/engines/mxnet/mxnet-model-zoo/README.md
+++ b/engines/mxnet/mxnet-model-zoo/README.md
@@ -27,7 +27,7 @@ You can pull the MXNet engine from the central Maven repository by including the
 <dependency>
     <groupId>ai.djl.mxnet</groupId>
     <artifactId>mxnet-model-zoo</artifactId>
-    <version>0.14.0</version>
+    <version>0.15.0</version>
 </dependency>
 ```
 
diff --git a/engines/onnxruntime/onnxruntime-engine/README.md b/engines/onnxruntime/onnxruntime-engine/README.md
index b9134d590..155db17f9 100644
--- a/engines/onnxruntime/onnxruntime-engine/README.md
+++ b/engines/onnxruntime/onnxruntime-engine/README.md
@@ -37,13 +37,13 @@ for the official ONNX Runtime project.
 ## Installation
 You can pull the ONNX Runtime engine from the central Maven repository by including the following dependency:
 
-- ai.djl.onnxruntime:onnxruntime-engine:0.14.0
+- ai.djl.onnxruntime:onnxruntime-engine:0.15.0
 
 ```xml
 <dependency>
     <groupId>ai.djl.onnxruntime</groupId>
     <artifactId>onnxruntime-engine</artifactId>
-    <version>0.14.0</version>
+    <version>0.15.0</version>
     <scope>runtime</scope>
 </dependency>
 ```
@@ -61,7 +61,7 @@ Maven:
 <dependency>
     <groupId>ai.djl.onnxruntime</groupId>
     <artifactId>onnxruntime-engine</artifactId>
-    <version>0.14.0</version>
+    <version>0.15.0</version>
     <scope>runtime</scope>
     <exclusions>
         <exclusion>
@@ -80,7 +80,7 @@ Maven:
 
 Gradle:
 ```
-    implementation("ai.djl.onnxruntime:onnxruntime-engine:0.14.0") {
+    implementation("ai.djl.onnxruntime:onnxruntime-engine:0.15.0") {
         exclude group: "com.microsoft.onnxruntime", module: "onnxruntime"
     }
     implementation "com.microsoft.onnxruntime:onnxruntime_gpu:1.10.0"
diff --git a/engines/paddlepaddle/paddlepaddle-engine/README.md b/engines/paddlepaddle/paddlepaddle-engine/README.md
index 6dcf65e6f..6da909601 100644
--- a/engines/paddlepaddle/paddlepaddle-engine/README.md
+++ b/engines/paddlepaddle/paddlepaddle-engine/README.md
@@ -30,30 +30,15 @@ You can pull the PaddlePaddle engine from the central Maven repository by includ
 <dependency>
     <groupId>ai.djl.paddlepaddle</groupId>
     <artifactId>paddlepaddle-engine</artifactId>
-    <version>0.14.0</version>
+    <version>0.15.0</version>
     <scope>runtime</scope>
 </dependency>
 ```
 
-Besides the `paddlepaddle-engine` library, you may also need to include the PaddlePaddle native library in your project.
-
-Choose a native library based on your platform and needs:
-
-### Automatic (Recommended)
-
-We offer an automatic option that will download the native libraries into [cache folder](../../../docs/development/cache_management.md) the first time you run DJL.
+By default, DJL will download the PaddlePaddle native libraries into [cache folder](../../../docs/development/cache_management.md) the first time you run DJL.
 It will automatically determine the appropriate jars for your system based on the platform and GPU support.
 
-- ai.djl.paddlepaddle:paddlepaddle-native-auto:2.0.2
-
-```xml
-<dependency>
-    <groupId>ai.djl.paddlepaddle</groupId>
-    <artifactId>paddlepaddle-native-auto</artifactId>
-    <version>2.0.2</version>
-    <scope>runtime</scope>
-</dependency>
-```
+You can choose a native library based on your platform if you don't have network access at runtime.
 
 ### macOS
 For macOS, you can use the following library:
diff --git a/engines/paddlepaddle/paddlepaddle-model-zoo/README.md b/engines/paddlepaddle/paddlepaddle-model-zoo/README.md
index a5e299cfb..fc969b36b 100644
--- a/engines/paddlepaddle/paddlepaddle-model-zoo/README.md
+++ b/engines/paddlepaddle/paddlepaddle-model-zoo/README.md
@@ -26,7 +26,7 @@ from the central Maven repository by including the following dependency:
 <dependency>
     <groupId>ai.djl.paddlepaddle</groupId>
     <artifactId>paddlepaddle-model-zoo</artifactId>
-    <version>0.14.0</version>
+    <version>0.15.0</version>
 </dependency>
 ```
 
diff --git a/engines/pytorch/pytorch-engine/README.md b/engines/pytorch/pytorch-engine/README.md
index d9c0511ea..3ec6e3ba0 100644
--- a/engines/pytorch/pytorch-engine/README.md
+++ b/engines/pytorch/pytorch-engine/README.md
@@ -24,20 +24,17 @@ The javadocs output is built in the `build/doc/javadoc` folder.
 ## Installation
 You can pull the PyTorch engine from the central Maven repository by including the following dependency:
 
-- ai.djl.pytorch:pytorch-engine:0.14.0
+- ai.djl.pytorch:pytorch-engine:0.15.0
 
 ```xml
 <dependency>
     <groupId>ai.djl.pytorch</groupId>
     <artifactId>pytorch-engine</artifactId>
-    <version>0.14.0</version>
+    <version>0.15.0</version>
     <scope>runtime</scope>
 </dependency>
 ```
 
-Besides the `pytorch-engine` library, you may also need to include the PyTorch native library in your project.
-All current provided PyTorch native libraries are downloaded from [PyTorch C++ distribution](https://pytorch.org/get-started/locally/#start-locally).
-
 Since DJL 0.14.0, `pytorch-engine` can load older version of pytorch native library. There are two
 ways to specify PyTorch version:
 
@@ -46,54 +43,39 @@ ways to specify PyTorch version:
 
 The following table illustrates which pytorch version that DJL supports:
 
-| PyTorch engine version | PyTorch native library version           |
-|------------------------|------------------------------------------|
-| pytorch-engine:0.14.0  | pytorch-native-auto: 1.8.1, 1.9.0, 1.9.1 |
-| pytorch-engine:0.13.0  | pytorch-native-auto:1.9.0                |
-| pytorch-engine:0.12.0  | pytorch-native-auto:1.8.1                |
-| pytorch-engine:0.11.0  | pytorch-native-auto:1.8.1                |
-| pytorch-engine:0.10.0  | pytorch-native-auto:1.7.1                |
-| pytorch-engine:0.9.0   | pytorch-native-auto:1.7.0                |
-| pytorch-engine:0.8.0   | pytorch-native-auto:1.6.0                |
-| pytorch-engine:0.7.0   | pytorch-native-auto:1.6.0                |
-| pytorch-engine:0.6.0   | pytorch-native-auto:1.5.0                |
-| pytorch-engine:0.5.0   | pytorch-native-auto:1.4.0                |
-| pytorch-engine:0.4.0   | pytorch-native-auto:1.4.0                |
+| PyTorch engine version | PyTorch native library version             |
+|------------------------|--------------------------------------------|
+| pytorch-engine:0.15.0  | pytorch-native-auto: 1.8.1, 1.9.1, 1.10.0  |
+| pytorch-engine:0.14.0  | pytorch-native-auto: 1.8.1, 1.9.0, 1.9.1   |
+| pytorch-engine:0.13.0  | pytorch-native-auto:1.9.0                  |
+| pytorch-engine:0.12.0  | pytorch-native-auto:1.8.1                  |
+| pytorch-engine:0.11.0  | pytorch-native-auto:1.8.1                  |
+| pytorch-engine:0.10.0  | pytorch-native-auto:1.7.1                  |
+| pytorch-engine:0.9.0   | pytorch-native-auto:1.7.0                  |
+| pytorch-engine:0.8.0   | pytorch-native-auto:1.6.0                  |
+| pytorch-engine:0.7.0   | pytorch-native-auto:1.6.0                  |
+| pytorch-engine:0.6.0   | pytorch-native-auto:1.5.0                  |
+| pytorch-engine:0.5.0   | pytorch-native-auto:1.4.0                  |
+| pytorch-engine:0.4.0   | pytorch-native-auto:1.4.0                  |
 
 We strongly recommend you to use [Bill of Materials (BOM)](../../../bom/README.md) to manage your dependencies.
 
-Choose a native library based on your platform and needs:
-
-### Automatic (Recommended)
-
-We offer an automatic option that will download the native libraries into [cache folder](../../../docs/development/cache_management.md) the first time you run DJL.
+By default, DJL will download the PyTorch native libraries into [cache folder](../../../docs/development/cache_management.md) the first time you run DJL.
 It will automatically determine the appropriate jars for your system based on the platform and GPU support.
 
-Since DJL 0.14.0, the auto package is optional, DJL will download the latest pytorch native library
-if no `pytorch-native-auto` package is included.
-
-- ai.djl.pytorch:pytorch-native-auto:1.9.1
-
-```xml
-<dependency>
-    <groupId>ai.djl.pytorch</groupId>
-    <artifactId>pytorch-native-auto</artifactId>
-    <version>1.9.1</version>
-    <scope>runtime</scope>
-</dependency>
-```
+You can choose a native library based on your platform if you don't have network access at runtime.
 
 ### macOS
 For macOS, you can use the following library:
 
-- ai.djl.pytorch:pytorch-native-cpu:1.9.1:osx-x86_64
+- ai.djl.pytorch:pytorch-native-cpu:1.10.0:osx-x86_64
 
 ```xml
 <dependency>
     <groupId>ai.djl.pytorch</groupId>
     <artifactId>pytorch-native-cpu</artifactId>
     <classifier>osx-x86_64</classifier>
-    <version>1.9.1</version>
+    <version>1.10.0</version>
     <scope>runtime</scope>
 </dependency>
 ```
@@ -104,15 +86,15 @@ installed on your GPU machine, you can use one of the following library:
 
 #### Linux GPU
 
-- ai.djl.pytorch:pytorch-native-cu111:1.9.1:linux-x86_64 - CUDA 11.1
-- ai.djl.pytorch:pytorch-native-cu102:1.9.1:linux-x86_64 - CUDA 10.2
+- ai.djl.pytorch:pytorch-native-cu113:1.10.0:linux-x86_64 - CUDA 11.3
+- ai.djl.pytorch:pytorch-native-cu102:1.10.0:linux-x86_64 - CUDA 10.2
 
 ```xml
 <dependency>
     <groupId>ai.djl.pytorch</groupId>
-    <artifactId>pytorch-native-cu111</artifactId>
+    <artifactId>pytorch-native-cu113</artifactId>
     <classifier>linux-x86_64</classifier>
-    <version>1.9.1</version>
+    <version>1.10.0</version>
     <scope>runtime</scope>
 </dependency>
 ```
@@ -122,14 +104,14 @@ installed on your GPU machine, you can use one of the following library:
     <groupId>ai.djl.pytorch</groupId>
     <artifactId>pytorch-native-cu102</artifactId>
     <classifier>linux-x86_64</classifier>
-    <version>1.9.1</version>
+    <version>1.10.0</version>
     <scope>runtime</scope>
 </dependency>
 ```
 
 ### Linux CPU
 
-- ai.djl.pytorch:pytorch-native-cpu:1.9.1:linux-x86_64
+- ai.djl.pytorch:pytorch-native-cpu:1.10.0:linux-x86_64
 
 ```xml
 <dependency>
@@ -137,7 +119,7 @@ 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>1.9.1</version>
+    <version>1.10.0</version>
 </dependency>
 ```
 
@@ -146,14 +128,36 @@ 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-native-cpu-precxx11:1.9.1:linux-x86_64
+- ai.djl.pytorch:pytorch-native-cu113-precxx11:1.10.0:linux-x86_64 - CUDA 11.3
+- ai.djl.pytorch:pytorch-native-cu102-precxx11:1.10.0:linux-x86_64 - CUDA 10.2
+- ai.djl.pytorch:pytorch-native-cpu-precxx11:1.10.0:linux-x86_64   - CPU
+
+```xml
+<dependency>
+    <groupId>ai.djl.pytorch</groupId>
+    <artifactId>pytorch-native-cu113-precxx11</artifactId>
+    <classifier>linux-x86_64</classifier>
+    <version>1.10.0</version>
+    <scope>runtime</scope>
+</dependency>
+```
+
+```xml
+<dependency>
+    <groupId>ai.djl.pytorch</groupId>
+    <artifactId>pytorch-native-cu102-precxx11</artifactId>
+    <classifier>linux-x86_64</classifier>
+    <version>1.10.0</version>
+    <scope>runtime</scope>
+</dependency>
+```
 
 ```xml
 <dependency>
     <groupId>ai.djl.pytorch</groupId>
     <artifactId>pytorch-native-cpu-precxx11</artifactId>
     <classifier>linux-x86_64</classifier>
-    <version>1.9.1</version>
+    <version>1.10.0</version>
     <scope>runtime</scope>
 </dependency>
 ```
@@ -168,15 +172,15 @@ For the Windows platform, you can choose between CPU and GPU.
 
 #### Windows GPU
 
-- ai.djl.pytorch:pytorch-native-cu111:1.9.1:win-x86_64
-- ai.djl.pytorch:pytorch-native-cu102:1.9.1:win-x86_64
+- ai.djl.pytorch:pytorch-native-cu113:1.10.0:win-x86_64
+- ai.djl.pytorch:pytorch-native-cu102:1.10.0:win-x86_64
 
 ```xml
 <dependency>
     <groupId>ai.djl.pytorch</groupId>
-    <artifactId>pytorch-native-cu111</artifactId>
+    <artifactId>pytorch-native-cu113</artifactId>
     <classifier>win-x86_64</classifier>
-    <version>1.9.1</version>
+    <version>1.10.0</version>
     <scope>runtime</scope>
 </dependency>
 ```
@@ -186,14 +190,14 @@ For the Windows platform, you can choose between CPU and GPU.
     <groupId>ai.djl.pytorch</groupId>
     <artifactId>pytorch-native-cu102</artifactId>
     <classifier>win-x86_64</classifier>
-    <version>1.9.1</version>
+    <version>1.10.0</version>
     <scope>runtime</scope>
 </dependency>
 ```
 
 ### Windows CPU
 
-- ai.djl.pytorch:pytorch-native-cpu:1.9.1:win-x86_64
+- ai.djl.pytorch:pytorch-native-cpu:1.10.0:win-x86_64
 
 ```xml
 <dependency>
@@ -201,6 +205,6 @@ 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>1.9.1</version>
+    <version>1.10.0</version>
 </dependency>
 ```
diff --git a/engines/pytorch/pytorch-model-zoo/README.md b/engines/pytorch/pytorch-model-zoo/README.md
index 389fee8cb..df25b3038 100644
--- a/engines/pytorch/pytorch-model-zoo/README.md
+++ b/engines/pytorch/pytorch-model-zoo/README.md
@@ -25,7 +25,7 @@ You can pull the PyTorch engine from the central Maven repository by including t
 <dependency>
     <groupId>ai.djl.pytorch</groupId>
     <artifactId>pytorch-model-zoo</artifactId>
-    <version>0.14.0</version>
+    <version>0.15.0</version>
 </dependency>
 ```
 
diff --git a/engines/tensorflow/tensorflow-api/README.md b/engines/tensorflow/tensorflow-api/README.md
index d2a843af2..10c696a2e 100644
--- a/engines/tensorflow/tensorflow-api/README.md
+++ b/engines/tensorflow/tensorflow-api/README.md
@@ -16,6 +16,6 @@ You can pull the TensorFlow core java API from the central Maven repository by i
 <dependency>
     <groupId>ai.djl.tensorflow</groupId>
     <artifactId>tensorflow-api</artifactId>
-    <version>0.14.0</version>
+    <version>0.15.0</version>
 </dependency>
 ```
diff --git a/engines/tensorflow/tensorflow-engine/README.md b/engines/tensorflow/tensorflow-engine/README.md
index cd7e04b3b..ed0a69214 100644
--- a/engines/tensorflow/tensorflow-engine/README.md
+++ b/engines/tensorflow/tensorflow-engine/README.md
@@ -28,35 +28,20 @@ The javadocs output is built in the `build/doc/javadoc` folder.
 
 You can pull the TensorFlow engine from the central Maven repository by including the following dependency:
 
-- ai.djl.tensorflow:tensorflow-engine:0.14.0
+- ai.djl.tensorflow:tensorflow-engine:0.15.0
 
 ```xml
 <dependency>
     <groupId>ai.djl.tensorflow</groupId>
     <artifactId>tensorflow-engine</artifactId>
-    <version>0.14.0</version>
+    <version>0.15.0</version>
     <scope>runtime</scope>
 </dependency>
 ```
-Besides the `tensorflow-engine` library, you may also need to include the TensorFlow native library in your project.
-
-Choose a native library based on your platform and needs:
-
-### Automatic (Recommended)
-
-We offer an automatic option that will download the native libraries into [cache folder](../../../docs/development/cache_management.md) the first time you run DJL.
+By default, DJL will download the TensorFlow native libraries into [cache folder](../../../docs/development/cache_management.md) the first time you run DJL.
 It will automatically determine the appropriate jars for your system based on the platform and GPU support.
 
-- ai.djl.tensorflow:tensorflow-native-auto:2.4.1
-
-```xml
-<dependency>
-    <groupId>ai.djl.tensorflow</groupId>
-    <artifactId>tensorflow-native-auto</artifactId>
-    <version>2.4.1</version>
-    <scope>runtime</scope>
-</dependency>
-```
+You can choose a native library based on your platform if you don't have network access at runtime.
 
 ### macOS
 For macOS, you can use the following library:
diff --git a/engines/tensorflow/tensorflow-model-zoo/README.md b/engines/tensorflow/tensorflow-model-zoo/README.md
index e329b8c49..88b412cd7 100644
--- a/engines/tensorflow/tensorflow-model-zoo/README.md
+++ b/engines/tensorflow/tensorflow-model-zoo/README.md
@@ -26,7 +26,7 @@ from the central Maven repository by including the following dependency:
 <dependency>
     <groupId>ai.djl.tensorflow</groupId>
     <artifactId>tensorflow-model-zoo</artifactId>
-    <version>0.14.0</version>
+    <version>0.15.0</version>
 </dependency>
 ```
 
diff --git a/engines/tensorrt/README.md b/engines/tensorrt/README.md
index aacc8498b..fe33a7e9c 100644
--- a/engines/tensorrt/README.md
+++ b/engines/tensorrt/README.md
@@ -28,13 +28,13 @@ The javadocs output is generated in the `build/doc/javadoc` folder.
 ## Installation
 You can pull the TensorRT engine from the central Maven repository by including the following dependency:
 
-- ai.djl.tensorrt:tensorrt:0.14.0
+- ai.djl.tensorrt:tensorrt:0.15.0
 
 ```xml
 <dependency>
     <groupId>ai.djl.tensorrt</groupId>
     <artifactId>tensorrt</artifactId>
-    <version>0.14.0</version>
+    <version>0.15.0</version>
     <scope>runtime</scope>
 </dependency>
 ```
diff --git a/engines/tflite/tflite-engine/README.md b/engines/tflite/tflite-engine/README.md
index 7eff8f130..f0befe2f9 100644
--- a/engines/tflite/tflite-engine/README.md
+++ b/engines/tflite/tflite-engine/README.md
@@ -35,10 +35,10 @@ You can pull the TensorFlow Lite engine from the central Maven repository by inc
 </dependency>
 ```
 
-### Automatic
+By default, DJL will download the TensorFlow Lite native libraries into [cache folder](../../../docs/development/cache_management.md) the first time you run DJL.
+It will automatically determine the appropriate jars for your system based on the platform and GPU support.
 
-By default, DJL will automatically download the native libraries into [cache folder](../../../docs/development/cache_management.md) the first time you run DJL.
-It will automatically determine the appropriate jars for your system based on the platform.
+You can choose a native library based on your platform if you don't have network access at runtime.
 
 ### macOS
 For macOS, you can use the following library:
diff --git a/extensions/hadoop/build.gradle b/extensions/hadoop/build.gradle
index 2130fcf92..9ab777f21 100644
--- a/extensions/hadoop/build.gradle
+++ b/extensions/hadoop/build.gradle
@@ -8,7 +8,8 @@ dependencies {
     testImplementation "org.apache.hadoop:hadoop-minicluster:${hadoop_version}"
     testImplementation(project(":testing"))
 
-    testImplementation("org.testng:testng:${testng_version}");
+    testImplementation "org.testng:testng:${testng_version}"
+    testRuntimeOnly "junit:junit:${junit_version}" // hadoop-client test depends on junit
 }
 
 publishing {
diff --git a/gradle.properties b/gradle.properties
index 3dd6d9a6c..412acc01c 100644
--- a/gradle.properties
+++ b/gradle.properties
@@ -25,15 +25,15 @@ commons_cli_version=1.4
 commons_compress_version=1.21
 commons_csv_version=1.8
 commons_logging_version=1.2
-gson_version=2.8.8
+gson_version=2.8.9
 jna_version=5.9.0
 slf4j_version=1.7.32
 log4j_slf4j_version=2.17.1
-awssdk_version=2.17.54
+awssdk_version=2.17.109
 hadoop_version=3.3.1
 javacpp_version=1.5.6
-protobuf_version=3.8.0
+protobuf_version=3.19.2
 
 antlr_version=4.9.2
-# testng 7.4.0 has bug, we have to keep it as 7.3.0 for now
-testng_version=7.3.0
+testng_version=7.5
+junit_version=4.13.2


Test patch:
diff --git a/testing/build.gradle b/testing/build.gradle
index 2369e7396..9b2081f35 100644
--- a/testing/build.gradle
+++ b/testing/build.gradle
@@ -1,6 +1,4 @@
 dependencies {
     api project(":api")
-    api("org.testng:testng:${testng_version}") {
-        exclude group: "junit", module: "junit"
-    }
+    api "org.testng:testng:${testng_version}"
 }