Update DJL release version to 0.8.0

Change-Id: I4b352458c1ecf768a0e8aa187741c3fc1fe1d0f5

android/README.md

@@ -15,9 +15,9 @@ In gradle, you can include the snapshot repository and add the 4 modules in your
 
 ```
 dependencies {
-    implementation "ai.djl:api:0.7.0"
-    implementation "ai.djl.android:core:0.7.0"
-    androidRuntimeOnly "ai.djl.pytorch:pytorch-engine:0.7.0"
-    androidRuntimeOnly "ai.djl.android:pytorch-native:0.7.0"
+    implementation "ai.djl:api:0.8.0"
+    implementation "ai.djl.android:core:0.8.0"
+    androidRuntimeOnly "ai.djl.pytorch:pytorch-engine:0.8.0"
+    androidRuntimeOnly "ai.djl.android:pytorch-native:0.8.0"
 }
 ```

api/README.md

@@ -35,7 +35,7 @@ You can pull the DJL API from the central Maven repository by including the foll
 <dependency>
     <groupId>ai.djl</groupId>
     <artifactId>api</artifactId>
-    <version>0.7.0</version>
+    <version>0.8.0</version>
 </dependency>
 ```
 

basicdataset/README.md

@@ -39,7 +39,7 @@ You can pull the module from the central Maven repository by including the follo
 <dependency>
     <groupId>ai.djl</groupId>
     <artifactId>basicdataset</artifactId>
-    <version>0.7.0</version>
+    <version>0.8.0</version>
 </dependency>
 ```
 

bom/README.md

@@ -22,7 +22,7 @@ will need to mention the type as pom and the scope as import) as the following:
         <dependency>
             <groupId>ai.djl</groupId>
             <artifactId>bom</artifactId>
-            <version>0.7.0</version>
+            <version>0.8.0</version>
             <type>pom</type>
             <scope>import</scope>
         </dependency>
@@ -38,7 +38,7 @@ will need to mention the type as pom and the scope as import) as the following:
         <dependency>
             <groupId>ai.djl</groupId>
             <artifactId>bom</artifactId>
-            <version>0.7.0</version>
+            <version>0.8.0</version>
             <type>pom</type>
             <scope>import</scope>
         </dependency>
@@ -70,7 +70,7 @@ will need to mention the type as pom and the scope as import) as the following:
 - First you need add BOM into your build.gradle file as the following:
 
 ```
-    implementation platform("ai.djl:bom:0.7.0")
+    implementation platform("ai.djl:bom:0.8.0")
 ```
 
 - Then you import the desired DJL modules into to you pom.xml file (no version is needed):

docs/development/development_guideline.md

@@ -159,7 +159,7 @@ You can create your own NDArray renderer as follows:
 Please make sure to:
 
 - Check the "On-demand" option, which causes IntelliJ to only render the NDArray when you click on the variable.
-- Change the "Use following expression" field to something like [toDebugString(100, 10, 10, 20)](https://javadoc.io/static/ai.djl/api/0.7.0/ai/djl/ndarray/NDArray.html#toDebugString-int-int-int-int-)
+- Change the "Use following expression" field to something like [toDebugString(100, 10, 10, 20)](https://javadoc.io/static/ai.djl/api/0.8.0/ai/djl/ndarray/NDArray.html#toDebugString-int-int-int-int-)
 if you want to adjust the range of NDArray's debug output.
 
 ## Common Problems

docs/development/how_to_use_dataset.md

@@ -118,8 +118,8 @@ api group: 'org.apache.commons', name: 'commons-csv', version: '1.7'
 In order to extend the dataset, the following dependencies are required:
 
 ```
-api "ai.djl:api:0.7.0"
-api "ai.djl:basicdataset:0.7.0"
+api "ai.djl:api:0.8.0"
+api "ai.djl:basicdataset:0.8.0"
 ```
 
 There are three parts we need to implement for CSVDataset.

docs/development/memory_management.md

@@ -36,7 +36,7 @@ The intermediate NDArrays involving in training case are usually
 
 In general, all the parameters in the model should be associated with Model level NDManager.
 All of the input and output NDArrays should be associated with one NDManager which is one level down to the model NDManager.
-Please check if you call [batch.close()](https://javadoc.io/static/ai.djl/api/0.7.0/ai/djl/training/dataset/Batch.html#close--)
+Please check if you call [batch.close()](https://javadoc.io/static/ai.djl/api/0.8.0/ai/djl/training/dataset/Batch.html#close--)
 to release one batch of the dataset at the end of each batch.
 If you still see the memory grows as the training process goes, it is most likely that intermediate NDArrays are attached to the Model(Block) parameter level.
 As a result, those NDArrays would not closed until the training is finished.

docs/development/troubleshooting.md

@@ -28,7 +28,7 @@ For example, adding MXNet engine dependencies:
 Gradle:
 
 ```
-implementation "ai.djl.mxnet:mxnet-engine:0.7.0"
+implementation "ai.djl.mxnet:mxnet-engine:0.8.0"
 // See https://github.com/awslabs/djl/blob/master/mxnet/mxnet-engine/README.md for more MXNet library selection options
 runtimeOnly "ai.djl.mxnet:mxnet-native-auto:1.7.0-backport"
 ```

docs/load_model.md

@@ -176,7 +176,7 @@ Here is a few tips you can use to help you debug model loading issue:
 See [here](development/configure_logging.md#configure-logging-level) for how to enable debug log
 
 #### List models programmatically in your code
-You can use [ModelZoo.listModels()](https://javadoc.io/static/ai.djl/api/0.7.0/ai/djl/repository/zoo/ModelZoo.html#listModels--) API to query available models.
+You can use [ModelZoo.listModels()](https://javadoc.io/static/ai.djl/api/0.8.0/ai/djl/repository/zoo/ModelZoo.html#listModels--) API to query available models.
 
 #### List available models using DJL command line
 

docs/onnxruntime/hybrid_engine.md

@@ -11,14 +11,14 @@ The minimum dependencies for the ONNX Runtime Engine are:
 #### gradle
 
 ```
-runtimeOnly "ai.djl.onnxruntime:onnxruntime-engine:0.7.0"
+runtimeOnly "ai.djl.onnxruntime:onnxruntime-engine:0.8.0"
 runtimeOnly "ai.djl.onnxruntime:onnxruntime-native-auto:1.3.0"
 ```
 
 To use it along with Apache MXNet for additional API support, add the following two dependencies:
 
 ```
-runtimeOnly "ai.djl.mxnet:mxnet-engine:0.7.0"
+runtimeOnly "ai.djl.mxnet:mxnet-engine:0.8.0"
 runtimeOnly "ai.djl.mxnet:mxnet-native-auto:1.7.0-backport"
 ```
 

extensions/aws-ai/README.md

@@ -58,6 +58,6 @@ You can pull the module from the central Maven repository by including the follo
 <dependency>
     <groupId>ai.djl.aws</groupId>
     <artifactId>aws-ai</artifactId>
-    <version>0.7.0</version>
+    <version>0.8.0</version>
 </dependency>
 ```

extensions/fasttext/README.md

@@ -29,7 +29,7 @@ You can pull the fastText engine from the central Maven repository by including
 <dependency>
     <groupId>ai.djl.fasttext</groupId>
     <artifactId>fasttext-engine</artifactId>
-    <version>0.7.0</version>
+    <version>0.8.0</version>
 </dependency>
 ```
 

extensions/hadoop/README.md

@@ -52,6 +52,6 @@ You can pull the module from the central Maven repository by including the follo
 <dependency>
     <groupId>ai.djl.hadoop</groupId>
     <artifactId>hadoop</artifactId>
-    <version>0.7.0</version>
+    <version>0.8.0</version>
 </dependency>
 ```

extensions/sentencepiece/README.md

@@ -21,6 +21,6 @@ You can pull the module from the central Maven repository by including the follo
 <dependency>
     <groupId>ai.djl.sentencepiece</groupId>
     <artifactId>sentencepiece</artifactId>
-    <version>0.7.0</version>
+    <version>0.8.0</version>
 </dependency>
 ```

jupyter/BERTQA.ipynb

@@ -46,11 +46,11 @@
    "source": [
     "// %mavenRepo snapshots https://oss.sonatype.org/content/repositories/snapshots/\n",
     "\n",
-    "%maven ai.djl:api:0.7.0\n",
-    "%maven ai.djl.mxnet:mxnet-engine:0.7.0\n",
-    "%maven ai.djl.mxnet:mxnet-model-zoo:0.7.0\n",
-    "%maven ai.djl.pytorch:pytorch-engine:0.7.0\n",
-    "%maven ai.djl.pytorch:pytorch-model-zoo:0.7.0\n",
+    "%maven ai.djl:api:0.8.0\n",
+    "%maven ai.djl.mxnet:mxnet-engine:0.8.0\n",
+    "%maven ai.djl.mxnet:mxnet-model-zoo:0.8.0\n",
+    "%maven ai.djl.pytorch:pytorch-engine:0.8.0\n",
+    "%maven ai.djl.pytorch:pytorch-model-zoo:0.8.0\n",
     "%maven org.slf4j:slf4j-api:1.7.26\n",
     "%maven org.slf4j:slf4j-simple:1.7.26\n",
     "%maven net.java.dev.jna:jna:5.3.0\n",

jupyter/load_mxnet_model.ipynb

@@ -22,10 +22,10 @@
    "source": [
     "// %mavenRepo snapshots https://oss.sonatype.org/content/repositories/snapshots/\n",
     "\n",
-    "%maven ai.djl:api:0.7.0\n",
-    "%maven ai.djl:model-zoo:0.7.0\n",
-    "%maven ai.djl.mxnet:mxnet-engine:0.7.0\n",
-    "%maven ai.djl.mxnet:mxnet-model-zoo:0.7.0\n",
+    "%maven ai.djl:api:0.8.0\n",
+    "%maven ai.djl:model-zoo:0.8.0\n",
+    "%maven ai.djl.mxnet:mxnet-engine:0.8.0\n",
+    "%maven ai.djl.mxnet:mxnet-model-zoo:0.8.0\n",
     "%maven org.slf4j:slf4j-api:1.7.26\n",
     "%maven org.slf4j:slf4j-simple:1.7.26\n",
     "%maven net.java.dev.jna:jna:5.3.0\n",

jupyter/load_pytorch_model.ipynb

@@ -25,8 +25,8 @@
    "source": [
     "// %mavenRepo snapshots https://oss.sonatype.org/content/repositories/snapshots/\n",
     "\n",
-    "%maven ai.djl:api:0.7.0\n",
-    "%maven ai.djl.pytorch:pytorch-engine:0.7.0\n",
+    "%maven ai.djl:api:0.8.0\n",
+    "%maven ai.djl.pytorch:pytorch-engine:0.8.0\n",
     "%maven org.slf4j:slf4j-api:1.7.26\n",
     "%maven org.slf4j:slf4j-simple:1.7.26\n",
     "%maven net.java.dev.jna:jna:5.3.0\n",
@@ -111,7 +111,7 @@
     "...\n",
     "```\n",
     "\n",
-    "Then, we will use this pipeline to create the [`Translator`](https://javadoc.io/static/ai.djl/api/0.7.0/index.html?ai/djl/translate/Translator.html)"
+    "Then, we will use this pipeline to create the [`Translator`](https://javadoc.io/static/ai.djl/api/0.8.0/index.html?ai/djl/translate/Translator.html)"
    ]
   },
   {
@@ -140,7 +140,7 @@
    "source": [
     "## Step 3: Load your model\n",
     "\n",
-    "Next, we will set the model zoo location to the `build/pytorch_models` directory we saved the model to. You can also create your own [`Repository`](https://javadoc.io/static/ai.djl/repository/0.7.0/index.html?ai/djl/repository/Repository.html) to avoid manually managing files.\n",
+    "Next, we will set the model zoo location to the `build/pytorch_models` directory we saved the model to. You can also create your own [`Repository`](https://javadoc.io/static/ai.djl/repository/0.8.0/index.html?ai/djl/repository/Repository.html) to avoid manually managing files.\n",
     "\n",
     "Next, we add some search criteria to find the resnet18 model and load it."
    ]

jupyter/mxnet/load_your_own_mxnet_bert.ipynb

@@ -41,9 +41,9 @@
    "source": [
     "// %mavenRepo snapshots https://oss.sonatype.org/content/repositories/snapshots/\n",
     "\n",
-    "%maven ai.djl:api:0.7.0\n",
-    "%maven ai.djl.mxnet:mxnet-engine:0.7.0\n",
-    "%maven ai.djl.mxnet:mxnet-model-zoo:0.7.0\n",
+    "%maven ai.djl:api:0.8.0\n",
+    "%maven ai.djl.mxnet:mxnet-engine:0.8.0\n",
+    "%maven ai.djl.mxnet:mxnet-model-zoo:0.8.0\n",
     "%maven org.slf4j:slf4j-api:1.7.26\n",
     "%maven org.slf4j:slf4j-simple:1.7.26\n",
     "%maven net.java.dev.jna:jna:5.3.0\n",
@@ -296,7 +296,7 @@
    "cell_type": "markdown",
    "metadata": {},
    "source": [
-    "Armed with the needed knowledge, you can write an implementation of the `Translator` interface. `BertTranslator` uses the code snippets explained previously to implement the `processInput`method. For more information, see [`NDManager`](https://javadoc.io/static/ai.djl/api/0.7.0/index.html?ai/djl/ndarray/NDManager.html).\n",
+    "Armed with the needed knowledge, you can write an implementation of the `Translator` interface. `BertTranslator` uses the code snippets explained previously to implement the `processInput`method. For more information, see [`NDManager`](https://javadoc.io/static/ai.djl/api/0.8.0/index.html?ai/djl/ndarray/NDManager.html).\n",
     "\n",
     "```\n",
     "manager.create(Number[] data, Shape)\n",
@@ -369,7 +369,7 @@
    "source": [
     "Congrats! You have created your first Translator! We have pre-filled the `processOutput()` function to process the `NDList` and return it in a desired format. `processInput()` and `processOutput()` offer the flexibility to get the predictions from the model in any format you desire. \n",
     "\n",
-    "With the Translator implemented, you need to bring up the predictor that uses your `Translator` to start making predictions. You can find the usage for `Predictor` in the [Predictor Javadoc](https://javadoc.io/static/ai.djl/api/0.7.0/index.html?ai/djl/inference/Predictor.html). Create a translator and use the `question` and `resourceDocument` provided previously."
+    "With the Translator implemented, you need to bring up the predictor that uses your `Translator` to start making predictions. You can find the usage for `Predictor` in the [Predictor Javadoc](https://javadoc.io/static/ai.djl/api/0.8.0/index.html?ai/djl/inference/Predictor.html). Create a translator and use the `question` and `resourceDocument` provided previously."
    ]
   },
   {

jupyter/object_detection_with_model_zoo.ipynb

@@ -21,9 +21,9 @@
    "source": [
     "// %mavenRepo snapshots https://oss.sonatype.org/content/repositories/snapshots/\n",
     "\n",
-    "%maven ai.djl:api:0.7.0\n",
-    "%maven ai.djl.mxnet:mxnet-engine:0.7.0\n",
-    "%maven ai.djl.mxnet:mxnet-model-zoo:0.7.0\n",
+    "%maven ai.djl:api:0.8.0\n",
+    "%maven ai.djl.mxnet:mxnet-engine:0.8.0\n",
+    "%maven ai.djl.mxnet:mxnet-model-zoo:0.8.0\n",
     "%maven org.slf4j:slf4j-api:1.7.26\n",
     "%maven org.slf4j:slf4j-simple:1.7.26\n",
     "%maven net.java.dev.jna:jna:5.3.0\n",

jupyter/onnxruntime/machine_learning_with_ONNXRuntime.ipynb

@@ -54,9 +54,9 @@
    "source": [
     "// %mavenRepo snapshots https://oss.sonatype.org/content/repositories/snapshots/\n",
     "\n",
-    "%maven ai.djl:api:0.7.0\n",
-    "%maven ai.djl.onnxruntime:onnxruntime-engine:0.7.0\n",
-    "%maven ai.djl.pytorch:pytorch-engine:0.7.0\n",
+    "%maven ai.djl:api:0.8.0\n",
+    "%maven ai.djl.onnxruntime:onnxruntime-engine:0.8.0\n",
+    "%maven ai.djl.pytorch:pytorch-engine:0.8.0\n",
     "%maven org.slf4j:slf4j-api:1.7.26\n",
     "%maven org.slf4j:slf4j-simple:1.7.26\n",
     "\n",

jupyter/pytorch/load_your_own_pytorch_bert.ipynb

@@ -41,9 +41,9 @@
    "source": [
     "// %mavenRepo snapshots https://oss.sonatype.org/content/repositories/snapshots/\n",
     "\n",
-    "%maven ai.djl:api:0.7.0\n",
-    "%maven ai.djl.pytorch:pytorch-engine:0.7.0\n",
-    "%maven ai.djl.pytorch:pytorch-model-zoo:0.7.0\n",
+    "%maven ai.djl:api:0.8.0\n",
+    "%maven ai.djl.pytorch:pytorch-engine:0.8.0\n",
+    "%maven ai.djl.pytorch:pytorch-model-zoo:0.8.0\n",
     "%maven org.slf4j:slf4j-api:1.7.26\n",
     "%maven org.slf4j:slf4j-simple:1.7.26\n",
     "%maven net.java.dev.jna:jna:5.3.0\n",
@@ -284,7 +284,7 @@
    "cell_type": "markdown",
    "metadata": {},
    "source": [
-    "Armed with the needed knowledge, you can write an implementation of the `Translator` interface. `BertTranslator` uses the code snippets explained previously to implement the `processInput`method. For more information, see [`NDManager`](https://javadoc.io/static/ai.djl/api/0.7.0/index.html?ai/djl/ndarray/NDManager.html).\n",
+    "Armed with the needed knowledge, you can write an implementation of the `Translator` interface. `BertTranslator` uses the code snippets explained previously to implement the `processInput`method. For more information, see [`NDManager`](https://javadoc.io/static/ai.djl/api/0.8.0/index.html?ai/djl/ndarray/NDManager.html).\n",
     "\n",
     "```\n",
     "manager.create(Number[] data, Shape)\n",
@@ -347,7 +347,7 @@
    "source": [
     "Congrats! You have created your first Translator! We have pre-filled the `processOutput()` function to process the `NDList` and return it in a desired format. `processInput()` and `processOutput()` offer the flexibility to get the predictions from the model in any format you desire. \n",
     "\n",
-    "With the Translator implemented, you need to bring up the predictor that uses your `Translator` to start making predictions. You can find the usage for `Predictor` in the [Predictor Javadoc](https://javadoc.io/static/ai.djl/api/0.7.0/index.html?ai/djl/inference/Predictor.html). Create a translator and use the `question` and `resourceDocument` provided previously."
+    "With the Translator implemented, you need to bring up the predictor that uses your `Translator` to start making predictions. You can find the usage for `Predictor` in the [Predictor Javadoc](https://javadoc.io/static/ai.djl/api/0.8.0/index.html?ai/djl/inference/Predictor.html). Create a translator and use the `question` and `resourceDocument` provided previously."
    ]
   },
   {

jupyter/tensorflow/pneumonia_detection.ipynb

@@ -36,10 +36,10 @@
    "source": [
     "// %mavenRepo snapshots https://oss.sonatype.org/content/repositories/snapshots/\n",
     "\n",
-    "%maven ai.djl:api:0.7.0\n",
-    "%maven ai.djl.tensorflow:tensorflow-api:0.7.0\n",
-    "%maven ai.djl.tensorflow:tensorflow-engine:0.7.0\n",
-    "%maven ai.djl.tensorflow:tensorflow-model-zoo:0.7.0\n",
+    "%maven ai.djl:api:0.8.0\n",
+    "%maven ai.djl.tensorflow:tensorflow-api:0.8.0\n",
+    "%maven ai.djl.tensorflow:tensorflow-engine:0.8.0\n",
+    "%maven ai.djl.tensorflow:tensorflow-model-zoo:0.8.0\n",
     "%maven org.bytedeco:javacpp:1.5.4\n",
     "%maven org.slf4j:slf4j-simple:1.7.26\n",
     "\n",

jupyter/transfer_learning_on_cifar10.ipynb

@@ -35,10 +35,10 @@
    "source": [
     "// %mavenRepo snapshots https://oss.sonatype.org/content/repositories/snapshots/\n",
     "\n",
-    "%maven ai.djl:api:0.7.0\n",
-    "%maven ai.djl:basicdataset:0.7.0\n",
-    "%maven ai.djl.mxnet:mxnet-engine:0.7.0\n",
-    "%maven ai.djl.mxnet:mxnet-model-zoo:0.7.0\n",
+    "%maven ai.djl:api:0.8.0\n",
+    "%maven ai.djl:basicdataset:0.8.0\n",
+    "%maven ai.djl.mxnet:mxnet-engine:0.8.0\n",
+    "%maven ai.djl.mxnet:mxnet-model-zoo:0.8.0\n",
     "%maven org.slf4j:slf4j-api:1.7.26\n",
     "%maven org.slf4j:slf4j-simple:1.7.26\n",
     "%maven net.java.dev.jna:jna:5.3.0\n",