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Upgrade dependency version and update README (#2005)
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* Upgrade dependency versions

* Update README files
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xyang16 authored Sep 9, 2022
1 parent 5ca256a commit 4fa0ccf
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Showing 9 changed files with 16 additions and 14 deletions.
4 changes: 2 additions & 2 deletions basicdataset/README.md
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Expand Up @@ -41,12 +41,12 @@ images that not supported by default JDK, you can consider add the following dep
<dependency>
<groupId>com.twelvemonkeys.imageio</groupId>
<artifactId>imageio-jpeg</artifactId>
<version>3.5</version>
<version>3.8.3</version>
</dependency>
<dependency>
<groupId>com.twelvemonkeys.imageio</groupId>
<artifactId>imageio-bmp</artifactId>
<version>3.5</version>
<version>3.8.3</version>
</dependency>
...
```
2 changes: 1 addition & 1 deletion engines/ml/xgboost/README.md
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Expand Up @@ -17,7 +17,7 @@ User can only create two-dimension NDArray to form as the input.

## Documentation

The latest javadocs can be found on [here](https://javadoc.io/doc/ai.djl.onnxruntime/onnxruntime-engine/latest/index.html).
The latest javadocs can be found on [here](https://javadoc.io/doc/ai.djl.ml.xgboost/xgboost/latest/index.html).

You can also build the latest javadocs locally using the following command:

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2 changes: 1 addition & 1 deletion engines/onnxruntime/onnxruntime-engine/README.md
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Expand Up @@ -3,7 +3,7 @@
## Overview
This module contains the Deep Java Library (DJL) EngineProvider for ONNX Runtime.

It is based off the [ONNX Runtime Deep Learning Framework](https://microsoft.github.io/onnxruntime/).
It is based off the [ONNX Runtime Deep Learning Framework](https://onnxruntime.ai/).


We don't recommend developers use classes within this module directly.
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2 changes: 1 addition & 1 deletion extensions/aws-ai/README.md
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Expand Up @@ -41,7 +41,7 @@ If you want to customize your AWS credentials and region, you can manually regis

## Documentation

The latest javadocs can be found on [here](https://javadoc.io/ai.djl.aws/aws-ai/latest/index.html).
The latest javadocs can be found on [here](https://javadoc.io/doc/ai.djl.aws/aws-ai/latest/index.html).

You can also build the latest javadocs locally using the following command:

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2 changes: 1 addition & 1 deletion extensions/hadoop/README.md
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Expand Up @@ -34,7 +34,7 @@ If you want to customize your Hadoop configuration, you can manually register a

## Documentation

The latest javadocs can be found on [here](https://javadoc.io/ai.djl.hadoop/hadoop/latest/index.html).
The latest javadocs can be found on [here](https://javadoc.io/doc/ai.djl.hadoop/hadoop/latest/index.html).

You can also build the latest javadocs locally using the following command:

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1 change: 1 addition & 0 deletions extensions/hadoop/build.gradle
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Expand Up @@ -9,6 +9,7 @@ dependencies {

testImplementation project(":engines:mxnet:mxnet-engine")
testImplementation "org.apache.hadoop:hadoop-minicluster:${hadoop_version}"
testImplementation "org.mockito:mockito-core:${mockito_version}"
testImplementation(project(":testing"))

testImplementation "org.testng:testng:${testng_version}"
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2 changes: 1 addition & 1 deletion extensions/sentencepiece/README.md
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Expand Up @@ -2,7 +2,7 @@

This module contains the NLP support with SentencePiece implementation.

This is an implementation from [SentencePiece's](https://github.com/google/sentencepiece) C++ API.
This is an implementation from [SentencePiece](https://github.com/google/sentencepiece)'s C++ API.

## Documentation

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4 changes: 2 additions & 2 deletions extensions/timeseries/README.md
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@@ -1,6 +1,6 @@
# TimeSeries support

This module contains the time series model support extension with [gluon-ts](https://github.com/awslabs/gluon-ts).
This module contains the time series model support extension with [GluonTS](https://github.com/awslabs/gluonts).

Right now, the package provides the `BaseTimeSeriesTranslator` and transform package that allows you to do inference from your pre-trained time series model.

Expand Down Expand Up @@ -81,7 +81,7 @@ The following pseudocode demonstrates how to create a `DeepARTranslator` with `a

If you want to customize your own time series model translator, you can easily use the transform package for your data preprocess.

See [examples](../src/main/java/ai/djl/timeseries/examples) for more details.
See [examples](../../examples) for more details.

We plan to add the following features in the future:

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11 changes: 6 additions & 5 deletions gradle.properties
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Expand Up @@ -31,16 +31,17 @@ commons_cli_version=1.5.0
commons_compress_version=1.21
commons_csv_version=1.9.0
commons_logging_version=1.2
gson_version=2.9.0
jna_version=5.11.0
gson_version=2.9.1
jna_version=5.12.1
slf4j_version=1.7.36
log4j_slf4j_version=2.18.0
awssdk_version=2.17.151
hadoop_version=3.3.1
awssdk_version=2.17.269
hadoop_version=3.3.4
javacpp_version=1.5.6
protobuf_version=3.19.2
protobuf_version=3.21.5
tablesaw_version=0.43.1

antlr_version=4.9.3
testng_version=7.5
junit_version=4.13.2
mockito_version=4.8.0

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