Bump api from 0.14.0 to 0.16.0

[dependabot]

Bumps api from 0.14.0 to 0.16.0.

Release notes

Sourced from api's releases.

DJL v0.15.0 release

DJL v0.15.0 updates the engines PyTorch to 1.10.0, ONNXRuntime to 1.10.0, TensorFlow to 2.7.0, TensorFlowLite to 2.6.2 and introduces several new features:

Key Features

• Introduces Huggingface tokenizers extension which allows user to leverage high performance fast tokenizer in Java
• Upgrades PyTorch engine to 1.10.0 with CUDA 11.3 support
• Upgrades TensorFlow to 2.7.0 with CUDA 11.3 support
• Upgrades ONNXRuntime engine to 1.10.0
• Upgrades TensorFlowLite to 2.6.2
• Provides better PyTorch engine backward compatibility support
• Adds load model from InputStream support
• Adds Windows support for SentencePiece
• Removes -auto packages to simplify DJL dependencies
• Fixes log4j CVEs

Enhancement

• Improves PyTorch engine:
  • Adds support to load custom build PyTorch native library from specified location
  • Adds support to use precxx11 version of PyTorch on GPU
  • Provides offline native package for older version of PyTorch to run with latest DJL (#1385)
  • Report correct engine version for custom build PyTorch native library
  • Adds Tuple support to IValue (#1436)
• Adds support to load model from InputStream for some of the engines (#1400):
  • Adds load from InputStream for PyTorch model
  • Adds load from InputStream for TensorFlowLite model (#1402)
  • Adds load from InputStream for ONNXRuntime model (#1402)
  • Adds load from InputStream for SentencePiece (#1139)
• Introduces several new features in djl-serving:
  • Automatically detect model’s engine
  • Reduces netty dependencies to minimize package size
  • Installs engine dependency on-demand for non-commonly used engines
  • Adds support for nested folder in model archive file
  • Released djl-serving to homebrew
• Introduces server new features in djl-bench
  • Release djl-bench to homebrew and snapcraft
• Improve opencv extension to expose API from opencv to end users
• Introduces several API improvements:
  • Improves TrainingResult with toString() print out (#1369)
  • Allows to register engine at runtime (#1386)
  • Allows to dynamic add model zoo (#1397)
  • Creates IndexEvaluator and IndexLoss (#1414)
  • Introduces Huggingface Tokenizer (#1406)
• Publishes several new docker images to dockerhub (https://hub.docker.com/u/deepjavalibrary)
  • djl-serving docker image
  • djl-serving for inferentia docker image
  • DJL windows docker image with jdk11

Documentation and examples

... (truncated)

Commits

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[dependabot]

Superseded by #27.