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kevmo314 / magic-copy

Magic Copy is a Chrome extension that uses Meta's Segment Anything Model to extract a foreground object from an image and copy it to the clipboard.
MIT License
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build(deps): bump onnxruntime-web from 1.14.0 to 1.16.3 #85

Closed dependabot[bot] closed 8 months ago

dependabot[bot] commented 9 months ago

Bumps onnxruntime-web from 1.14.0 to 1.16.3.

Release notes

Sourced from onnxruntime-web's releases.

ONNX Runtime v1.16.3

What's Changed

  1. Stable Diffusion XL demo update by @​tianleiwu in microsoft/onnxruntime#18496
  2. Fixed a memory leak issue(#18466) in TensorRT EP by @​chilo-ms in microsoft/onnxruntime#18467
  3. Fix a use-after-free bug in SaveInputOutputNamesToNodeMapping function by @​snnn in microsoft/onnxruntime#18456 . The issue was found by AddressSanitizer.

ONNX Runtime v1.16.2

The patch release includes updates on:

  • Performance optimizations for Llama2 on CUDA EP and DirectML EP
  • Performance optimizations for Stable Diffusion XL model for CUDA EP
    • Demos for text to image generation
  • Mobile bug fixes for crash on some older 64-bit ARM devices and AOT inlining issue on iOS with C# bindings
  • TensorRT EP bug fixes for user provided compute stream and stream synchronization

ONNX Runtime v1.16.1

Patch release for 1.16

  • Fix type of weights and activations in the ONNX quantizer
  • Fix quantization bug in historic quantizer #17619
  • Enable session option access in nodejs API
  • Update nodejs to v18
  • Align ONNX Runtime extensions inclusion in source and build
  • Limit per thread context to 1 in the TensorRT EP to avoid error caused by input shape changes

ONNX Runtime v1.16.0

General

  • Support for serialization of models >=2GB

APIs

  • New session option to disable default CPU EP fallback session.disable_cpu_ep_fallback
  • Java
    • Support for fp16 and bf16 tensors as inputs and outputs, along with utilities to convert between these and fp32 data. On JDK 20 and newer the fp16 conversion methods use the JDK's Float.float16ToFloat and Float.floatToFloat16 methods which can be hardware accelerated and vectorized on some platforms.
    • Support for external initializers so that large models that can be instantiated without filesystem access
  • C#
    • Expose OrtValue API as the new preferred API to run inference in C#. This reduces garbage and exposes direct native memory access via Slice like interfaces.
    • Make Float16 and BFloat16 full featured fp16 interfaces that support conversion and expose floating properties (e.g. IsNaN, IsInfinity, etc)
  • C++
    • Make Float16_t and BFloat16_t full featured fp16 interfaces that support conversion and expose floating properties (e.g. IsNaN, IsInfinity, etc)

Performance

  • Improve LLM quantization accuracy with smoothquant

... (truncated)

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dependabot[bot] commented 8 months ago

Superseded by #96.