coremltools 7.2

• New Features
  • Supports ExecuTorch 0.2 (see ExecuTorch doc for examples)
    • Core ML Partitioner: If a PyTorch model is partially supported with Core ML, then Core ML partitioner can determine the supported part and have ExecuTorch delegate to Core ML.
    • Core ML Quantizer: Quantize PyTorch models in Core ML favored scheme
• Enhancements
  • Improved Model Conversion Speed
  • Expanded Operation Translation Coverage
    • add torch.narrow
    • add torch.adaptive_avg_pool1d and torch.adaptive_max_pool1d
    • add torch.numpy_t (i.e. the numpy-style transpose operator .T)
    • enhance torch.clamp_min for integer data type
    • enhance torch.add for complex data type
    • enhance tf.math.top_k when k is variable

Thanks to our ExecuTorch partners and our open-source community: @KrassCodes @M-Quadra @teelrabbit @minimalic @alealv @ChinChangYang @pcuenca