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
- Supports ExecuTorch 0.2 (see ExecuTorch doc for examples)
- Enhancements
- Improved Model Conversion Speed
- Expanded Operation Translation Coverage
- add
torch.narrow
- add
torch.adaptive_avg_pool1d
andtorch.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
whenk
is variable
- add
Thanks to our ExecuTorch partners and our open-source community: @KrassCodes @M-Quadra @teelrabbit @minimalic @alealv @ChinChangYang @pcuenca