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MLProgram compression: affine quantization, palettize, sparsify. See coremltools.compression_utils
Python 3.10 support.
Support for latest scikit-learn version (1.1.2).
Support for latest PyTorch version (1.12.1).
Support for TensorFlow 2.8.
Support for options to specify input and output data types, for both images and multiarrays
Update coremltools python bindings to work with GRAYSCALE_FLOAT16 image datatype of CoreML
New options to set input and output types to multi array of type float16, grayscale image of type float16 and set output type as images, similar to the coremltools.ImageType used with inputs.
New compute unit enum type: CPU_AND_NE to select the model runtime to the Neural engine and CPU.
Support for several new TensorFlow and PyTorch ops.
Changes to opset (available from iOS16, macOS13)
New MIL ops: full_like, resample, reshape_like, pixel_unshuffle, topk
Existing MIL ops with new functionality: crop_resize, gather, gather_nd, topk, upsample_bilinear.
API Breaking Changes:
Do not assume source prediction column is “predictions”, fixes #58.
Remove useCPUOnly parameter from coremltools.convert and coremltools.models.MLModel. Use coremltools.ComputeUnit instead.
Remove ONNX support.
Remove multi-backend Keras support.
Various other bug fixes, optimizations and improvements.