Coremltools

Core ML Tools 6.2 Release Note

* Support new PyTorch version: `torch==1.13.1` and `torchvision==0.14.1`.
* New ops support:
* New PyTorch ops support: 1-D and N-D FFT / RFFT / IFFT / IRFFT in `torch.fft`, `torchvision.ops.nms`, `torch.atan2`, `torch.bitwise_and`, `torch.numel`,
* New TensorFlow ops support: FFT / RFFT / IFFT / IRFFT in `tf.signal`, `tf.tensor_scatter_nd_add`.
* Existing ops improvements:
* Supports int input for `clamp` op.
* Supports dynamic `topk` (k not determined during compile time).
* Supports `padding='valid'` in PyTorch convolution.
* Supports PyTorch Adaptive Pooling.
* Supports numpy v1.24.0 (1718)
* Add int8 affine quantization for the compression_utils.
* Various other bug fixes, optimizations and improvements.

Special thanks to our external contributors for this release: fukatani, ChinChangYang, danvargg, bhushan23 and cjblocker.

* Support for TensorFlow `2.10`.
* New PyTorch ops supported: `baddbmm`, `glu`, `hstack`, `remainder`, `weight_norm`, `hann_window`, `randint`, `cross`, `trace`, and `reshape_as.`
* Avoid root logger and use the coremltools logger instead.
* Support dynamic input shapes for PyTorch `repeat` and `expand` op.
* Enhance translation of torch `where` op with only one input.
* Add support for PyTorch einsum equation: `'bhcq,bhck→bhqk’`.
* Optimization graph pass improvement
* 3D convolution batchnorm fusion
* Consecutive relu fusion
* Noop elimination
* Actively catch the tensor which has rank >= 6 and error out
* Various other bug fixes, optimizations and improvements.

Special thanks to our external contributors for this release: fukatani, piraka9011, giorgiop, hollance, SangamSwadiK, RobertRiachi, waylybaye, GaganNarula, and sunnypurewal.

* 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.

* Support for new MIL ops added in iOS16/macOS13: `pixel_unshuffle`, `resample`, `topk`
* Update coremltools python bindings to work with GRAYSCALE_FLOAT16 image datatype of CoreML
* New compute unit enum type: `CPU_AND_NE`
* New PyTorch ops: `AdaptiveAvgPool2d`, `cosine_similarity`, `eq`, `linalg.norm`, `linalg.matrix_norm`, `linalg.vector_norm`, `ne`, `PixelUnshuffle`
* Support for `identity_n` TensorFlow op
* Various other bug fixes, optimizations and improvements.

* MLProgram compression: affine quantization, palettize, sparsify. See `coremltools.compression_utils`.
* 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.
* Support for PyTorch 1.11.0.
* Support for TensorFlow 2.8.
* [API Breaking Change] Remove `useCPUOnly` parameter from `coremltools.convert` and `coremltools.models.MLModel`. Use `coremltools.ComputeUnit` instead.
* Support for many new PyTorch and TensorFlow layers
* Many bug fixes and enhancements.


**Known issues**
* While conversion and CoreML models with Grayscale Float16 images should work with ios16/macos13 beta, the coremltools-CoreML python binding has an issue which would cause the `predict` API in coremltools to crash when the either the input or output is of type grayscale float16
* The new Compute unit configuration `MLComputeUnitsCPUAndNeuralEngine` is not available in coremltools yet

* Support latest version (1.10.2) of PyTorch
* Support TensorFlow 2.6.2
* Support New PyTorch ops:
* `bitwise_not`
* `dim`
* `dot`
* `eye`
* `fill`
* `hardswish`
* `linspace`
* `mv`
* `new_full`
* `new_zeros`
* `rrelu`
* `selu`
* Support TensorFlow ops
* `DivNoNan`
* `Log1p`
* `SparseSoftmaxCrossEntropyWithLogits`
* Various bug fixes, clean ups and optimizations.
* This is the final coremltools version to support Python 3.5