coremltools 7.0b2

• The default neural network backend is now mlprogram for iOS15/macOS12. Previously calling coremltools.convert() without providing the convert_to or the minimum_deployment_target arguments, used the lowest deployment target (iOS11/macOS10.13) and the neuralnetwork backend. Now the conversion process will default to iOS15/macOS12 and the mlprogram backend. You can change this behavior by providing a minimum_deployment_target or convert_to value.
• Changes default I/O type for Neural Networks to FP16 for iOS16/macOS13 or later when mlprogram backend is used.
• Changes upper input range behavior when backend is mlprogram:
  • If RangeDim is used and no upper-bound is set (with a positive number), an exception will be raised.
  • If the user does not use the inputs parameter but there are undetermined dim in input shape (for example, TF with "None" in input placeholder), it will be sanitized to a finite number (default_size + 1) and raise a warning.
• New utility method for getting weight metadata: coremltools.optimize.coreml.get_weights_metadata. This information can be used to customize optimization across ops when using coremltools.optimize.coreml APIs.
• Support for new PyTorch ops: repeat_interleave and unflatten.
• New and updated iOS17/macOS14 ops: batch_norm, conv, conv_transpose, expand_dims, gru, instance_norm, inverse, l2_norm, layer_norm, linear, local_response_norm, log, lstm, matmul, reshape_like, resample, resize, reverse, reverse_sequence, rnn, rsqrt, slice_by_index, slice_by_size, sliding_windows, squeeze, transpose.
• Various other bug fixes, enhancements, clean ups and optimizations.

Special thanks to our external contributors for this release: @fukatani, @pcuenca, @KWiecko, @comeweber and @sercand