v2.0.0

Switched from tensorflow to pytorch.

Existing models for recent basecallers have been converted to the new format.
Pytorch format models contain a _pt suffix in the filename.

Changed

• Inference is now performed using PyTorch instead of TensorFlow.
• The medaka consensus command has been renamed to medaka inference to reflect
  its function in running an arbitrary model and avoid confusion with medaka_consensus.
• The medaka stitch command has been renamed to medaka sequence to reflect its
  function in creating a consensus sequence.
• The medaka variant command has been renamed to medaka vcf to reflect its function
  in consolidating variants and avoid confusion with medaka_variant.
• Order of arguments to medaka vcf has been changed to be more consistent
  with medaka sequence.
• The helper script medaka_haploid_variant has been renamed medaka_variant to
  save typing.
• Make --ignore_read_groups option available to more medaka subcommands including inference.

Removed

• The medaka snp command has been removed. This was long defunct as diploid SNP calling
  had been deprecated, and medaka variant is used to create VCFs for current models.
• Loading models in hdf format has been deprecated.
• Deleted minimap2 and racon wrappers in medaka/wrapper.py.

Added

• Release conda packages for Linux (x86 and aarch64) and macOS (arm64).
• Option --lr_schedule allows using cosine learning rate schedule in training.
• Option --max_valid_samples to set number of samples in a training validation batch.

Fixed

• Training models with DiploidLabelScheme uses categorical cross-entropy loss
  instead of binary cross-entropy.