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CHANGELOG.md

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Change log

[0.1.3] - 2021-07-09

Fixed:

  • Fix filtering of logits which impacts loglikelihood computation
  • Fix fasta file reading in compute_loglikelihood

Features:

  • Add normalize mode in compute_loglikelihood.

[0.1.3] - 2021-07-01

Features:

  • Add msa-transformers for methods:
    • compute_logits
    • compute_embeddings
    • compute_probabilities
    • compute_accuracy

Fixed:

  • Remove torch DataParallel wrapper.

[0.1.0] - 2021-07-01

Features:

  • Add ray worker for multi-gpus inference

Removed:

  • Remove torch DataParallel wrapper.

[0.0.10] - 2021-06-14

Note on the release

Features:

  • Add BIO_LOG_LEVEL environnement variable to control logging message (logger)
  • Check if every unique amino acids in sequences are in tokens_list (compute_probabilities)

Fixed:

  • Add shuffling in batch_sampler (lightning_utils)
  • Fix tokens argument for dataloader (lightning_utils)
  • Fix rtd CI to separates docs and package environment.

Changed:

  • Modified the signature of some functions to improve clarity (tansformers_wrappers)
  • Update train_masked method to finetune (tansformers_wrappers)
  • compute_embeddings with option full return a list of embeddingsn, no matter the size (tansformers_wrappers)

Removed:

  • Remove the tokens_list argument when not necessary and tried to make its usage clearer (tansformers_wrappers)
  • Remove functions (tansformers_wrappers):
    • _filter_and_pool_embeddings
    • _split_logits
    • _slabels_remaping
    • _filter_logits
    • _filter_loglikelihood
    • _compute_accuracy
    • _compute_calibration

[0.0.9] - 2021-06-04

Fixed:

  • Batch_sampler issue

[0.0.8] - 2021-06-03

Note on the release

Features:

  • Merge ESM/protbert for finetuning model with pytorch-lightning
  • Possibility to restore a training session.

Fixed:

  • Fix conflicts when saving model with DDP
  • Fix loading checkpoint created by pytorch-lightning

[0.0.7] - 2021-05-12

Note on the release

Features:

  • Add fasta files support for each compute function.
  • Add train_masked function to finetune model on custom dataset. (Only ESM for the moment, protbert is coming.)

Docs:

  • Update documentation to add tutorial on training.

Changed:

  • GPU is used by default if found, even if not specified.

[0.0.6] - 2021-05-24

Note on the release

Fixed:

  • Update torch dependencies to be less restrictive. Create conflict with other packages.

[0.0.5] - 2021-05-12

Note on the release

Added

  • added multi-gpu support for inference
  • added function to finetuned a model on a specific dataset on multi-gpu

Changed

Fixed