v0.12.4

v0.12.4 (2020-09-18)

Fix

• auto releases on github (#56)
• bumps versions of important third party packages (#55)

v0.12.3

v0.12.3 (2020-09-18)

v0.12.2

• Fix bug in the event that a token id is supplied that overrides a default of
  an inferred token.
• Add pad_at_end boolean setting that when True pads at the end of the
  sequence, and when False pads at the beginning.
• Add dedicated Vocab object which replaces the dictionary of string to
  integer.
• Update tokenizer integration to override convert_tokens_to_string
• Fix bug when trying to save the huggingface tokenizer.
• Make the third party "extras" during python packaging.
• Add better testing and batch encoding operatons.

0.12.0 (2020-01-25)

• Improved the docs to reflect the SequenceTokenizerSpec that was added in
  0.11.0.
• Made max length optional for the tokenizer.
• Added CLI that parses use the SequencePiece library.
• Began versioning docker build, and make pushing easier during build process.
• Have the tokenizer resolve the named alphabets.
• Use poetry along with general updates to a build pipeline.

v0.11.0 (2019-11-15)

Added

• Added the SequenceTokenizerSpec object for specifying the tokenizer.
• Added Vocab object for storing the int to token, and token to int encodings.
• Added example of using tensorflow/keras together with gcgc.

v0.10.0 (2019-11-09)

gcgc has been revamped quite a bit to better support existing processing
pipelines for NLP without trying to do to much. See the docs for more
information about how this works.

v0.9.1

0.9.0 (2019-08-05)

Added

• Parser now outputs the length of the tensor not including padding. This is
  useful for packing and length based iteration.
• Generating masked output from the parse_record method is now available.
• Alphabet can include an optional mask token.

Changed

• Can now specify how large of kmer step size to generate when supplying a kmer
  value.
• Renames EncodedSeq.integer_encoded to EncodedSeq.get_integer_encoding which
  takes a kmer_step_size to specify how large of steps to take when encoding.
• Add parsed_seq_len to the SequenceParser object to control how much padding to
  apply to the end of the integer encoded sequence. This is useful since a batch
  of tensors is expected to have the same size.

0.8.0 (2019-07-04)

Fixed

• Broken test due to platform differences in Path.glob sorting.

Added

• User can specify to use start or end tokens optionally.

Removed

• Removed one_hot_encoding. The user can do that pretty easily if needed. E.g.
  see scatter in PyTorch.

0.7.0 (2019-06-22)

Added

• Properties to access the integer encodings of special tokens. (35cae2a)
  • Alphabet.encoded_start
  • Alphabet.encoded_end
  • Alphabet.encoded_padding
• Remove uniprot dataset creation. (e233162)
• Simplify index handling for GenomicDataset. (3213a9e)

0.6.1 (2019-06-10)

Added

• Updated package management so gcgc is easier to use with other version of
  torch.

0.6.0 (2019-04-04)

Added

• Ability for kmer size to be passed to an alphabet.

0.5.2 (2019-03-21)

Added

• Add Dockerfile and docker-compose.yml for development.
• EncodedSeq.shift, which will shift sequence by an offset integer.
• EncodedSeq.from_integer_encoded_seq will take a list of integers and an
  alphabet and return an EncodedSeq object.
• Add the ability to apply a function to the rollout_kmers yielded values.

Changed

• Alphabet special characters are now located at the start, rather than the end,
  of the letters and token sequence.

0.5.1 (2019-01-09)

Added

• Add extra css to make underline links in articles.
• Exit if the download directory doesn't exist in the call to download organism.
• Wording improvements in docs.

0.5.0 (2018-12-31)

Added

• Include seq_tensor_one_hot in the PyTorch Parser.
• Added a GCGCRecord.encoded_seq property.
• New gcgc.random module to start holding sequence data.
• New gcgc.rollout module to handle working through chunks of sequences.
  • rollout_kmers will roll out kmers.
  • rollout_seq_features will roll out the SeqFeatures from a SeqRecord.
• EncodingAlphabet now can optionally take a gap_characters set of characters to add to the
  alphabet letters. It also takes add_lower_case_for_inserts which will duplicate the alphabet,
  but convert the letters to lowercase.

Changed

Fixed

• Fixed bug in GenomicDataset.from_path where it still referred to init_from_path_generator.

0.4.0

Added

• EncodedSeq now supports iterating through kmers, see EncodedSeq.rollout_kmers for options.
• GCGC is citable.
• GCGC now has a CHANGELOG.md.

# Changelog

Development

0.9.0 (2019-08-05)

Added

• Parser now outputs the length of the tensor not including padding. This is
  useful for packing and length based iteration.
• Generating masked output from the parse_record method is now available.
• Alphabet can include an optional mask token.

Changed

• Can now specify how large of kmer step size to generate when supplying a kmer
  value.
• Renames EncodedSeq.integer_encoded to EncodedSeq.get_integer_encoding which
  takes a kmer_step_size to specify how large of steps to take when encoding.
• Add parsed_seq_len to the SequenceParser object to control how much padding to
  apply to the end of the integer encoded sequence. This is useful since a batch
  of tensors is expected to have the same size.

0.8.0 (2019-07-04)

Fixed

• Broken test due to platform differences in Path.glob sorting.

Added

• User can specify to use start or end tokens optionally.

Removed

• Removed one_hot_encoding. The user can do that pretty easily if needed. E.g.
  see scatter in PyTorch.

0.7.0 (2019-06-22)

Added

• Properties to access the integer encodings of special tokens. (35cae2a)
  • Alphabet.encoded_start
  • Alphabet.encoded_end
  • Alphabet.encoded_padding
• Remove uniprot dataset creation. (e233162)
• Simplify index handling for GenomicDataset. (3213a9e)

0.6.1 (2019-06-10)

Added

• Updated package management so gcgc is easier to use with other version of
  torch.

0.6.0 (2019-04-04)

Added

• Ability for kmer size to be passed to an alphabet.

0.5.2 (2019-03-21)

Added

• Add Dockerfile and docker-compose.yml for development.
• EncodedSeq.shift, which will shift sequence by an offset integer.
• EncodedSeq.from_integer_encoded_seq will take a list of integers and an
  alphabet and return an EncodedSeq object.
• Add the ability to apply a function to the rollout_kmers yielded values.

Changed

• Alphabet special characters are now located at the start, rather than the end,
  of the letters and token sequence.

0.5.1 (2019-01-09)

Added

• Add extra css to make underline links in articles.
• Exit if the download directory doesn't exist in the call to download organism.
• Wording improvements in docs.

0.5.0 (2018-12-31)

Added

• Include seq_tensor_one_hot in the PyTorch Parser.
• Added a GCGCRecord.encoded_seq property.
• New gcgc.random module to start holding sequence data.
• New gcgc.rollout module to handle working through chunks of sequences.
  • rollout_kmers will roll out kmers.
  • rollout_seq_features will roll out the SeqFeatures from a SeqRecord.
• EncodingAlphabet now can optionally take a gap_characters set of characters to add to the
  alphabet letters. It also takes add_lower_case_for_inserts which will duplicate the alphabet,
  but convert the letters to lowercase.

Changed

Fixed

• Fixed bug in GenomicDataset.from_path where it still referred to init_from_path_generator.

0.4.0

Added

• EncodedSeq now supports iterating through kmers, see EncodedSeq.rollout_kmers for options.
• GCGC is citable.
• GCGC now has a CHANGELOG.md.

Release v0.9.0

Added

• Parser now outputs the length of the tensor not including padding. This is
  useful for packing and length based iteration.
• Generating masked output from the parse_record method is now available.
• Alphabet can include an optional mask token.

Changed

• Can now specify how large of kmer step size to generate when supplying a kmer
  value.
• Renames EncodedSeq.integer_encoded to EncodedSeq.get_integer_encoding which
  takes a kmer_step_size to specify how large of steps to take when encoding.
• Add parsed_seq_len to the SequenceParser object to control how much padding to
  apply to the end of the integer encoded sequence. This is useful since a batch
  of tensors is expected to have the same size.

v0.8.0

Fixed

• Broken test due to platform differences in Path.glob sorting.

Added

• User can specify to use start or end tokens optionally.

Removed

• Removed one_hot_encoding. The user can do that pretty easily if needed. E.g.
  see scatter in PyTorch.