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Add option to dekonize peptide into AA list #22

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merged 7 commits into from
Nov 15, 2022
Merged

Add option to dekonize peptide into AA list #22

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57ff2ef
Add option to dekonize peptide into AA list
melihyilmaz Nov 15, 2022
e54f723
Bump workflow versions
wfondrie Nov 15, 2022
349ee69
Add Codecov token
wfondrie Nov 15, 2022
09bcc5c
Return list from detokenize by default
melihyilmaz Nov 15, 2022
b2f2bd0
Fix my lazy docstring
wfondrie Nov 15, 2022
3ae4524
Fix broken test
wfondrie Nov 15, 2022
16b9098
Bump changelog
wfondrie Nov 15, 2022
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7 changes: 5 additions & 2 deletions depthcharge/components/transformers.py
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Original file line number Diff line number Diff line change
Expand Up @@ -184,12 +184,15 @@ def tokenize(self, sequence, partial=False):
tokens = torch.tensor(tokens, device=self.device)
return tokens

def detokenize(self, tokens):
def detokenize(self, tokens, pep_as_str=True):
"""Transform tokens back into a peptide sequence

Parameters
----------
tokens : torch.Tensor of shape (n_amino_acids)
pep_as_str: bool, optional
Return peptide sequence in str format by default.
If "False", returns a list of amino acids.
"""
sequence = [self._idx2aa.get(i.item(), "") for i in tokens]
if "$" in sequence:
Expand All @@ -199,7 +202,7 @@ def detokenize(self, tokens):
if self.reverse:
sequence = list(reversed(sequence))

return "".join(sequence)
return "".join(sequence) if pep_as_str else sequence

@property
def vocab_size(self):
Expand Down