roll back changes to RobertaFeaturizer (347ac6ac) · Commits · 钟慕尧 / deepchem

deepchem/feat/init.py

+6 −0

Original line number	Diff line number	Diff line
		@@ -73,6 +73,12 @@ try:
		except ModuleNotFoundError:
		pass

		try:
		from transformers import BertTokenizerFast
		from deepchem.feat.bert_tokenizer import BertFeaturizer
		except ModuleNotFoundError:
		pass

		try:
		from transformers import RobertaTokenizerFast
		from deepchem.feat.roberta_tokenizer import RobertaFeaturizer

+5 −7

Original line number	Diff line number	Diff line
		from deepchem.feat import Featurizer
		from typing import Dict, List
		from typing import Dict, List, Optional
		try:
		from transformers import BertTokenizerFast
		except ModuleNotFoundError:
		@@ -8,7 +8,7 @@ except ModuleNotFoundError:
		pass


		class BertFeaturizer(BertFeaturizerFast, Featurizer):
		class BertFeaturizer(Featurizer):
		"""Bert Featurizer.

		Bert Featurizer.
		@@ -24,15 +24,14 @@ class BertFeaturizer(BertFeaturizerFast, Featurizer):

		Notes
		-----
		This class inherits from BertTokenizerFast.
		This class may contain code and/or documentation taken from the
		RobertaFeaturizer pull request (#2581), which have been moved here due to
		code restructuring.
		"""

		def __init__(self, **kwargs):
		super().__init__(**kwargs)
		return
		def __init__(self, tokenizer: BertTokenizerFast = BertTokenizerFast()):
		self.tokenizer = tokenizer
		return self.tokenizer

		def _featurize(self, datapoint: str, **kwargs) -> List[List[int]]:
		"""Calculate encoding using HuggingFace's RobertaTokenizerFast
		@@ -49,7 +48,6 @@ class BertFeaturizer(BertFeaturizerFast, Featurizer):
		"""

		# the encoding is natively a dictionary with keys 'input_ids', 'token_type_ids', and 'attention_mask'
		# encoding = list(self(smiles_string, **kwargs).values())
		encoding = list(self(datapoint, **kwargs).values())
		return encoding

+1 −4

Original line number	Diff line number	Diff line
		@@ -19,6 +19,7 @@ def test_call():
		assert len(embedding['input_ids']) == 2 and len(
		emb['attention_mask']) == 2


		def test_featurize():
		"""Test that BertFeaturizer.featurize() correctly featurizes all sequences,
		correctly outputs input_ids and attention_mask.
		@@ -32,10 +33,6 @@ def test_featurize():
		"Rostlab/prot_bert", do_lower_case=False)
		feats = featurizer.featurize(sequence)
		long_feat = featurizer.featurize(sequence_long)
		"""
		for f in feats:
		print(f)
		"""
		assert (len(feats) == 2)
		assert (all([len(f) == 3 for f in feats]))
		assert (len(long_feat) == 1)

+14 −0

Original line number	Diff line number	Diff line
		@@ -396,6 +396,20 @@ References:
		Other Featurizers
		-----------------

		BertFeaturizer
		^^^^^^^^^^^^^^

		.. autoclass:: deepchem.feat.BertFeaturizer
		:members:
		:inherited-members:

		RobertaFeaturizer
		^^^^^^^^^^^^^^^^^

		.. autoclass:: deepchem.feat.RobertaFeaturizer
		:members:
		:inherited-members:

		BindingPocketFeaturizer
		^^^^^^^^^^^^^^^^^^^^^^^