AF3process_final函数解读

AlphaFold3feature_processing_multimer模块的process_final函数是数据处理管道中的最终步骤，它在合并和配对处理之后对np_example（一个包含特征的字典）进行一系列后处理操作。这些步骤旨在确保所有特征符合 AlphaFold3 训练和预测所需的格式，并为模型的输入做好准备。

process_final的主要任务是：

调用一系列函数对np_example进行处理。 最终输出经过后处理的np_example，它包含了适合模型输入的特征。 源代码： def process_final( np_example: Mapping[str, np.ndarray] ) -> Mapping[str, np.ndarray]: """Final processing steps in data pipeline, after merging and pairing.""" np_example = _correct_msa_restypes(np_example) np_example = _make_seq_mask(np_example) np_example = _make_msa_mask(np_example) np_example = _filter_features(np_example) return np_example def _correct_msa_restypes(np_example): """Correct MSA restype to have the same order as residue_constants.""" new_order_list = residue_constants.MAP_HHBLITS_AATYPE_TO_OUR_AATYPE np_example['msa'] = np.take(new_order_list, np_example['msa'], axis=0) np_example['msa'] = np_example['msa'].astype(np.int32) return np_example def _make_seq_mask(np_example): np_example['seq_mask'] = (np_example['entity_id'] > 0).astype(np.float32) return np_example def _make_msa_mask(np_example): """Mask features are all ones, but will later be zero-padded.""" np_example['msa_mask'] = np.ones_like(np_example['msa'], dtype=np.float32) seq_mask = (np_example['entity_id'] > 0).astype(np.float32) np_example['msa_mask'] *= seq_mask[None] return np_example REQUIRED_FEATURES = frozenset({ 'aatype', 'all_atom_mask', 'all_atom_positions', 'all_chains_entity_ids', 'all_crops_all_chains_mask', 'all_crops_all_chains_positions', 'all_crops_all_chains_residue_ids', 'assembly_num_chains', 'asym_id', 'bert_mask', 'cluster_bias_mask', 'deletion_matrix', 'deletion_mean', 'entity_id', 'entity_mask', 'mem_peak', 'msa', 'msa_mask', 'num_alignments', 'num_templates', 'queue_size', 'residue_index', 'resolution', 'seq_length', 'seq_mask', 'sym_id', 'template_aatype', 'template_all_atom_mask', 'template_all_atom_positions' }) def _filter_features( np_examp