o ߥi@sUddlZddlmZmZddlmZddlmZmZm Z ddl Z ddl Z ddl mZddlmZmZmZmZddlmZmZmZmZddlmZdd lmZmZeee j fZ!eee j fZ"e"e#d <gd Z$d d Z%ddZ&ddZ'ddZ(ddZ)ddZ*e(ddZ+ddZ,ddZ-ddZ.d d!Z/dd"d#Z0e( $ $dd%d&Z1e(d'd(Z2e(d)d*Z3e(d+d,Z4d-d.Z5e(d/d0Z6e(dd2d3Z7d4d5Z8d6d7Z9e(dd8d9Z:d:d;Z;dddDdEZ?dFdGZ@dHdIZAdJdKZBdLdMZCe( $ $ddNdOZDe( ddPdQZEdRdSZFdTdUZGdVdWZHe(dXdYZIe(dZd[ZJd\d]ZKd^d_ZLd`daZMddcddZNe( >ddedfZOdgdhZPdidjZQe( $ddkdlZRe(dmdnZSe(dodpZTdqe!dreUdse eUdte jVfdudvZW  $ddwe jVdreUdse eUdxeXdte jVf dydzZY  $dd e!dreUdse eUdxeXdte jVf d{d|ZZ }dd e!dreUdseUd~e[de[dteeUf ddZ\de jVdte jVfddZ]de jVde jVde jVdte jVfddZ^ddZ_dS)N)reducewraps)add)ListMutableMappingOptional) data_utils)batched_gatherone_hottensor_tree_maptree_map) N_EXTRA_MSAN_MSAN_RESN_TPL)residue_constants)FrameRotationprotein)msadeletion_matrixmsa_mask msa_row_mask bert_masktrue_msa msa_chainscCsX|D]%\}}|dr|tj||<q|jtjtjtjfvr)|tj ||<q|S)N_mask) itemsendswithtypetorchfloat32dtypeint32uint8int8int64)rkvr)c/home/ubuntu/.local/lib/python3.10/site-packages/modelscope/models/science/unifold/data/data_ops.pycast_to_64bit_ints#s r+cCstj|djtjd|d<|S)Naatyper"seq_maskr onesshaper!rr)r)r* make_seq_mask.s  r3cCs"tj|djdtjd|d<|S)Ntemplate_aatyperr- template_maskr/r2r)r)r*make_template_mask4s r6cstfdd}|S)z#Supply all arguments but the first.csfddS)Ncs|gRiSNr)x)argsfkwargsr)r*?sz$curry1..fc..r)r:r<r;r>r*fc=szcurry1..fc)r)r;r@r)r?r*curry1:srAcCs\|d|d<tj}tj|tjddd|djd}t |d|d|d<|S)z1Correct MSA restype to have the same order as rc.rr-r) longrc MAP_HHBLITS_AATYPE_TO_OUR_AATYPEr tensorr% unsqueezeexpandr1gather)rnew_order_list new_orderr)r)r*correct_msa_restypesDsrMcCst|djdkrtj|ddd|d<d|vr)t|djdkr)|dd|d<dD];}||vrft||jrf||jd}t|trf|dkrft||r[tj||dd||<q+tj||dd ||<q+d D]}||vr~t||jr~||d||<qi|S) z=Remove singleton and repeated dimensions in protein features.r,rBdim resolutionrCr) domain_namernum_alignments seq_lengthsequence superfamilyrbetween_segment_residues residue_indextemplate_all_atom_mask)axis)rTrS) lenr1r argmax isinstanceint is_tensorsqueezenp)rr' final_dimr)r)r*squeeze_featuresPs" rccCs|dkrLtj|dj|k}d}d}t||d|k}t|t|d||d|d<tj|dj|k}t|t|d||d|d<|S)z&Replace a portion of the MSA with 'X'.rr,)rarandomrandr1r logical_andwhere ones_like)rreplace_proportionrx_idxgap_idx aatype_maskr)r)r*!randomly_replace_msa_with_unknownrs(rpcCs:d}ttjdd|}tt|| | }|S)zGenerate Gumbel Noise of given Shape. This generates samples from Gumbel(0, 1). Args: shape: Shape of noise to return. Returns: Gumbel noise of given shape. ư>rrC)r from_numpyrarguniformlog)r1epsilon uniform_noisegumbelr)r)r* gumbel_noisesrxcCst|j}tj||ddS)a;Samples from a probability distribution given by 'logits'. This uses Gumbel-max trick to implement the sampling in an efficient manner. Args: logits: Logarithm of probabilities to sample from, probabilities can be unnormalized. Returns: Sample from logprobs in one-hot form. rBrO)rxr1r r\logitszr)r)r*gumbel_max_samples r|cCst|j}tj||dddS)aSamples with replacement from a distribution given by 'logits'. This uses Gumbel trick to implement the sampling an efficient manner. For a distribution over k items this samples k times without replacement, so this is effectively sampling a random permutation with probabilities over the permutations derived from the logprobs. Args: logits: Logarithm of probabilities to sample from, probabilities can be unnormalized. Returns: Sample from logprobs in index rBT)rP descending)rxr1r argsortryr)r)r*gumbel_argsort_sample_idxs rcCs4ttj|dd}tjtdg|fddS)NrCrrO)r rrrarg permutationcatrG)num_seqshuffledr)r)r*uniform_permutationsrcCsbtj|dddk}tj|tjd}d||<t|jdks!J|dd}|dd}|jddkr:tdgS|dur|ddd}d||<t j |dd\}}|}|dk}||}|dk} d |d ||<d||<|D]} | dkr|| k} | } | dkr|| || | 9<qxt |d }t |d} tj tdg| fddS) NrBrOrr-g.rCT return_counts?rq)r sumrD zeros_liker!r[r1rGreshaperauniquertrr)rrhas_msarzkeyscounts num_has_msanum_pair num_unpair num_chainsr'cur_maskcur_cntrr)r)r*gumbel_permutations8         rFc Cs|djd}t||}|st|}n|rd|vr|dnd}t|d|}t||}t||||g\} } tD] } | |vrY|rNt|| d| |d| <t|| d| || <q9|S)zLSample MSA randomly, remaining sequences are stored are stored as `extra_*`.rrrNrextra_)r1minrrr splitMSA_FEATURE_NAMES index_select) rmax_seq keep_extra gumbel_samplebiased_msa_by_chainrnum_sel index_orderrsel_seq not_sel_seqr'r)r)r* sample_msas0      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|d <|S) NrfrCrrrrextra_msa_maskrOextra_cluster_assignment) r rr0rr r1r transposer\rD)rgap_agreement_weightweights msa_one_hotsample_one_hotextra_msa_one_hot extra_one_hotrnum_res_ extra_num_seqab agreementr)r)r*nearest_neighbor_clustersJs"  rcCst|jdkr|jd|jdksJ|j|jdgdt|jddR}||j}|gt|jdd}tj|d||}| |j }|S)NrCrrC) r[r1rrIlistr r scatter_add_floatrr")data segment_ids num_segmentsr1rGr)r)r*unsorted_segment_sumes  rcsdjdfdd}d}dd||}||dddddftd d }|tdd 7}||dddddfd <~||d }|d 7}||d<~S)z=Produce profile and deletion_matrix_mean within each cluster.rrcst|dS)Nr)rr8rrr)r*csumus z summarize_clusters..csumrrqrNrrcluster_profileextra_deletion_matrixrcluster_deletion_mean)r1r )rrmask mask_countsmsa_sumdel_sumr)rr*summarize_clustersqs(  rcCstjdgd|gdgtjd}|d}|d}t|dd}t|d d}|d d d d d f|}|d d d d d f|}||} | | jd | jd | jd } ||jd |jd |jd } | | j} tjjj d| d d} | t d||9} tj | dd} | d7} t d| |}||7}|| d d d d f}|d}|d}t d| ||}||7}|| d d d f}||d<||d<|S)zFAssign each extra MSA sequence to its nearest neighbor in sampled MSA.rrfrdr-rrrrrNrrCrNg@@rOz mr, nr->mnrBz nm, mrc->nrcrrz nm, mc->ncrr) r rGr!r rr1Tnn functionalsoftmaxeinsumr)batchrrr extra_maskrrmsa_one_hot_maskedextra_one_hot_maskedt1t2rcluster_assignment cluster_countrrrrrrr)r)r*nearest_neighbor_clusters_v2sF " rcCsDd|vrtj|djtjd|d<tj|djdtjd|d<|S)z:Mask features are all ones, but will later be zero-padded.rrr-rrr/r2r)r)r* make_msa_masks   rc Cs|jddkr?t|tjd}tjd}tjd}tt|ddgt|jdg|d|d d f|d|d d f}n |j g|jdR}|d urs|jddkrht||d|f|d|f}||fSt | }||fS|S) zCreate pseudo beta features.rGCACB.NrC.N) r1r eqrE restype_order atom_orderrjtiler[ new_zerosrr)r,all_atom_positions all_atom_maskis_glyca_idxcb_idx pseudo_betapseudo_beta_maskr)r)r*pseudo_beta_fns&    rcCsP|dvsJt||r dnd||d||rdnd\||d<||d<|S) z9Create pseudo-beta (alpha for glycine) position and mask.)r template_r4r,rrYrr r )r)rprefixr)r)r*make_pseudo_betas    rcCst|||<|Sr7r rG)rkeyvaluer)r)r*add_constant_fieldsr绽|=cCs`|j}|d}t||d|g}t}|tjdtj|d|d}t||ddS)NrBirC) generator) r1r r Generator manual_seedrargr multinomial)probsruds num_classesgenrr)r)r*shaped_categoricalsr cCs0d|vr|St|dd}tj|dd|d<|S)7Compute the HHblits MSA profile if not already present.hhblits_profilerrrO)r r mean)rrr)r)r*make_hhblits_profiles r%cCsLt|dd}|ddddddf}||9}|jdd|jdddS)zCompute the MSA profile.rr#rNrrOr)r r)rohrr)r)r*make_msa_profile sr'cCsd|vr|St||d<|S)r!r")r'r2r)r)r*make_hhblits_profile_v2s r(c Csd|vr|S|d}|d}|d}|}|dk}|D]*}||k}t||d} | dkrF||@} |dd| f} | d| |dd|f<q|S)Nnum_sym entity_idsym_idrCr)rr^repeat) mask_positionrr*r+r)unique_entity_idsfirst_sym_mask cur_entity_idcur_entity_mask cur_num_sym cur_sym_maskcur_sym_bert_maskr)r)r*share_mask_by_entitys$r5c Csntjdgdddgtjd}|j||j|d|jt|dd}ttt dd t t |j D}d |d <d |j|j|j}|dksKJtj jj|||d }|dj } ttjj| |k} | |d M} d|vry| |dM} |rt| |} |rt|d} t| } nt|} t| | |d} | |d 9} | tj|d<|d|d<| |d<|S)z Create data for BERT on raw MSA.g?rerdr-r"rr#cSg|]}dqS)rrr).0rr)r)r* @z#make_masked_msa..rCr)rrrrqr)r rGr! uniform_prob profile_prob same_probr rrrranger[r1rrpadrrrargrhboolr5rtr|r rjrDr) rrreplace_fractionr share_mask random_aacategorical_probs pad_shapes mask_probshr-rzbert_msar)r)r*make_masked_msa/sB      rJc sXddd}|dur$d|vr|djdn|djd}||kr$||d}d |vr8|d jd}||kr8||d }t|t|t|t|i|D]c\} | d krOqFtj} || } d } t| t| ksqJ| d | d| d| fddt| | D} fddt | D}| tt j |}|rt jj||| <t || | || <qF|S)z;Guess at the MSA and sequence dimension to make fixed size.cSst|||d||S)NrCmax)cur_size multiplierr)r)r* get_pad_sizejsz%make_fixed_size..get_pad_sizeNr,rrrCrrz0Rank mismatch between shape and shape schema for z: z vs cs g|] \}}|dp |qSr7)get)r9s1s2) pad_size_mapr)r*r:sz#make_fixed_size..cs"g|] \}}d|j|fqSrr1)r9ip)r(r)r*r:s")rK)r1rrr rrrr[zip enumeratereverse itertoolschainr rrr@r)r shape_schemamsa_cluster_sizeextra_msa_sizer num_templatesrP input_num_resinput_extra_msa_sizer'r1schemamsgpad_sizepaddingr))rVr(r*make_fixed_size_sF     . rjcCs|d|d<d|vrt|dtjdd}n%tj|dtjd}d|vr;|d}tj|ddd d}d ||<|}t|dd }tj |dd|g}tj |dd|d <|S) $Create and concatenate MSA features.r,rWrrCr-asym_lenrBrONrrf target_feat) rDr rrr!rcumsumrr rHr)r has_breakrl entity_ends aatype_1hotrmr)r)r*make_target_feats" rrcCst|dd}t|ddd}t|dddtj}|tj|dd tj|dd g}d |vrMt|d ddtj}||d tj|dd gd |vrlt|d dd|d <t|d ddtj|d<tj|dd |d<|S)rkrrrrdr@@rBrOrrrextra_msa_has_deletionextra_msa_deletion_valuemsa_feat) r r ratanrapirHextendr)rmsa_1hot has_deletiondeletion_valuerwdeletion_mean_valuer)r)r* make_msa_feats@       rcCst|dd}|d}t|ddd}t|ddtjd}t|d ddtjd}||||d |g}tj|d d |d <|S)rkrrrrdrrrsrtrrrBrOrw)r r rrxraryarctanr)rr{rr|r}r~rwr)r)r*make_msa_feat_v2s"rcCsz|dd|}|dd|}t|dd}t|ddtj}|dd|}||d<||d<||d<||d <|S) Nrrrdrrsrtrrurv)r rrxrary)r num_extra_msarrr|r}rr)r)r*make_extra_msa_featsrcsfdd|DS)Ncsi|] \}}|vr||qSr)r)r9r'r( feature_listr)r* szselect_feat..)r)rrr)rr* select_featsrcCsd|vr|Stjtjtj|djd}tjtjtj|djd}tjtjtj|djd}tjtj tj|djd}|d }|| |d<|| |d<|||d<|||d<|S)z>Construct denser atom positions (14 dimensions instead of 37).atom14_atom_existsr,r"deviceresidx_atom14_to_atom37residx_atom37_to_atom14atom37_atom_exists) r rGrErestype_atom14_to_atom37r&rrestype_atom37_to_atom14restype_atom14_maskr!restype_atom37_maskrD)rrrrrprotein_aatyper)r)r*make_atom14_maskssH   rcCs,tdd|tj}t|}tdd|}|S)NcS t|Sr7r)nr)r)r*r= z&make_atom14_masks_np..cSrr7)raarray)tr)r)r*r=r)r randarrayrr )routr)r)r*make_atom14_masks_npsrc Cs8|d|d<|d|d<|d|d<|d}|d}|t|d|dt|djddd}|d t|d|d t|djdd d}||d<||d <||d <tjtj|dj |dj d }||d}t d||}||d<t d||}||d<tjtj |dj |dj d } | |d|d<|S)z?Constructs denser atom positions (14 dimensions instead of 37).r,rrrrrBNrPnum_batch_dimsratom14_gt_existsatom14_gt_positionsrz...rac,...rab->...rbcatom14_alt_gt_positionsz...ra,...rab->...rbatom14_alt_gt_existsatom14_atom_is_ambiguous) rDrr r[r1r rGrErenaming_matricesr"rrrestype_atom14_is_ambiguous) rresidx_atom14_maskrresidx_atom14_gt_maskresidx_atom14_gt_positionsrrenaming_transformalternative_gt_positionsalternative_gt_maskrr)r)r*make_atom14_positions!s^ r:0yE>cs|d}|d}|d}t|jdd}tjgddtd}gd|ddd ddf<gd |ddd ddf<ttjD]-\}}tj|} t d D]} tj || rjtj | | } | d d||| d ddf<qKq>| 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