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5032722 | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 117 118 119 120 121 122 123 124 125 126 127 128 129 130 131 132 133 134 135 136 137 138 139 140 141 142 143 144 145 | #!/usr/bin/env python3
# -*- coding: utf-8 -*-
"""
Created on Wed Jan 29 18:16:22 2025
"""
#########################################
### enforcing defaults in config file #
#########################################
def enforce_valid_defaults(args):
provided_args = list(vars(args).keys())
# if skipping an embedder, make sure they don't write anything to tensorboard
if ('anc_model_type' in provided_args) and (args.anc_model_type is None):
args.interms_for_tboard['embeddings'] = False
args.interms_for_tboard['sow_outputs'] = False
if ('desc_model_type' in provided_args) and (args.desc_model_type is None):
args.interms_for_tboard['embeddings'] = False
args.interms_for_tboard['sow_outputs'] = False
# if you're not updating gradients, don't run any training updates
if not args.update_grads:
args.num_epochs = 1
##########################################
### filling config with default values #
##########################################
def general_fill_with_default_values(args):
"""
alphabets:
===========
emission alphabet size: normal tokens
> 20 for amino acids
> 4 for DNA
base alphabet size: emission alphabet size + 3 (<bos>, <eos>, and <pad> tags); the input alphabet size
> 23 for amino acids
> 7 for DNA
"""
args.seq_padding_idx = getattr( args, "seq_padding_idx", 0 )
args.align_padding_idx = getattr( args, "align_padding_idx", -9 )
args.update_grads = getattr( args, "update_grads", True )
args.gap_idx = getattr( args, "gap_idx", 43 )
args.emission_alphabet_size = getattr( args, "emission_alphabet_size", 20 )
def feedforward_fill_with_default_values(args):
"""
alphabets:
===========
full alphabet size: alignment-augment alphabet, where inserted
residues/nucleotides are different from matched residues/nucleotides;
the output alphabet size; includes special tokens
"""
general_fill_with_default_values(args)
args.in_alph_size = getattr( args, "in_alph_size", args.emission_alphabet_size + 3 )
args.chunk_length = getattr( args, "chunk_length", 512 )
args.out_alph_size = getattr( args, "out_alph_size", 44 )
# remap option
if args.pred_config['t_per_sample']:
args.pred_config['times_from'] = 't_per_sample'
elif not args.pred_config['t_per_sample']:
args.pred_config['times_from'] = None
def neural_hmm_fill_with_default_values(args):
"""
alphabets:
===========
full alphabet size: alignment-augment alphabet, where inserted
residues/nucleotides are different from matched residues/nucleotides;
the output alphabet size; includes special tokens
"""
general_fill_with_default_values(args)
args.in_alph_size = getattr( args, "in_alph_size", args.emission_alphabet_size + 3 )
args.chunk_length = getattr( args, "chunk_length", 512 )
def pairhmm_indp_sites_fill_with_default_values(args):
"""
no indel mixtures, so num_domain_mixtures and num_fragment_mixtures is automatically 1
"""
general_fill_with_default_values(args)
args.pred_config['num_domain_mixtures'] = 1
args.pred_config['num_fragment_mixtures'] = 1
def pairhmm_frag_and_site_classes_fill_with_default_values(args):
"""
num_domain_mixtures is automatically 1
"""
general_fill_with_default_values(args)
if args.pred_model_type == 'pairhmm_frag_and_site_classes':
args.pred_config['num_domain_mixtures'] = 1
#########################################################
### sharing top-level arguments with sub-dictionaries #
#########################################################
def general_share_top_level_args(args):
args.pred_config['seq_padding_idx'] = args.seq_padding_idx
args.pred_config['align_padding_idx'] = args.align_padding_idx
args.pred_config['gap_idx'] = args.gap_idx
def feedforward_share_top_level_args(args):
general_share_top_level_args(args)
args.pred_config['in_alph_size'] = args.in_alph_size
args.pred_config['out_alph_size'] = args.out_alph_size
args.anc_enc_config['in_alph_size'] = args.in_alph_size
args.anc_enc_config['seq_padding_idx'] = args.seq_padding_idx
args.desc_dec_config['in_alph_size'] = args.in_alph_size
args.desc_dec_config['seq_padding_idx'] = args.seq_padding_idx
def neural_hmm_share_top_level_args(args):
general_share_top_level_args(args)
args.pred_config['in_alph_size'] = args.in_alph_size
args.anc_enc_config['in_alph_size'] = args.in_alph_size
args.anc_enc_config['seq_padding_idx'] = args.seq_padding_idx
args.desc_dec_config['in_alph_size'] = args.in_alph_size
args.desc_dec_config['seq_padding_idx'] = args.seq_padding_idx
args.pred_config['emission_alphabet_size'] = args.emission_alphabet_size
args.pred_config['emissions_postproc_config']['emission_alphabet_size'] = args.emission_alphabet_size
args.pred_config['transitions_postproc_config']['emission_alphabet_size'] = args.emission_alphabet_size
def pairhmms_share_top_level_args(args):
general_share_top_level_args(args)
args.pred_config['emission_alphabet_size'] = args.emission_alphabet_size
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