def create_decoder():
"""Creates the ``Decoder`` instance. This specifies the search
strategy used to traverse the space spanned by the predictors. This
method relies on the global ``args`` variable.
TODO: Refactor to avoid long argument lists
Returns:
Decoder. Instance of the search strategy
"""
# Create decoder instance and add predictors
if args.decoder == "greedy":
decoder = GreedyDecoder(args)
elif args.decoder == "beam":
decoder = BeamDecoder(args, args.hypo_recombination, args.beam,
args.pure_heuristic_scores,
args.decoder_diversity_factor,
args.early_stopping)
elif args.decoder == "multisegbeam":
decoder = MultisegBeamDecoder(args, args.hypo_recombination, args.beam,
args.multiseg_tokenizations,
args.early_stopping, args.max_word_len)
elif args.decoder == "syncbeam":
decoder = SyncBeamDecoder(args, args.hypo_recombination, args.beam,
args.pure_heuristic_scores,
args.decoder_diversity_factor,
args.early_stopping, args.sync_symbol,
args.max_word_len)
elif args.decoder == "dfs":
decoder = DFSDecoder(args, args.early_stopping,
args.max_node_expansions)
elif args.decoder == "restarting":
decoder = RestartingDecoder(args, args.hypo_recombination,
args.max_node_expansions,
args.low_decoder_memory,
args.restarting_node_score,
args.stochastic_decoder,
args.decode_always_single_step)
elif args.decoder == "bow":
decoder = BOWDecoder(args, args.hypo_recombination,
args.max_node_expansions, args.stochastic_decoder,
args.early_stopping,
args.decode_always_single_step)
elif args.decoder == "flip":
decoder = FlipDecoder(args, args.trg_test, args.max_node_expansions,
args.early_stopping, args.flip_strategy)
elif args.decoder == "bigramgreedy":
decoder = BigramGreedyDecoder(args, args.trg_test,
args.max_node_expansions,
args.early_stopping)
elif args.decoder == "bucket":
decoder = BucketDecoder(
args, args.hypo_recombination, args.max_node_expansions,
args.low_decoder_memory, args.beam, args.pure_heuristic_scores,
args.decoder_diversity_factor, args.early_stopping,
args.stochastic_decoder, args.bucket_selector,
args.bucket_score_strategy, args.collect_statistics)
elif args.decoder == "astar":
decoder = AstarDecoder(args, args.beam, args.pure_heuristic_scores,
args.early_stopping, max(1, args.nbest))
elif args.decoder == "vanilla":
decoder = get_nmt_vanilla_decoder(
args, args.nmt_path,
_parse_config_param("nmt_config", get_default_nmt_config()))
args.predictors = "vanilla"
else:
logging.fatal("Decoder %s not available. Please double-check the "
"--decoder parameter." % args.decoder)
add_predictors(decoder)
# Add heuristics for search strategies like A*
if args.heuristics:
add_heuristics(decoder)
# Update start sentence id if necessary
if args.range:
idx, _ = args.range.split(":") if (":" in args.range) else (args.range,
0)
decoder.set_start_sen_id(int(idx) -
1) # -1 because indices start with 1
return decoder
def create_decoder():
"""Creates the ``Decoder`` instance. This specifies the search
strategy used to traverse the space spanned by the predictors. This
method relies on the global ``args`` variable.
TODO: Refactor to avoid long argument lists
Returns:
Decoder. Instance of the search strategy
"""
# Create decoder instance and add predictors
decoder = None
try:
if args.decoder == "greedy":
decoder = GreedyDecoder(args)
elif args.decoder == "beam":
decoder = BeamDecoder(args)
elif args.decoder == "multisegbeam":
decoder = MultisegBeamDecoder(args,
args.hypo_recombination,
args.beam,
args.multiseg_tokenizations,
args.early_stopping,
args.max_word_len)
elif args.decoder == "syncbeam":
decoder = SyncBeamDecoder(args)
elif args.decoder == "mbrbeam":
decoder = MBRBeamDecoder(args)
elif args.decoder == "sepbeam":
decoder = SepBeamDecoder(args)
elif args.decoder == "syntaxbeam":
decoder = SyntaxBeamDecoder(args)
elif args.decoder == "combibeam":
decoder = CombiBeamDecoder(args)
elif args.decoder == "dfs":
decoder = DFSDecoder(args)
elif args.decoder == "restarting":
decoder = RestartingDecoder(args,
args.hypo_recombination,
args.max_node_expansions,
args.low_decoder_memory,
args.restarting_node_score,
args.stochastic_decoder,
args.decode_always_single_step)
elif args.decoder == "bow":
decoder = BOWDecoder(args)
elif args.decoder == "flip":
decoder = FlipDecoder(args)
elif args.decoder == "bigramgreedy":
decoder = BigramGreedyDecoder(args)
elif args.decoder == "bucket":
decoder = BucketDecoder(args,
args.hypo_recombination,
args.max_node_expansions,
args.low_decoder_memory,
args.beam,
args.pure_heuristic_scores,
args.decoder_diversity_factor,
args.early_stopping,
args.stochastic_decoder,
args.bucket_selector,
args.bucket_score_strategy,
args.collect_statistics)
elif args.decoder == "astar":
decoder = AstarDecoder(args)
elif args.decoder == "vanilla":
decoder = construct_nmt_vanilla_decoder()
args.predictors = "vanilla"
else:
logging.fatal("Decoder %s not available. Please double-check the "
"--decoder parameter." % args.decoder)
except Exception as e:
logging.fatal("An %s has occurred while initializing the decoder: %s"
" Stack trace: %s" % (sys.exc_info()[0],
e,
traceback.format_exc()))
if decoder is None:
sys.exit("Could not initialize decoder.")
add_predictors(decoder)
# Add heuristics for search strategies like A*
if args.heuristics:
add_heuristics(decoder)
return decoder