def __init__(self, input, options={}, grammar=None, *args, **kwargs):
super(MidiHmmPathBuilder, self).__init__(input, options, *args, **kwargs)
if grammar is None:
self.grammar = get_grammar()
else:
self.grammar = grammar
# Make a copy of the options that we will pass through to HmmPath
options = self.options.copy()
# Remove the options that the tagger doesn't need
labeling_model_name = options.pop("labeling_model")
latticen = options.pop("latticen")
beam_ratio = options.pop("lattice_beam")
viterbi = options.pop("label_viterbi")
partition_labeler = options.pop("partition_labeler")
# Use an HP chord labeler to label the MIDI data
# Partition the labeling model if requested and a partition number
# was given for the supertagger
if partition_labeler and "partition" in self.options and self.options["partition"] is not None:
labeling_model_name += "%d" % self.options["partition"]
# First run the chord labeler on the MIDI input
# Load a labeling model
labeler = HPChordLabeler.load_model(labeling_model_name)
self.labeler = labeler
# Get chord labels from the model: get a lattice of possible chords
lattice = labeler.label_lattice(input, options={"n": latticen, "nokey": True, "viterbi": viterbi}, corpus=True)
# Store the lattice for later reference
self.lattice = lattice
# Beam the lattice to get rid of very low probability labels
lattice.apply_ratio_beam(ratio=beam_ratio)
# Tag the lattice
self.hmmpath = HmmPathBuilder(lattice, options, grammar, *args, **kwargs)
def __init__(self, grammar, input, options={}, logger=None, *args, **kwargs):
Tagger.__init__(self, grammar, input, options, logger=logger)
# Make a copy of the options that we will pass through to the tagger
options = self.options.copy()
# Remove the options that the tagger doesn't need
labeling_model_name = options.pop("labeling_model")
latticen = options.pop("latticen")
beam_ratio = options.pop("lattice_beam")
viterbi = options.pop("label_viterbi")
partition_labeler = options.pop("partition_labeler")
label_output = options.pop("label_output")
only_label = options.pop("only_label")
# Partition the labeling model if requested and a partition number
# was given for the supertagger
if partition_labeler and "partition" in self.options and self.options["partition"] is not None:
labeling_model_name += "%d" % self.options["partition"]
self.logger.info("Labeling model: %s" % labeling_model_name)
# First run the chord labeler on the MIDI input
# Load a labeling model
labeler = HPChordLabeler.load_model(labeling_model_name)
self.labeler = labeler
# Get chord labels from the model: get a lattice of possible chords
lattice = labeler.label_lattice(input, options={"n": latticen, "nokey": True, "viterbi": viterbi}, corpus=True)
# Store the lattice for later reference
self.lattice = lattice
# Also store the labeler's emission matrix
emissions = midi_to_emission_stream(input, remove_empty=False)[0]
self.labeler_emission_matrix = labeler.get_small_emission_matrix(emissions)
# Beam the lattice to get rid of very low probability labels
lattice.apply_ratio_beam(ratio=beam_ratio)
if label_output:
# Output the labelling to a file
with open(label_output, "a") as outfile:
for chord_tags in lattice:
print >> outfile, " ".join(str(crd) for (crd, prob) in chord_tags)
if only_label:
self.tagger = FailTagger(grammar, NullInput())
else:
self.tagger = MultiChordNgramTagger(grammar, lattice, options, logger=logger, *args, **kwargs)
self._lex_prob_cache = [{} for i in range(self.input_length)]
def __init__(self, input, options={}, grammar=None, *args, **kwargs):
super(MidiHmmPathBuilder, self).__init__(input, options, *args,
**kwargs)
if grammar is None:
self.grammar = get_grammar()
else:
self.grammar = grammar
# Make a copy of the options that we will pass through to HmmPath
options = self.options.copy()
# Remove the options that the tagger doesn't need
labeling_model_name = options.pop('labeling_model')
latticen = options.pop('latticen')
beam_ratio = options.pop('lattice_beam')
viterbi = options.pop('label_viterbi')
partition_labeler = options.pop('partition_labeler')
# Use an HP chord labeler to label the MIDI data
# Partition the labeling model if requested and a partition number
# was given for the supertagger
if partition_labeler and 'partition' in self.options and \
self.options['partition'] is not None:
labeling_model_name += "%d" % self.options['partition']
# First run the chord labeler on the MIDI input
# Load a labeling model
labeler = HPChordLabeler.load_model(labeling_model_name)
self.labeler = labeler
# Get chord labels from the model: get a lattice of possible chords
lattice = labeler.label_lattice(input,
options={
'n': latticen,
'nokey': True,
'viterbi': viterbi
},
corpus=True)
# Store the lattice for later reference
self.lattice = lattice
# Beam the lattice to get rid of very low probability labels
lattice.apply_ratio_beam(ratio=beam_ratio)
# Tag the lattice
self.hmmpath = HmmPathBuilder(lattice, options, grammar, *args,
**kwargs)
def __init__(self,
grammar,
input,
options={},
logger=None,
*args,
**kwargs):
Tagger.__init__(self, grammar, input, options, logger=logger)
# Make a copy of the options that we will pass through to the tagger
options = self.options.copy()
# Remove the options that the tagger doesn't need
labeling_model_name = options.pop('labeling_model')
latticen = options.pop('latticen')
beam_ratio = options.pop('lattice_beam')
viterbi = options.pop('label_viterbi')
partition_labeler = options.pop('partition_labeler')
label_output = options.pop('label_output')
only_label = options.pop('only_label')
# Partition the labeling model if requested and a partition number
# was given for the supertagger
if partition_labeler and 'partition' in self.options and \
self.options['partition'] is not None:
labeling_model_name += "%d" % self.options['partition']
self.logger.info("Labeling model: %s" % labeling_model_name)
# First run the chord labeler on the MIDI input
# Load a labeling model
labeler = HPChordLabeler.load_model(labeling_model_name)
self.labeler = labeler
# Get chord labels from the model: get a lattice of possible chords
lattice = labeler.label_lattice(input,
options={
'n': latticen,
'nokey': True,
'viterbi': viterbi
},
corpus=True)
# Store the lattice for later reference
self.lattice = lattice
# Also store the labeler's emission matrix
emissions = midi_to_emission_stream(input, remove_empty=False)[0]
self.labeler_emission_matrix = labeler.get_small_emission_matrix(
emissions)
# Beam the lattice to get rid of very low probability labels
lattice.apply_ratio_beam(ratio=beam_ratio)
if label_output:
# Output the labelling to a file
with open(label_output, 'a') as outfile:
for chord_tags in lattice:
print >> outfile, " ".join(
str(crd) for (crd, prob) in chord_tags)
if only_label:
self.tagger = FailTagger(grammar, NullInput())
else:
self.tagger = MultiChordNgramTagger(grammar,
lattice,
options,
logger=logger,
*args,
**kwargs)
self._lex_prob_cache = [{} for i in range(self.input_length)]
