def encode(self, melody):
"""Returns a SequenceExample for the given melody.
Args:
melody: A MonophonicMelody object.
Returns:
A tf.train.SequenceExample containing inputs and labels.
"""
melody.squash(self.min_note, self.max_note, self.transpose_to_key)
inputs = []
labels = []
for i in range(len(melody) - 1):
inputs.append(self.melody_to_input(melody, i))
labels.append(self.melody_to_label(melody, i + 1))
return sequence_example_lib.make_sequence_example(inputs, labels)
def encode(self, lead_sheet):
"""Returns a SequenceExample for the given lead sheet.
Args:
lead_sheet: A LeadSheet object.
Returns:
A tf.train.SequenceExample containing inputs and labels.
"""
lead_sheet.squash(self.min_note, self.max_note, self.transpose_to_key)
inputs = []
labels = []
for i in range(len(lead_sheet) - 1):
inputs.append(self.lead_sheet_to_input(lead_sheet, i))
labels.append(self.lead_sheet_to_label(lead_sheet, i + 1))
return sequence_example_lib.make_sequence_example(inputs, labels)
def encode(self, chords, transpose_amount):
"""Returns a SequenceExample for the given chord progression.
Args:
chords: A ChordProgression object.
transpose_amount: The number of half steps to transpose the chords.
Returns:
A tf.train.SequenceExample containing inputs and labels.
"""
chords.transpose(transpose_amount)
inputs = []
labels = []
for i in range(len(chords) - 1):
inputs.append(self.chords_to_input(chords, i))
labels.append(self.chords_to_label(chords, i + 1))
return sequence_example_lib.make_sequence_example(inputs, labels)
def testEncode(self):
events = [100, 100, 107, 111, NO_EVENT, 99, 112, NOTE_OFF, NO_EVENT]
melody = melodies_lib.Melody()
melody.from_event_list(events)
sequence_example = self.melody_encoder_decoder.encode(melody)
expected_inputs = [
[0.0, 0.0, 1.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0],
[0.0, 0.0, 1.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0],
[0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 1.0, 0.0, 0.0, 0.0, 0.0],
[0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 1.0],
[1.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0],
[0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 1.0],
[0.0, 0.0, 1.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0],
[0.0, 1.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0]]
expected_labels = [2, 9, 13, 0, 13, 2, 1, 0]
expected_sequence_example = sequence_example_lib.make_sequence_example(
expected_inputs, expected_labels)
self.assertEqual(sequence_example, expected_sequence_example)
def testEncode(self):
events = [100, 100, 107, 111, NO_EVENT, 99, 112, NOTE_OFF, NO_EVENT]
melody = melodies_lib.MonophonicMelody()
melody.from_event_list(events)
sequence_example = self.melody_encoder_decoder.encode(melody)
expected_inputs = [
[0.0, 0.0, 1.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0],
[0.0, 0.0, 1.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0],
[0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 1.0, 0.0, 0.0, 0.0, 0.0],
[0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 1.0],
[1.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0],
[0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 1.0],
[0.0, 0.0, 1.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0],
[0.0, 1.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0]]
expected_labels = [2, 9, 13, 0, 13, 2, 1, 0]
expected_sequence_example = sequence_example_lib.make_sequence_example(
expected_inputs, expected_labels)
self.assertEqual(sequence_example, expected_sequence_example)
def encode(self, melody):
"""Returns a SequenceExample for the given melody.
Args:
melody: A MonophonicMelody object.
Returns:
A tf.train.SequenceExample containing inputs and labels.
"""
melody.squash(self.min_note, self.max_note, self.transpose_to_key)
inputs = []
labels = []
melody_events = melody.events
melody.events = melody_events[:1]
for i in xrange(1, len(melody_events)):
inputs.append(self.melody_to_input(melody))
melody.events = melody_events[:i + 1]
labels.append(self.melody_to_label(melody))
return sequence_example_lib.make_sequence_example(inputs, labels)
def encode(self, melody):
"""Returns a SequenceExample for the given melody.
Args:
melody: A Melody object.
Returns:
A tf.train.SequenceExample containing inputs and labels.
"""
melody.squash(self.min_note, self.max_note, self.transpose_to_key)
inputs = []
labels = []
melody_events = melody.events
melody.events = melody_events[:1]
for i in xrange(1, len(melody_events)):
inputs.append(self.melody_to_input(melody))
melody.events = melody_events[:i + 1]
labels.append(self.melody_to_label(melody))
return sequence_example_lib.make_sequence_example(inputs, labels)
