def generate_basic_notes(self, qpm=160, failsafe=False):
"""
Requires melody conditioned model.
"""
if not self.conditioned:
raise ValueError("Model should be conditioned!")
if failsafe:
self.failsafe()
else:
melody_ns = copy.deepcopy(self.sequence)
try:
melody_instrument = mm.infer_melody_for_sequence(melody_ns)
notes = [note for note in melody_ns.notes
if note.instrument == melody_instrument]
melody_ns.notes.extend(
sorted(notes, key=lambda note: note.start_time))
for i in range(len(melody_ns.notes) - 1):
melody_ns.notes[i].end_time = melody_ns.notes[i + 1].start_time
# sequence can only be one min to save time during inference.
melody_ns = mm.extract_subsequence(melody_ns, 0, 60)
self.inputs = self.encoders['inputs'].encode_note_sequence(
melody_ns)
print("Melody successfully parsed and encoded!")
except Exception as e:
print(f"Error in encoding stage {e}")
print("Resorting to a basic melody")
self.failsafe()
self.decode_length = 4096
sample_ids = next(self.samples)['outputs']
# Decode to NoteSequence.
midi_filename = self.decode(
sample_ids,
encoder=self.encoders['targets'])
accompaniment_ns = mm.midi_file_to_note_sequence(midi_filename)
request_dict = self.put_request_dict
generated_sequence_2_mp3(accompaniment_ns, f"{self.unique_id}", use_salamander=True,
request_dict=request_dict)
def get_melody_ns(filename):
"""
Convert melody Midi file to note sequence.
:param filename: Midi file name.
:return:
Melody note sequences.
"""
melody_ns = mm.midi_file_to_note_sequence(filename)
melody_instrument = mm.infer_melody_for_sequence(melody_ns)
# pylint: disable=no-member
notes = [
note for note in melody_ns.notes
if note.instrument == melody_instrument
]
del melody_ns.notes[:]
melody_ns.notes.extend(sorted(notes, key=lambda note: note.start_time))
for i in range(len(melody_ns.notes) - 1):
melody_ns.notes[i].end_time = melody_ns.notes[i + 1].start_time
# pylint: disable=no-member
return melody_ns
def render_sequence_to_music_dict(midi_file,
music_dict,
model_string="melody_rnn"):
sequence = mm.midi_file_to_note_sequence(midi_file)
# scale to num steps.
music_dict['num_steps'] = 1024 * music_dict['length']
backup_sequence = None
basic_models = [
"melody_rnn", "performance_rnn", "polyphony_rnn", "pianoroll_rnn_nade"
]
if model_string in basic_models:
subsequence = mm.extract_subsequence(sequence, 0.0, C.SUBSEQUENCE_TIME)
for note in subsequence.notes:
# rnns can work with piano data.
note.program = 0
note.instrument = 1
music_dict['sequence'] = subsequence
if model_string == "performance_rnn":
music_dict['num_steps'] = music_dict['num_steps'] * 4
elif model_string == "improv_rnn" or model_string == "music_vae":
subsequence = mm.extract_subsequence(sequence, 0.0, C.SUBSEQUENCE_TIME)
melody = mm.infer_melody_for_sequence(subsequence)
new_sequence = music_pb2.NoteSequence()
backup_sequence = music_pb2.NoteSequence()
new_val = 0.
backup_val = 0.
for note in subsequence.notes:
# rnns can work with piano data.
if note.instrument == melody:
start = note.start_time
end = note.end_time
diff = end - start
new_sequence.notes.add(pitch=note.pitch,
start_time=new_val,
end_time=new_val + diff,
velocity=160)
backup_sequence.notes.add(pitch=note.pitch,
start_time=backup_val,
end_time=backup_val + 0.5,
velocity=160)
new_val += diff
backup_val += 0.5
if model_string == "improv_rnn":
note.program = 0
note.instrument = 1
new_sequence.total_time = new_val
new_sequence.tempos.add(qpm=subsequence.tempos[0].qpm)
backup_sequence.total_time = backup_val
backup_sequence.tempos.add(qpm=60)
music_dict['sequence'] = subsequence
music_dict['backup_sequence'] = backup_sequence
elif model_string == "music_transformer":
# model generate will take care of things
music_dict['sequence'] = sequence
return music_dict
'Twinkle Twinkle Little Star': [
60, 60, 67, 67, 69, 69, 67, mm.MELODY_NO_EVENT,
65, 65, 64, 64, 62, 62, 60, mm.MELODY_NO_EVENT,
67, 67, 65, 65, 64, 64, 62, mm.MELODY_NO_EVENT,
67, 67, 65, 65, 64, 64, 62, mm.MELODY_NO_EVENT,
60, 60, 67, 67, 69, 69, 67, mm.MELODY_NO_EVENT,
65, 65, 64, 64, 62, 62, 60, mm.MELODY_NO_EVENT
]
}
melody = 'Twinkle Twinkle Little Star' #@param ['Mary Had a Little Lamb', 'Row Row Row Your Boat', 'Twinkle Twinkle Little Star', 'Upload your own!']
if melody == 'Upload your own!':
# Extract melody from user-uploaded MIDI file.
melody_ns = upload_midi()
melody_instrument = mm.infer_melody_for_sequence(melody_ns)
notes = [note for note in melody_ns.notes
if note.instrument == melody_instrument]
del melody_ns.notes[:]
melody_ns.notes.extend(
sorted(notes, key=lambda note: note.start_time))
for i in range(len(melody_ns.notes) - 1):
melody_ns.notes[i].end_time = melody_ns.notes[i + 1].start_time
inputs = melody_conditioned_encoders['inputs'].encode_note_sequence(
melody_ns)
else:
# Use one of the provided melodies.
events = [event + 12 if event != mm.MELODY_NO_EVENT else event
for e in melodies[melody]
for event in [e] + event_padding]
inputs = melody_conditioned_encoders['inputs'].encode(