290 lines
11 KiB
Python
290 lines
11 KiB
Python
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# Copyright 2016 Google Inc. All Rights Reserved.
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#
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# Licensed under the Apache License, Version 2.0 (the "License");
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# you may not use this file except in compliance with the License.
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# You may obtain a copy of the License at
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#
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# http://www.apache.org/licenses/LICENSE-2.0
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#
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# Unless required by applicable law or agreed to in writing, software
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# distributed under the License is distributed on an "AS IS" BASIS,
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# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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# See the License for the specific language governing permissions and
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# limitations under the License.
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"""MIDI ops.
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Input and output wrappers for converting between MIDI and other formats.
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"""
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from collections import defaultdict
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import sys
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# pylint: disable=g-import-not-at-top
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if sys.version_info.major <= 2:
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from cStringIO import StringIO
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else:
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from io import StringIO
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# internal imports
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import pretty_midi
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import tensorflow as tf
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from magenta.protobuf import music_pb2
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# pylint: enable=g-import-not-at-top
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# The offset used to change the mode of a key from major to minor when
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# generating a PrettyMIDI KeySignature.
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_PRETTY_MIDI_MAJOR_TO_MINOR_OFFSET = 12
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class MIDIConversionError(Exception):
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pass
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def midi_to_sequence_proto(midi_data):
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"""Convert MIDI file contents to a tensorflow.magenta.NoteSequence proto.
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Converts a MIDI file encoded as a string into a
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tensorflow.magenta.NoteSequence proto. Decoding errors are very common when
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working with large sets of MIDI files, so be sure to handle
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MIDIConversionError exceptions.
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Args:
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midi_data: A string containing the contents of a MIDI file or populated
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pretty_midi.PrettyMIDI object.
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Returns:
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A tensorflow.magenta.NoteSequence proto.
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Raises:
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MIDIConversionError: An improper MIDI mode was supplied.
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"""
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# In practice many MIDI files cannot be decoded with pretty_midi. Catch all
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# errors here and try to log a meaningful message. So many different
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# exceptions are raised in pretty_midi.PrettyMidi that it is cumbersome to
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# catch them all only for the purpose of error logging.
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# pylint: disable=bare-except
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if isinstance(midi_data, pretty_midi.PrettyMIDI):
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midi = midi_data
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else:
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try:
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midi = pretty_midi.PrettyMIDI(StringIO(midi_data))
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except:
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raise MIDIConversionError('Midi decoding error %s: %s' %
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(sys.exc_info()[0], sys.exc_info()[1]))
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# pylint: enable=bare-except
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sequence = music_pb2.NoteSequence()
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# Populate header.
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sequence.ticks_per_quarter = midi.resolution
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sequence.source_info.parser = music_pb2.NoteSequence.SourceInfo.PRETTY_MIDI
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sequence.source_info.encoding_type = (
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music_pb2.NoteSequence.SourceInfo.MIDI)
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# Populate time signatures.
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for midi_time in midi.time_signature_changes:
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time_signature = sequence.time_signatures.add()
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time_signature.time = midi_time.time
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time_signature.numerator = midi_time.numerator
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try:
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# Denominator can be too large for int32.
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time_signature.denominator = midi_time.denominator
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except ValueError:
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raise MIDIConversionError('Invalid time signature denominator %d' %
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midi_time.denominator)
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# Populate key signatures.
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for midi_key in midi.key_signature_changes:
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key_signature = sequence.key_signatures.add()
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key_signature.time = midi_key.time
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key_signature.key = midi_key.key_number % 12
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midi_mode = midi_key.key_number / 12
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if midi_mode == 0:
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key_signature.mode = key_signature.MAJOR
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elif midi_mode == 1:
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key_signature.mode = key_signature.MINOR
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else:
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raise MIDIConversionError('Invalid midi_mode %i' % midi_mode)
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# Populate tempo changes.
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tempo_times, tempo_qpms = midi.get_tempo_changes()
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for time_in_seconds, tempo_in_qpm in zip(tempo_times, tempo_qpms):
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tempo = sequence.tempos.add()
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tempo.time = time_in_seconds
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tempo.qpm = tempo_in_qpm
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# Populate notes by first gathering them all from the midi's instruments, then
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# sorting them primarily by start and secondarily by end, and finally looping
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# through this sorted list and appending each as a new sequence.note. We also
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# here set the sequence.total_time as the max end time in the notes.
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# TODO(douglaseck): Eliminate some of this boilerplate code.
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midi_notes = []
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midi_pitch_bends = []
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midi_control_changes = []
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for num_instrument, midi_instrument in enumerate(midi.instruments):
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for midi_note in midi_instrument.notes:
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if not sequence.total_time or midi_note.end > sequence.total_time:
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sequence.total_time = midi_note.end
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midi_notes.append((midi_instrument.program, num_instrument,
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midi_instrument.is_drum, midi_note))
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for midi_pitch_bend in midi_instrument.pitch_bends:
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midi_pitch_bends.append(
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(midi_instrument.program, num_instrument,
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midi_instrument.is_drum, midi_pitch_bend))
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for midi_control_change in midi_instrument.control_changes:
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midi_control_changes.append(
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(midi_instrument.program, num_instrument,
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midi_instrument.is_drum, midi_control_change))
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for program, instrument, is_drum, midi_note in midi_notes:
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note = sequence.notes.add()
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note.instrument = instrument
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note.program = program
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note.start_time = midi_note.start
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note.end_time = midi_note.end
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note.pitch = midi_note.pitch
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note.velocity = midi_note.velocity
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note.is_drum = is_drum
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for program, instrument, is_drum, midi_pitch_bend in midi_pitch_bends:
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pitch_bend = sequence.pitch_bends.add()
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pitch_bend.instrument = instrument
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pitch_bend.program = program
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pitch_bend.time = midi_pitch_bend.time
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pitch_bend.bend = midi_pitch_bend.pitch
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pitch_bend.is_drum = is_drum
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for program, instrument, is_drum, midi_control_change in midi_control_changes:
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control_change = sequence.control_changes.add()
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control_change.instrument = instrument
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control_change.program = program
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control_change.time = midi_control_change.time
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control_change.control_number = midi_control_change.number
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control_change.control_value = midi_control_change.value
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control_change.is_drum = is_drum
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# TODO(douglaseck): Estimate note type (e.g. quarter note) and populate
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# note.numerator and note.denominator.
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return sequence
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def sequence_proto_to_pretty_midi(sequence):
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"""Convert tensorflow.magenta.NoteSequence proto to a PrettyMIDI.
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Time is stored in the NoteSequence in absolute values (seconds) as opposed to
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relative values (MIDI ticks). When the NoteSequence is translated back to
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PrettyMIDI the absolute time is retained. The tempo map is also recreated.
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Args:
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sequence: A tensorfow.magenta.NoteSequence proto.
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Returns:
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A pretty_midi.PrettyMIDI object or None if sequence could not be decoded.
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"""
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kwargs = {}
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if sequence.tempos and sequence.tempos[0].time == 0:
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kwargs['initial_tempo'] = sequence.tempos[0].qpm
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pm = pretty_midi.PrettyMIDI(resolution=sequence.ticks_per_quarter, **kwargs)
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# Create an empty instrument to contain time and key signatures.
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instrument = pretty_midi.Instrument(0)
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pm.instruments.append(instrument)
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# Populate time signatures.
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for seq_ts in sequence.time_signatures:
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time_signature = pretty_midi.containers.TimeSignature(
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seq_ts.numerator, seq_ts.denominator, seq_ts.time)
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pm.time_signature_changes.append(time_signature)
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# Populate key signatures.
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for seq_key in sequence.key_signatures:
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key_number = seq_key.key
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if seq_key.mode == seq_key.MINOR:
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key_number += _PRETTY_MIDI_MAJOR_TO_MINOR_OFFSET
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key_signature = pretty_midi.containers.KeySignature(
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key_number, seq_key.time)
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pm.key_signature_changes.append(key_signature)
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# Populate tempo. The first tempo change was done in PrettyMIDI constructor.
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# TODO(douglaseck): Update this code if pretty_midi adds the ability to
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# write tempo.
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if len(sequence.tempos) > 1:
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for seq_tempo in sequence.tempos[1:]:
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tick_scale = 60.0 / (pm.resolution * seq_tempo.qpm)
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tick = pm.time_to_tick(seq_tempo.time)
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# pylint: disable=protected-access
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pm._PrettyMIDI__tick_scales.append((tick, tick_scale))
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# pylint: enable=protected-access
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# Populate instrument events by first gathering notes and other event types
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# in lists then write them sorted to the PrettyMidi object.
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instrument_events = defaultdict(lambda: defaultdict(list))
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for seq_note in sequence.notes:
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instrument_events[(seq_note.instrument, seq_note.program,
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seq_note.is_drum)]['notes'].append(
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pretty_midi.Note(
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seq_note.velocity, seq_note.pitch,
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seq_note.start_time, seq_note.end_time))
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for seq_bend in sequence.pitch_bends:
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instrument_events[(seq_bend.instrument, seq_bend.program,
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seq_bend.is_drum)]['bends'].append(
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pretty_midi.PitchBend(seq_bend.bend, seq_bend.time))
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for seq_cc in sequence.control_changes:
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instrument_events[(seq_cc.instrument, seq_cc.program,
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seq_cc.is_drum)]['controls'].append(
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pretty_midi.ControlChange(
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seq_cc.control_number,
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seq_cc.control_value, seq_cc.time))
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for (instr_id, prog_id, is_drum) in sorted(instrument_events.keys()):
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# For instr_id 0 append to the instrument created above.
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if instr_id > 0:
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instrument = pretty_midi.Instrument(prog_id, is_drum)
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pm.instruments.append(instrument)
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instrument.program = prog_id
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instrument.notes = instrument_events[
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(instr_id, prog_id, is_drum)]['notes']
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instrument.pitch_bends = instrument_events[
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(instr_id, prog_id, is_drum)]['bends']
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instrument.control_changes = instrument_events[
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(instr_id, prog_id, is_drum)]['controls']
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return pm
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def midi_file_to_sequence_proto(midi_file):
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"""Converts MIDI file to a tensorflow.magenta.NoteSequence proto.
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Args:
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midi_file: A string path to a MIDI file.
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Returns:
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A tensorflow.magenta.Sequence proto.
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Raises:
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MIDIConversionError: Invalid midi_file.
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"""
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with tf.gfile.Open(midi_file, 'r') as f:
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midi_as_string = f.read()
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return midi_to_sequence_proto(midi_as_string)
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def sequence_proto_to_midi_file(sequence, output_file):
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"""Convert tensorflow.magenta.NoteSequence proto to a MIDI file on disk.
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Time is stored in the NoteSequence in absolute values (seconds) as opposed to
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relative values (MIDI ticks). When the NoteSequence is translated back to
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MIDI the absolute time is retained. The tempo map is also recreated.
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Args:
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sequence: A tensorfow.magenta.NoteSequence proto.
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output_file: String path to MIDI file that will be written.
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"""
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pretty_midi_object = sequence_proto_to_pretty_midi(sequence)
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pretty_midi_object.write(output_file)
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