def lookback_melody_encoder_decoder(min_note, max_note):
"""Return a LookbackEventSequenceEncoderDecoder for melodies.
Args:
min_note: The minimum midi pitch the encoded melodies can have.
max_note: The maximum midi pitch (exclusive) the encoded melodies can have.
Returns:
A melody LookbackEventSequenceEncoderDecoder.
"""
return note_seq.LookbackEventSequenceEncoderDecoder(
note_seq.MelodyOneHotEncoding(min_note, max_note))
list(range(39, note_seq.MAX_MIDI_PITCH + 1))])),
contrib_training.HParams(
batch_size=128,
rnn_layer_sizes=[128, 128],
dropout_keep_prob=0.5,
clip_norm=5,
learning_rate=0.001),
steps_per_quarter=2),
'drum_kit':
events_rnn_model.EventSequenceRnnConfig(
generator_pb2.GeneratorDetails(
id='drum_kit',
description='Drums RNN with multiple drums and binary counters.'
),
note_seq.LookbackEventSequenceEncoderDecoder(
note_seq.MultiDrumOneHotEncoding(),
lookback_distances=[],
binary_counter_bits=6),
contrib_training.HParams(
batch_size=128,
rnn_layer_sizes=[256, 256, 256],
dropout_keep_prob=0.5,
attn_length=32,
clip_norm=3,
learning_rate=0.001)),
'reduced_drum_kit':
events_rnn_model.EventSequenceRnnConfig(
generator_pb2.GeneratorDetails(
id='reduced_drum_kit',
description='Drums RNN without toms, rides and crashes (toms reinterpreted as snares, rides/crashes - as open hats).'
),
note_seq.LookbackEventSequenceEncoderDecoder(
events_rnn_model.EventSequenceRnnConfig(
generator_pb2.GeneratorDetails(
id='one_drum', description='Drums RNN with 2-state encoding.'),
note_seq.OneHotEventSequenceEncoderDecoder(
note_seq.MultiDrumOneHotEncoding(
[[39] + # use hand clap as default when decoding
list(range(note_seq.MIN_MIDI_PITCH, 39)) +
list(range(39, note_seq.MAX_MIDI_PITCH + 1))])),
contrib_training.HParams(batch_size=128,
rnn_layer_sizes=[128, 128],
dropout_keep_prob=0.5,
clip_norm=5,
learning_rate=0.001),
steps_per_quarter=2),
'drum_kit':
events_rnn_model.EventSequenceRnnConfig(
generator_pb2.GeneratorDetails(
id='drum_kit',
description='Drums RNN with multiple drums and binary counters.'),
note_seq.LookbackEventSequenceEncoderDecoder(
note_seq.MultiDrumOneHotEncoding(),
lookback_distances=[],
binary_counter_bits=6),
contrib_training.HParams(batch_size=128,
rnn_layer_sizes=[256, 256, 256],
dropout_keep_prob=0.5,
attn_length=32,
clip_norm=3,
learning_rate=0.001))
}
max_note=128)),
contrib_training.HParams(batch_size=128,
rnn_layer_sizes=[128, 128],
dropout_keep_prob=0.5,
clip_norm=5,
learning_rate=0.001),
min_note=0,
max_note=128,
transpose_to_key=None),
'lookback_rnn':
MelodyRnnConfig(
generator_pb2.GeneratorDetails(
id='lookback_rnn',
description='Melody RNN with lookback encoding.'),
note_seq.LookbackEventSequenceEncoderDecoder(
note_seq.MelodyOneHotEncoding(min_note=DEFAULT_MIN_NOTE,
max_note=DEFAULT_MAX_NOTE)),
contrib_training.HParams(batch_size=128,
rnn_layer_sizes=[128, 128],
dropout_keep_prob=0.5,
clip_norm=5,
learning_rate=0.001)),
#ここに独自モデル追加
'midi500_8bars_rnn':
MelodyRnnConfig(generator_pb2.GeneratorDetails(
id='midi500_8bars_rnn',
description=
'midi500_8bars_rnn RNN with lookback encoding and attention.'),
note_seq.KeyMelodyEncoderDecoder(min_note=0, max_note=128),
contrib_training.HParams(batch_size=128,
