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,