| |
| |
| |
|
|
| import time as reqtime |
| import datetime |
| from pytz import timezone |
|
|
| import re |
| import tqdm |
|
|
| import gradio as gr |
|
|
| from x_transformer_1_23_2 import * |
| import random |
|
|
| from midi_to_colab_audio import midi_to_colab_audio |
| import TMIDIX |
|
|
| import matplotlib.pyplot as plt |
| |
| |
|
|
| def parsons_code_to_tokens(parsons_code_str): |
|
|
| tokens = [388] |
|
|
| for chr in parsons_code_str[1:]: |
|
|
| if chr == 'D': |
| tokens.extend([385]) |
|
|
| elif chr == 'R': |
| tokens.extend([386]) |
|
|
| elif chr == 'U': |
| tokens.extend([387]) |
|
|
| return tokens |
|
|
| |
|
|
| def Generate_Melody(input_parsons_code, |
| input_first_note_duration, |
| iinput_first_note_MIDI_pitch |
| ): |
| |
| print('=' * 70) |
| print('Req start time: {:%Y-%m-%d %H:%M:%S}'.format(datetime.datetime.now(PDT))) |
| start_time = reqtime.time() |
|
|
| print('=' * 70) |
| print('Requested settings:') |
| print('-' * 70) |
| print('Parsons code:', input_parsons_code) |
| print('First note duration:', input_first_note_duration) |
| print('First note MIDI pitch:', iinput_first_note_MIDI_pitch) |
| print('=' * 70) |
|
|
| |
|
|
| print('Instantiating Parsons Code Melody Transformer model...') |
|
|
| SEQ_LEN = 322 |
| PAD_IDX = 392 |
| |
| model = TransformerWrapper( |
| num_tokens = PAD_IDX+1, |
| max_seq_len = SEQ_LEN, |
| attn_layers = Decoder(dim = 1024, |
| depth = 4, |
| heads = 8, |
| rotary_pos_emb = True, |
| attn_flash = True |
| ) |
| ) |
| |
| model = AutoregressiveWrapper(model, ignore_index = PAD_IDX, pad_value=PAD_IDX) |
| |
| print('=' * 70) |
| print('Loading model checkpoint...') |
| |
| model_path = 'Parsons_Code_Melody_Transformer_Trained_Model_13786_steps_0.3058_loss_0.8819_acc.pth' |
| |
| model.load_state_dict(torch.load(model_path, map_location='cpu')) |
|
|
| model.cpu() |
| model.eval() |
|
|
| dtype = torch.bfloat16 |
| |
| ctx = torch.amp.autocast(device_type='cpu', dtype=dtype) |
|
|
| print('Done!') |
| print('=' * 70) |
|
|
| |
|
|
| print('Prepping Parsons code string...') |
|
|
| td_str = re.sub('[^*DRU]', '', input_parsons_code) |
| |
| print(len(td_str)) |
| print('=' * 70) |
| |
| if '*' in td_str and len(td_str) > 1: |
| code_mult = (64 // len(td_str[1:]))+1 |
| mult_code = ('*' + (td_str[1:] * code_mult))[:64] |
| |
| else: |
| mult_code = '*UUUUUUUDDDDDDDUUUUUUUDDDDDDDUUUUUUUDDDDDDDUUUUUUUDDDDDDDUUUUUUU' |
|
|
| pcode = parsons_code_to_tokens(mult_code) |
|
|
| print('Done!') |
| print('=' * 70) |
|
|
| |
|
|
| print('Generating melody...') |
|
|
| song = [] |
|
|
| song.append(389) |
| song.extend(pcode) |
| song.append(390) |
| |
| song.extend([388, 0, 10+128, 66+256]) |
| |
| for i in tqdm.tqdm(range(1, len(td_str[:64]))): |
| |
| song.append(pcode[i]) |
| |
| x = torch.tensor(song, dtype=torch.long, device='cpu') |
| |
| with ctx: |
| out = model.generate(x, |
| 3, |
| filter_logits_fn=top_k, |
| filter_kwargs={'k': 1}, |
| temperature=1.0, |
| return_prime=False, |
| verbose=False) |
| |
| y = out.tolist()[0] |
| |
| song.extend(y) |
|
|
| print('Done!') |
| print('=' * 70) |
| |
| |
| print('Rendering results...') |
| |
| print('=' * 70) |
| print('Sample INTs', song[:5]) |
| print('=' * 70) |
|
|
| song_f = [] |
|
|
| time = 0 |
| dur = 4 |
| vel = 90 |
| pitch = 60 |
| channel = 0 |
|
|
| for ss in song: |
|
|
| if 0 <= ss < 128: |
|
|
| time += ss * 32 |
|
|
| if 128 <= ss < 256: |
|
|
| dur = (ss-128) * 32 |
|
|
| if 256 <= ss < 384: |
|
|
| pitch = ss-256 |
|
|
| song_f.append(['note', time, dur, channel, pitch, vel, 0]) |
|
|
| fn1 = 'Parsons-Code-Melody-Transformer-Composition' |
|
|
| detailed_stats = TMIDIX.Tegridy_ms_SONG_to_MIDI_Converter(song_f, |
| output_signature = 'Parsons Code Melody Transformer', |
| output_file_name = fn1, |
| track_name='Project Los Angeles' |
| ) |
| |
| new_fn = fn1+'.mid' |
| |
| |
| audio = midi_to_colab_audio(new_fn, |
| soundfont_path=soundfont, |
| sample_rate=16000, |
| volume_scale=10, |
| output_for_gradio=True |
| ) |
| |
| print('Done!') |
| print('=' * 70) |
|
|
| |
|
|
| output_midi_title = str(fn1) |
| output_midi = str(new_fn) |
| output_audio = (16000, audio) |
| |
| output_plot = TMIDIX.plot_ms_SONG(song_f, plot_title=output_midi_title, return_plt=True) |
|
|
| print('Output MIDI file name:', output_midi) |
| print('Output MIDI title:', output_midi_title) |
| print('=' * 70) |
| |
|
|
| |
| |
| print('-' * 70) |
| print('Req end time: {:%Y-%m-%d %H:%M:%S}'.format(datetime.datetime.now(PDT))) |
| print('-' * 70) |
| print('Req execution time:', (reqtime.time() - start_time), 'sec') |
|
|
| return output_midi_title, output_midi, output_audio, output_plot |
|
|
| |
|
|
| if __name__ == "__main__": |
| |
| PDT = timezone('US/Pacific') |
| |
| print('=' * 70) |
| print('App start time: {:%Y-%m-%d %H:%M:%S}'.format(datetime.datetime.now(PDT))) |
| print('=' * 70) |
|
|
| soundfont = "SGM-v2.01-YamahaGrand-Guit-Bass-v2.7.sf2" |
|
|
| app = gr.Blocks() |
| |
| with app: |
| |
| gr.Markdown("<h1 style='text-align: center; margin-bottom: 1rem'>Parsons Code Melody Transformer</h1>") |
| gr.Markdown("<h1 style='text-align: center; margin-bottom: 1rem'>Generate unique melodies from Parsons codes</h1>") |
| gr.Markdown( |
| "\n\n" |
| "This is a demo for Clean Melodies subset of Tegridy MIDI Dataset\n\n" |
| "Check out [Tegridy MIDI Dataset](https://github.com/asigalov61/Tegridy-MIDI-Dataset) on GitHub!\n\n" |
| ) |
| |
| gr.Markdown("## Enter Parsons code:") |
| |
| input_parsons_code = gr.Textbox(label="Parsons code", |
| info="Make sure your Parsons code starts with *", |
| lines=1, |
| value="*" |
| ) |
| |
| clr_btn = gr.ClearButton(components=input_parsons_code) |
|
|
| def reset_pcode(): |
| return '*' |
|
|
| clr_btn.click(reset_pcode, outputs=input_parsons_code) |
|
|
| gr.Markdown("## Select generation options:") |
| |
| input_first_note_duration = gr.Slider(1, 127, value=15, step=1, label="First note duration value") |
| iinput_first_note_MIDI_pitch = gr.Slider(1, 127, value=60, step=1, label="First note MIDI pitch") |
| |
| run_btn = gr.Button("Generate melody", variant="primary") |
| |
| gr.Markdown("## Output results") |
|
|
| output_midi_title = gr.Textbox(label="Output MIDI title") |
| output_audio = gr.Audio(label="Output MIDI audio", format="mp3", elem_id="midi_audio") |
| output_plot = gr.Plot(label="Output MIDI score plot") |
| output_midi = gr.File(label="Output MIDI file", file_types=[".mid"]) |
|
|
| run_event = run_btn.click(Generate_Melody, [input_parsons_code, |
| input_first_note_duration, |
| iinput_first_note_MIDI_pitch |
| ], |
| [output_midi_title, output_midi, output_audio, output_plot]) |
|
|
| gr.Examples( |
| [["*UUUUUUUDDDDDDDUUUUUUUDDDDDDDUUUUUUUDDDDDDDUUUUUUUDDDDDDDUUUUUUU", 15, 60], |
| ["*UDDDUDDDUDRURUDUUDRDDUDDRUDUDURUDRUDUDDDUDDDRDUURUDUUDDDUDRRUUD", 15, 60], |
| ["*DUDDDUUDDUUDDUDUDDDUUUUUDDDDUDDDUUDDUUDDUUDUDDUDDDUUDDUUDDUDUDD", 15, 60], |
| ["*DUUDDRDDUURUDUDDDUDDDDDURDDUDRDURUURUURDDDUURDUURUDUUDURDUDUDRD", 15, 60], |
| ["*UUUDDUUUDDDDDUDDUUDDDDUUDDUDDDDDUUUDDDDDUDDUUUDDDURDUDUUUDDUUUD", 15, 60], |
| ["*UDUUDRUDDUDRURUURUUUUUDUDDUDDUDDUDRUDDUDRUDDDUDUUDRUDDUDRURUURU", 15, 60], |
| ], |
| [input_parsons_code, |
| input_first_note_duration, |
| iinput_first_note_MIDI_pitch |
| ], |
| [output_midi_title, output_midi, output_audio, output_plot], |
| Generate_Melody, |
| cache_examples=True, |
| ) |
| |
| app.queue().launch() |
