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import time as reqtime |
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import datetime |
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from pytz import timezone |
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import re |
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import gradio as gr |
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from x_transformer_1_23_2 import * |
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import random |
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from midi_to_colab_audio import midi_to_colab_audio |
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import TMIDIX |
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import matplotlib.pyplot as plt |
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def parsons_code_to_tokens(parsons_code_str): |
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tokens = [388] |
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for chr in parsons_code_str[1:]: |
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if chr == 'D': |
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tokens.extend([385]) |
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elif chr == 'R': |
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tokens.extend([386]) |
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elif chr == 'U': |
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tokens.extend([387]) |
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return tokens |
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def Generate_Melody(input_parsons_code, |
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input_first_note_duration, |
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iinput_first_note_MIDI_pitch, |
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): |
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print('=' * 70) |
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print('Req start time: {:%Y-%m-%d %H:%M:%S}'.format(datetime.datetime.now(PDT))) |
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start_time = reqtime.time() |
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print('=' * 70) |
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print('Requested settings:') |
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print('-' * 70) |
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print('Parsons code:', input_parsons_code) |
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print('First note duration:', input_first_note_duration) |
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print('First note MIDI pitch:', iinput_first_note_MIDI_pitch) |
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print('=' * 70) |
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print('Instantiating Parsons Code Melody Transformer model...') |
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SEQ_LEN = 322 |
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PAD_IDX = 392 |
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model = TransformerWrapper( |
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num_tokens = PAD_IDX+1, |
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max_seq_len = SEQ_LEN, |
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attn_layers = Decoder(dim = 1024, |
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depth = 4, |
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heads = 8, |
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rotary_pos_emb = True, |
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attn_flash = True |
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) |
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) |
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model = AutoregressiveWrapper(model, ignore_index = PAD_IDX, pad_value=PAD_IDX) |
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print('=' * 70) |
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print('Loading model checkpoint...') |
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model_path = 'Parsons_Code_Melody_Transformer_Trained_Model_13786_steps_0.3058_loss_0.8819_acc.pth' |
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model.load_state_dict(torch.load(model_path, map_location='cpu')) |
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model.cpu() |
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model.eval() |
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dtype = torch.bfloat16 |
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ctx = torch.amp.autocast(device_type='cpu', dtype=dtype) |
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print('Done!') |
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print('=' * 70) |
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print('Prepping Parsons code string...') |
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td_str = '*DUDUA' |
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td_str = re.sub('[^*DRU]', '', td_str) |
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print(len(td_str)) |
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print('=' * 70) |
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if '*' in td_str and len(td_str) > 1: |
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code_mult = (64 // len(td_str[1:]))+1 |
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mult_code = ('*' + (td_str[1:] * code_mult))[:64] |
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else: |
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mult_code = '*UUUUUUUDDDDDDDUUUUUUUDDDDDDDUUUUUUUDDDDDDDUUUUUUUDDDDDDDUUUUUUU' |
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print('Done!') |
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print('=' * 70) |
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print('Rendering results...') |
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print('=' * 70) |
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print('Sample INTs', mixed_song[:5]) |
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print('=' * 70) |
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output_score, patches, overflow_patches = TMIDIX.patch_enhanced_score_notes(mixed_song) |
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detailed_stats = TMIDIX.Tegridy_ms_SONG_to_MIDI_Converter(output_score, |
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output_signature = 'Harmonic Melody MIDI Mixer', |
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output_file_name = fn1, |
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track_name='Project Los Angeles', |
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list_of_MIDI_patches=patches, |
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timings_multiplier=16 |
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) |
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new_fn = fn1+'.mid' |
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audio = midi_to_colab_audio(new_fn, |
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soundfont_path=soundfont, |
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sample_rate=16000, |
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volume_scale=10, |
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output_for_gradio=True |
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) |
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print('Done!') |
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print('=' * 70) |
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output_midi_title = str(fn1) |
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output_midi_summary = str(MIDI_Summary) |
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output_midi = str(new_fn) |
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output_audio = (16000, audio) |
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for o in output_score: |
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o[1] *= 16 |
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o[2] *= 16 |
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output_plot = TMIDIX.plot_ms_SONG(output_score, plot_title=output_midi_title, return_plt=True) |
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print('Output MIDI file name:', output_midi) |
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print('Output MIDI title:', output_midi_title) |
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print('Output MIDI summary:', MIDI_Summary) |
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print('=' * 70) |
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print('-' * 70) |
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print('Req end time: {:%Y-%m-%d %H:%M:%S}'.format(datetime.datetime.now(PDT))) |
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print('-' * 70) |
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print('Req execution time:', (reqtime.time() - start_time), 'sec') |
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return output_midi_title, output_midi_summary, output_midi, output_audio, output_plot |
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if __name__ == "__main__": |
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PDT = timezone('US/Pacific') |
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print('=' * 70) |
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print('App start time: {:%Y-%m-%d %H:%M:%S}'.format(datetime.datetime.now(PDT))) |
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print('=' * 70) |
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soundfont = "SGM-v2.01-YamahaGrand-Guit-Bass-v2.7.sf2" |
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app = gr.Blocks() |
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with app: |
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gr.Markdown("<h1 style='text-align: center; margin-bottom: 1rem'>Parsons Code Melody Transformer</h1>") |
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gr.Markdown("<h1 style='text-align: center; margin-bottom: 1rem'>Generate unique melodies from Parsons codes</h1>") |
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gr.Markdown( |
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"\n\n" |
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"This is a demo for Clean Melodies subset of Tegridy MIDI Dataset\n\n" |
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"Check out [Tegridy MIDI Dataset](https://github.com/asigalov61/Tegridy-MIDI-Dataset) on GitHub!\n\n" |
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) |
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gr.Markdown("## Enter Parsons code below") |
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input_parsons_code = gr.Textbox(label="Enter your Parsons code here", |
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info="Make sure your code starts with *", |
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lines=1, |
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value="*", |
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), |
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gr.Markdown("## Select generation options") |
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input_first_note_duration = gr.Slider(1, 127, value=15, step=1, label="First note duration value") |
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iinput_first_note_MIDI_pitch = gr.Slider(1, 127, value=60, step=1, label="First note MIDI pitch") |
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run_btn = gr.Button("Generate melody", variant="primary") |
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clear_btn = gr.ClearButton(components=[input_parsons_code]) |
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gr.Markdown("## Output results") |
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output_midi_title = gr.Textbox(label="Output MIDI title") |
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output_midi_summary = gr.Textbox(label="Output MIDI summary") |
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output_audio = gr.Audio(label="Output MIDI audio", format="mp3", elem_id="midi_audio") |
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output_plot = gr.Plot(label="Output MIDI score plot") |
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output_midi = gr.File(label="Output MIDI file", file_types=[".mid"]) |
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run_event = run_btn.click(Generate_Melody, [input_parsons_code, |
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input_first_note_duration, |
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iinput_first_note_MIDI_pitch, |
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], |
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[output_midi_title, output_midi_summary, output_midi, output_audio, output_plot]) |
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gr.Examples( |
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[["*UUUUUUUDDDDDDDUUUUUUUDDDDDDDUUUUUUUDDDDDDDUUUUUUUDDDDDDDUUUUUUU", 15, 60], |
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], |
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[input_parsons_code, |
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input_first_note_duration, |
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iinput_first_note_MIDI_pitch, |
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], |
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[output_midi_title, output_midi_summary, output_midi, output_audio, output_plot], |
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Generate_Melody, |
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cache_examples=True, |
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) |
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app.queue().launch() |
