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| #================================================================================== | |
| # https://huggingface.co/spaces/asigalov61/Ultimate-Chords-Progressions-Transformer | |
| #================================================================================== | |
| import time as reqtime | |
| import datetime | |
| from pytz import timezone | |
| import torch | |
| import spaces | |
| import gradio as gr | |
| from x_transformer_1_23_2 import * | |
| import random | |
| import statistics | |
| import copy | |
| import tqdm | |
| from midi_to_colab_audio import midi_to_colab_audio | |
| import TMIDIX | |
| import matplotlib.pyplot as plt | |
| # ================================================================================================= | |
| def Generate_Chords(input_midi, input_num_prime_chords, input_num_gen_chords, input_conditioning_type): | |
| print('=' * 70) | |
| print('Req start time: {:%Y-%m-%d %H:%M:%S}'.format(datetime.datetime.now(PDT))) | |
| start_time = reqtime.time() | |
| print('=' * 70) | |
| print('Instantiating the model...') | |
| SEQ_LEN = 8192 | |
| PAD_IDX = 2239 | |
| DEVICE = 'cuda' # 'cpu' | |
| # instantiate the model | |
| model = TransformerWrapper( | |
| num_tokens = PAD_IDX+1, | |
| max_seq_len = SEQ_LEN, | |
| attn_layers = Decoder(dim = 2048, | |
| depth = 8, | |
| heads = 32, | |
| rotary_pos_emb = True, | |
| attn_flash = True | |
| ) | |
| ) | |
| model = AutoregressiveWrapper(model, ignore_index = PAD_IDX, pad_value=PAD_IDX) | |
| model.to(DEVICE) | |
| print('Done!') | |
| print('=' * 70) | |
| print('Loading model checkpoint...') | |
| model.load_state_dict( | |
| torch.load('Ultimate_Chords_Progressions_Transformer_Trained_Model_LAX_5858_steps_0.4506_loss_0.8724_acc.pth', | |
| map_location=DEVICE)) | |
| model.eval() | |
| print('Done!') | |
| print('=' * 70) | |
| if DEVICE == 'cpu': | |
| dtype = torch.bfloat16 | |
| else: | |
| dtype = torch.bfloat16 | |
| ctx = torch.amp.autocast(device_type=DEVICE, dtype=dtype) | |
| print('Done!') | |
| print('=' * 70) | |
| fn = os.path.basename(input_midi.name) | |
| fn1 = fn.split('.')[0] | |
| print('=' * 70) | |
| print('Input file name:', fn) | |
| print('Num prime chords:', input_num_prime_chords) | |
| print('Num gen chords:', input_num_gen_chords) | |
| print('Conditioning type:', input_conditioning_type) | |
| print('=' * 70) | |
| #=============================================================================== | |
| raw_score = TMIDIX.midi2single_track_ms_score(input_midi.name) | |
| escore_notes = TMIDIX.advanced_score_processor(raw_score, return_enhanced_score_notes=True) | |
| if escore_notes: | |
| escore_notes = TMIDIX.augment_enhanced_score_notes(escore_notes[0], timings_divider=32, legacy_timings=True) | |
| if escore_notes: | |
| #======================================================= | |
| # PRE-PROCESSING | |
| # checking number of instruments in a composition | |
| instruments_list = sorted(set([e[6] for e in escore_notes])) | |
| instruments_list_without_drums = sorted(set([e[6] for e in escore_notes if e[3] != 9])) | |
| main_instruments_list = sorted(set([e[6] for e in escore_notes if e[6] < 80])) | |
| comp_times = [e[1] for e in escore_notes if e[6] < 80] | |
| comp_dtimes = [max(1, min(127, b-a)) for a, b in zip(comp_times[:-1], comp_times[1:]) if b-a != 0] | |
| avg_comp_dtime = max(0, min(127, int(sum(comp_dtimes) / len(comp_dtimes)))) | |
| #======================================================= | |
| # FINAL PROCESSING | |
| #======================================================= | |
| # Adjusting avg velocity | |
| vels = [e[5] for e in escore_notes] | |
| avg_vel = int(sum(vels) / len(vels)) | |
| if avg_vel < 60: | |
| TMIDIX.adjust_score_velocities(escore_notes, avg_vel * 2) | |
| melody_chords = [] | |
| melody_chords2 = [] | |
| mel_cho = [] | |
| #======================================================= | |
| # Break between compositions / Intro seq | |
| if 128 in instruments_list: | |
| drums_present = 1931 # Yes | |
| else: | |
| drums_present = 1930 # No | |
| melody_chords.extend([1929, drums_present]) | |
| mel_cho.extend([1929, drums_present]) | |
| #======================================================= | |
| # Composition patches list | |
| melody_chords.extend([i+1932 for i in instruments_list_without_drums]) | |
| mel_cho.extend([i+1932 for i in instruments_list_without_drums]) | |
| #======================================================= | |
| # Composition avg pitch and dtime | |
| mode_instruments_pitch = statistics.mode([e[4] for e in escore_notes if e[6] < 80]) | |
| melody_chords.extend([2060+mode_instruments_pitch, 2188+avg_comp_dtime]) | |
| mel_cho.extend([2060+mode_instruments_pitch, 2188+avg_comp_dtime]) | |
| melody_chords2.append(mel_cho) | |
| #======================================================= | |
| # MAIN PROCESSING CYCLE | |
| #======================================================= | |
| cscore = TMIDIX.chordify_score([1000, escore_notes]) | |
| pc = cscore[0] # Previous chord | |
| for i, c in enumerate(cscore): | |
| c.sort(key=lambda x: x[6]) # Sorting by patch | |
| #======================================================= | |
| # Outro seq | |
| #if len(cscore) > 256: | |
| # if len(cscore) - i == 64: | |
| # melody_chords.extend([2236]) | |
| #======================================================= | |
| # Timings... | |
| # Cliping all values... | |
| delta_time = max(0, min(127, c[0][1]-pc[0][1])) | |
| #======================================================= | |
| # Chords... | |
| cpitches = sorted([e[4] for e in c if e[3] != 9]) | |
| dpitches = [e[4] for e in c if e[3] == 9] | |
| tones_chord = sorted(set([p % 12 for p in cpitches])) | |
| if tones_chord: | |
| if tones_chord not in TMIDIX.ALL_CHORDS_SORTED: | |
| tones_chord_tok = 644 | |
| tones_chord_tok = TMIDIX.ALL_CHORDS_SORTED.index(TMIDIX.advanced_check_and_fix_tones_chord(tones_chord, cpitches[-1])) | |
| else: | |
| tones_chord_tok = TMIDIX.ALL_CHORDS_SORTED.index(tones_chord) # 321 | |
| if dpitches: | |
| if tones_chord_tok == 644: | |
| tones_chord_tok = 645 | |
| else: | |
| tones_chord_tok += 321 | |
| else: | |
| tones_chord_tok = 643 # Drums-only chord | |
| #======================================================= | |
| # Writing chord/time... | |
| melody_chords.extend([tones_chord_tok, delta_time+646]) | |
| mel_cho = [] | |
| mel_cho.extend([tones_chord_tok, delta_time+646]) | |
| #======================================================= | |
| # Notes... | |
| pp = -1 | |
| for e in c: | |
| #======================================================= | |
| # Duration | |
| dur = max(0, min(63, int(max(0, e[2] // 4) * 2))) | |
| # Pitch | |
| ptc = max(1, min(127, e[4])) | |
| # Octo-velocity | |
| vel = max(8, min(127, (max(1, e[5] // 8) * 8))) | |
| velocity = round(vel / 15)-1 | |
| # Patch | |
| pat = max(0, min(128, e[6])) | |
| if 7 < pat < 80: | |
| ptc += 128 | |
| elif 79 < pat < 128: | |
| ptc += 256 | |
| elif pat == 128: | |
| ptc += 384 | |
| #======================================================= | |
| # FINAL NOTE SEQ | |
| # Writing final note asynchronously | |
| dur_vel = (8 * dur) + velocity # 512 | |
| if pat != pp: | |
| melody_chords.extend([pat+774, ptc+904, dur_vel+1416]) # 1928 | |
| mel_cho.extend([pat+774, ptc+904, dur_vel+1416]) | |
| else: | |
| melody_chords.extend([ptc+904, dur_vel+1416]) | |
| mel_cho.extend([ptc+904, dur_vel+1416]) | |
| pp = pat | |
| pc = c | |
| melody_chords2.append(mel_cho) | |
| #======================================================= | |
| #melody_chords.extend([2237]) # EOS | |
| #======================================================= | |
| # TOTAL DICTIONARY SIZE 2237+1=2238 | |
| #======================================================= | |
| print('Done!') | |
| print('=' * 70) | |
| print('Melody chords length:', len(melody_chords)) | |
| print('=' * 70) | |
| #================================================================== | |
| print('=' * 70) | |
| print('Sample output events', melody_chords[:12]) | |
| print('=' * 70) | |
| print('Generating...') | |
| temperature=0.9 | |
| output = [] | |
| for m in melody_chords2[:input_num_prime_chords]: | |
| output.extend(m) | |
| for ct in tqdm.tqdm(melody_chords2[input_num_prime_chords:input_num_gen_chords]): | |
| if input_conditioning_type == 'Chords': | |
| output.extend(ct[:1]) | |
| else: | |
| output.extend(ct[:2]) | |
| y = 646 | |
| while y > 645: | |
| x = torch.LongTensor(output).to(DEVICE) | |
| with ctx: | |
| out = model.generate(x, | |
| 1, | |
| temperature=temperature, | |
| eos_token=2237, | |
| return_prime=False, | |
| verbose=False) | |
| y = out.tolist()[0][0] | |
| if y > 645: | |
| output.append(y) | |
| print('=' * 70) | |
| print('Done!') | |
| print('=' * 70) | |
| #=============================================================================== | |
| print('Rendering results...') | |
| print('=' * 70) | |
| print('Sample INTs', output[:12]) | |
| print('=' * 70) | |
| if len(output) != 0: | |
| song = output | |
| song_f = [] | |
| time = 0 | |
| dur = 4 | |
| vel = 90 | |
| pitch = 60 | |
| channel = 0 | |
| patches = [0] * 16 | |
| patches[9] = 9 | |
| for ss in song: | |
| if 645 < ss < 774: | |
| time += (ss-646) | |
| if 773 < ss < 904: | |
| pat = (ss - 774) | |
| chan = (pat // 8) | |
| if 0 <= chan < 9: | |
| channel = chan | |
| elif 8 < chan < 15: | |
| channel = chan + 1 | |
| elif chan == 16: | |
| channel = 9 | |
| if 903 < ss < 1416: | |
| pitch = (ss-904) % 128 | |
| if 1415 < ss < 1928: | |
| dur = (((ss-1416) // 8)+1) * 2 | |
| vel = (((ss-1416) % 8)+1) * 15 | |
| song_f.append(['note', time, dur, channel, pitch, vel, pat]) | |
| song_f, patches, overflow_patches = TMIDIX.patch_enhanced_score_notes(song_f) | |
| fn1 = "Ultimate-Chords-Progressions-Transformer-Composition" | |
| detailed_stats = TMIDIX.Tegridy_ms_SONG_to_MIDI_Converter(song_f, | |
| output_signature = 'Ultimate Chords Progressions Transformer', | |
| output_file_name = fn1, | |
| track_name='Project Los Angeles', | |
| list_of_MIDI_patches=patches, | |
| timings_multiplier=32 | |
| ) | |
| 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_summary = str(song_f[:3]) | |
| output_midi = str(new_fn) | |
| output_audio = (16000, audio) | |
| output_plot = TMIDIX.plot_ms_SONG(song_f, plot_title=output_midi, return_plt=True, timings_multiplier=32) | |
| print('Output MIDI file name:', output_midi) | |
| print('Output MIDI title:', output_midi_title) | |
| print('Output MIDI summary:', '') | |
| 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') | |
| print('*' * 70) | |
| return output_midi_title, output_midi_summary, 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'>Ultimate Chords Progressions Transformer</h1>") | |
| gr.Markdown("<h1 style='text-align: center; margin-bottom: 1rem'>Self-correcting multi-instrumental chords-conditioned music RoPE transformer</h1>") | |
| gr.Markdown( | |
| "\n\n" | |
| "Check out [Ultimate Chords Progressions Transformer](https://huggingface.co/asigalov61/Ultimate-Chords-Progressions-Transformer) on Hugging Face!\n\n" | |
| "[Open In Colab]" | |
| "(https://colab.research.google.com/github/asigalov61/Chords-Progressions-Transformer/blob/main/Chords_Progressions_Transformer.ipynb)" | |
| " for faster execution and endless generation" | |
| ) | |
| gr.Markdown("## Upload your MIDI or select a sample example MIDI") | |
| input_midi = gr.File(label="Input MIDI", file_types=[".midi", ".mid", ".kar"]) | |
| input_num_prime_chords = gr.Slider(1, 128, value=1, step=1, label="Number of prime chords") | |
| input_num_gen_chords = gr.Slider(4, 128, value=32, step=1, label="Number of composition chords to generate progression for") | |
| input_conditioning_type = gr.Radio(["Chords", "Chords-Times"], value="Chords", label="Conditioning type") | |
| run_btn = gr.Button("Generate Chords", variant="primary") | |
| gr.Markdown("## Generation results") | |
| output_midi_title = gr.Textbox(label="Output MIDI title") | |
| output_midi_summary = gr.Textbox(label="Output MIDI summary") | |
| output_audio = gr.Audio(label="Output MIDI audio", format="wav", 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_Chords, [input_midi, input_num_prime_chords, input_num_gen_chords, input_conditioning_type], | |
| [output_midi_title, output_midi_summary, output_midi, output_audio, output_plot]) | |
| gr.Examples( | |
| [["Chords-Progressions-Transformer-Piano-Seed-1.mid", 16, 128, "Chords"], | |
| ["Chords-Progressions-Transformer-Piano-Seed-2.mid", 16, 128, "Chords-Times"], | |
| ["Chords-Progressions-Transformer-Piano-Seed-3.mid", 16, 128, "Chords-Times"], | |
| ["Chords-Progressions-Transformer-Piano-Seed-4.mid", 16, 128, "Chords"], | |
| ["Chords-Progressions-Transformer-Piano-Seed-5.mid", 16, 128, "Chords-Times"], | |
| ["Chords-Progressions-Transformer-Piano-Seed-6.mid", 16, 128, "Chords-Times"], | |
| ["Chords-Progressions-Transformer-MI-Seed-1.mid", 16, 128, "Chords"], | |
| ["Chords-Progressions-Transformer-MI-Seed-2.mid", 16, 128, "Chords-Times"], | |
| ["Chords-Progressions-Transformer-MI-Seed-3.mid", 16, 128, "Chords-Times"], | |
| ["Chords-Progressions-Transformer-MI-Seed-4.mid", 16, 128, "Chords-Times"], | |
| ["Chords-Progressions-Transformer-MI-Seed-5.mid", 16, 128, "Chords"], | |
| ["Chords-Progressions-Transformer-MI-Seed-6.mid", 16, 128, "Chords-Times"] | |
| ], | |
| [input_midi, input_num_prime_chords, input_num_gen_chords, input_conditioning_type], | |
| [output_midi_title, output_midi_summary, output_midi, output_audio, output_plot], | |
| Generate_Chords, | |
| cache_examples=False, | |
| ) | |
| app.queue().launch() |