asigalov61's picture
Update app.py
1dd49e0 verified
#=========================================================================
# https://huggingface.co/spaces/asigalov61/Parsons-Code-Melody-Transformer
#=========================================================================
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(
"![Visitors](https://api.visitorbadge.io/api/visitors?path=asigalov61.Parsons-Code-Melody-Transformer&style=flat)\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()