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import os.path
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 tqdm
from midi_to_colab_audio import midi_to_colab_audio
import TMIDIX
import matplotlib.pyplot as plt
in_space = os.getenv("SYSTEM") == "spaces"
# =================================================================================================
@spaces.GPU
def Text_to_Music(input_title, input_num_tokens, input_prompt_type):
print('=' * 70)
print('Req start time: {:%Y-%m-%d %H:%M:%S}'.format(datetime.datetime.now(PDT)))
start_time = reqtime.time()
print('Loading model...')
SEQ_LEN = 4096 # Models seq len
PAD_IDX = 2571 # Models pad index
DEVICE = 'cuda' # 'cuda'
# instantiate the model
model = TransformerWrapper(
num_tokens = PAD_IDX+1,
max_seq_len = SEQ_LEN,
attn_layers = Decoder(dim = 2048, depth = 8, heads = 16, attn_flash = True)
)
model = AutoregressiveWrapper(model, ignore_index = PAD_IDX)
model.to(DEVICE)
print('=' * 70)
print('Loading model checkpoint...')
model.load_state_dict(
torch.load('Text_to_Music_Transformer_Medium_Trained_Model_33934_steps_0.6093_loss_0.813_acc.pth',
map_location=DEVICE))
print('=' * 70)
model.eval()
if DEVICE == 'cpu':
dtype = torch.bfloat16
else:
dtype = torch.float16
ctx = torch.amp.autocast(device_type=DEVICE, dtype=dtype)
print('Done!')
print('=' * 70)
input_num_tokens = max(8, min(2048, input_num_tokens))
print('-' * 70)
print('Input title:', input_title)
print('Req num toks:', input_num_tokens)
print('Open-ended prompt:', input_prompt_type)
print('-' * 70)
#===============================================================================
print('Setting up model patches and loading helper functions...')
# @title Setup and load model channels MIDI patches
model_channel_0_piano_family = "Acoustic Grand" # @param ["Acoustic Grand", "Bright Acoustic", "Electric Grand", "Honky-Tonk", "Electric Piano 1", "Electric Piano 2", "Harpsichord", "Clav"]
model_channel_1_chromatic_percussion_family = "Music Box" # @param ["Celesta", "Glockenspiel", "Music Box", "Vibraphone", "Marimba", "Xylophone", "Tubular Bells", "Dulcimer"]
model_channel_2_organ_family = "Church Organ" # @param ["Drawbar Organ", "Percussive Organ", "Rock Organ", "Church Organ", "Reed Organ", "Accordion", "Harmonica", "Tango Accordion"]
model_channel_3_guitar_family = "Acoustic Guitar(nylon)" # @param ["Acoustic Guitar(nylon)", "Acoustic Guitar(steel)", "Electric Guitar(jazz)", "Electric Guitar(clean)", "Electric Guitar(muted)", "Overdriven Guitar", "Distortion Guitar", "Guitar Harmonics"]
model_channel_4_bass_family = "Fretless Bass" # @param ["Acoustic Bass", "Electric Bass(finger)", "Electric Bass(pick)", "Fretless Bass", "Slap Bass 1", "Slap Bass 2", "Synth Bass 1", "Synth Bass 2"]
model_channel_5_strings_family = "Violin" # @param ["Violin", "Viola", "Cello", "Contrabass", "Tremolo Strings", "Pizzicato Strings", "Orchestral Harp", "Timpani"]
model_channel_6_ensemble_family = "Choir Aahs" # @param ["String Ensemble 1", "String Ensemble 2", "SynthStrings 1", "SynthStrings 2", "Choir Aahs", "Voice Oohs", "Synth Voice", "Orchestra Hit"]
model_channel_7_brass_family = "Trumpet" # @param ["Trumpet", "Trombone", "Tuba", "Muted Trumpet", "French Horn", "Brass Section", "SynthBrass 1", "SynthBrass 2"]
model_channel_8_reed_family = "Alto Sax" # @param ["Soprano Sax", "Alto Sax", "Tenor Sax", "Baritone Sax", "Oboe", "English Horn", "Bassoon", "Clarinet"]
model_channel_9_pipe_family = "Flute" # @param ["Piccolo", "Flute", "Recorder", "Pan Flute", "Blown Bottle", "Skakuhachi", "Whistle", "Ocarina"]
model_channel_10_synth_lead_family = "Lead 8 (bass+lead)" # @param ["Lead 1 (square)", "Lead 2 (sawtooth)", "Lead 3 (calliope)", "Lead 4 (chiff)", "Lead 5 (charang)", "Lead 6 (voice)", "Lead 7 (fifths)", "Lead 8 (bass+lead)"]
model_channel_11_synth_pad_family = "Pad 2 (warm)" # @param ["Pad 1 (new age)", "Pad 2 (warm)", "Pad 3 (polysynth)", "Pad 4 (choir)", "Pad 5 (bowed)", "Pad 6 (metallic)", "Pad 7 (halo)", "Pad 8 (sweep)"]
model_channel_12_synth_effects_family = "FX 3 (crystal)" # @param ["FX 1 (rain)", "FX 2 (soundtrack)", "FX 3 (crystal)", "FX 4 (atmosphere)", "FX 5 (brightness)", "FX 6 (goblins)", "FX 7 (echoes)", "FX 8 (sci-fi)"]
model_channel_13_ethnic_family = "Banjo" # @param ["Sitar", "Banjo", "Shamisen", "Koto", "Kalimba", "Bagpipe", "Fiddle", "Shanai"]
model_channel_14_percussive_family = "Melodic Tom" # @param ["Tinkle Bell", "Agogo", "Steel Drums", "Woodblock", "Taiko Drum", "Melodic Tom", "Synth Drum", "Reverse Cymbal"]
model_channel_15_sound_effects_family = "Bird Tweet" # @param ["Guitar Fret Noise", "Breath Noise", "Seashore", "Bird Tweet", "Telephone Ring", "Helicopter", "Applause", "Gunshot"]
model_channel_16_drums_family = "Drums" # @param ["Drums"]
print('=' * 70)
print('Loading helper functions...')
def txt2tokens(txt):
return [ord(char)+2440 if 0 < ord(char) < 128 else 0+2440 for char in txt.lower()]
def tokens2txt(tokens):
return [chr(tok-2440) for tok in tokens if 0+2440 < tok < 128+2440 ]
print('=' * 70)
print('Setting up patches...')
print('=' * 70)
instruments = [v[1] for v in TMIDIX.Number2patch.items()]
patches = [instruments.index(model_channel_0_piano_family),
instruments.index(model_channel_1_chromatic_percussion_family),
instruments.index(model_channel_2_organ_family),
instruments.index(model_channel_3_guitar_family),
instruments.index(model_channel_4_bass_family),
instruments.index(model_channel_5_strings_family),
instruments.index(model_channel_6_ensemble_family),
instruments.index(model_channel_7_brass_family),
instruments.index(model_channel_8_reed_family),
9, # Drums patch
instruments.index(model_channel_9_pipe_family),
instruments.index(model_channel_10_synth_lead_family),
instruments.index(model_channel_11_synth_pad_family),
instruments.index(model_channel_12_synth_effects_family),
instruments.index(model_channel_13_ethnic_family),
instruments.index(model_channel_15_sound_effects_family)
]
print('Done!')
print('=' * 70)
print('Generating...')
#@title Standard Text-to-Music Generator
#@markdown Prompt settings
song_title_prompt = input_title
open_ended_prompt = input_prompt_type
#@markdown Generation settings
number_of_tokens_to_generate = input_num_tokens
number_of_batches_to_generate = 1 #@param {type:"slider", min:1, max:16, step:1}
temperature = 0.9 # @param {type:"slider", min:0.1, max:1, step:0.05}
print('=' * 70)
print('Text-to-Music Model Generator')
print('=' * 70)
if song_title_prompt == '':
outy = [2569]
else:
if open_ended_prompt:
outy = [2569] + txt2tokens(song_title_prompt)
else:
outy = [2569] + txt2tokens(song_title_prompt) + [2570]
print('Selected prompt sequence:')
print(outy[:12])
print('=' * 70)
torch.cuda.empty_cache()
inp = [outy] * number_of_batches_to_generate
inp = torch.LongTensor(inp).cuda()
with ctx:
out = model.generate(inp,
number_of_tokens_to_generate,
temperature=temperature,
return_prime=True,
verbose=False)
out0 = out.tolist()
print('=' * 70)
print('Done!')
print('=' * 70)
#===============================================================================
print('Rendering results...')
print('=' * 70)
out1 = out0[0]
print('Sample INTs', out1[:12])
print('=' * 70)
generated_song_title = ''.join(tokens2txt(out1)).title()
print('Generated song title:', generated_song_title)
print('=' * 70)
if len(out1) != 0:
song = out1
song_f = []
time = 0
dur = 0
vel = 90
pitch = 0
channel = 0
chan = 0
for ss in song:
if 0 <= ss < 128:
time += ss * 32
if 128 <= ss < 256:
dur = (ss-128) * 32
if 256 <= ss < 2432:
chan = (ss-256) // 128
if chan < 9:
channel = chan
elif 9 < chan < 15:
channel = chan+1
elif chan == 15:
channel = 15
elif chan == 16:
channel = 9
pitch = (ss-256) % 128
if 2432 <= ss < 2440:
vel = (((ss-2432)+1) * 15)-1
song_f.append(['note', time, dur, channel, pitch, vel, chan*8 ])
fn1 = "Text-to-Music-Transformer-Composition"
detailed_stats = TMIDIX.Tegridy_ms_SONG_to_MIDI_Converter(song_f,
output_signature = 'Text-to-Music Transformer',
output_file_name = fn1,
track_name='Project Los Angeles',
list_of_MIDI_patches=patches
)
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 = generated_song_title
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)
print('Output MIDI file name:', output_midi)
print('Output MIDI title:', output_midi_title)
print('Output MIDI summary:', 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')
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'>Text-to-Music Transformer</h1>")
gr.Markdown("<h1 style='text-align: center; margin-bottom: 1rem'>Generate music based on a title of your imagination :)</h1>")
gr.Markdown(
"\n\n"
"Generate music based on a title of your imagination :)\n\n"
"Check out [Text-to-Music Transformer](https://github.com/asigalov61/Text-to-Music-Transformer) on GitHub!\n\n"
"[Open In Colab]"
"(https://colab.research.google.com/github/asigalov61/Text-to-Music-Transformer/blob/main/Text_to_Music_Transformer.ipynb)"
" for faster execution and endless generation"
)
gr.Markdown("## Enter any desired song title")
input_title = gr.Textbox(value="Nothing Else Matters", label="Song title")
input_prompt_type = gr.Checkbox(label="Open-ended prompt")
input_num_tokens = gr.Slider(8, 2048, value=512, step=8, label="Number of tokens to generate")
run_btn = gr.Button("generate", variant="primary")
gr.Markdown("## Generation results")
output_midi_title = gr.Textbox(label="Generated 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(Text_to_Music, [input_title, input_num_tokens, input_prompt_type],
[output_midi_title, output_midi_summary, output_midi, output_audio, output_plot])
app.queue().launch() |