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7d723ab
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Parent(s):
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Upload app.py
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app.py
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1 |
+
import os.path
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2 |
+
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3 |
+
import time as reqtime
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4 |
+
import datetime
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5 |
+
from pytz import timezone
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6 |
+
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7 |
+
import torch
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8 |
+
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9 |
+
import spaces
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10 |
+
import gradio as gr
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11 |
+
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12 |
+
from x_transformer_1_23_2 import *
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13 |
+
import random
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14 |
+
import tqdm
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15 |
+
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16 |
+
from midi_to_colab_audio import midi_to_colab_audio
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17 |
+
import TMIDIX
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18 |
+
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19 |
+
import matplotlib.pyplot as plt
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20 |
+
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21 |
+
in_space = os.getenv("SYSTEM") == "spaces"
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22 |
+
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23 |
+
# =================================================================================================
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24 |
+
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25 |
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@spaces.GPU
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26 |
+
def Text_to_Music(input_title, input_num_tokens, input_prompt_type):
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27 |
+
print('=' * 70)
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28 |
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print('Req start time: {:%Y-%m-%d %H:%M:%S}'.format(datetime.datetime.now(PDT)))
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29 |
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start_time = reqtime.time()
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30 |
+
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31 |
+
print('Loading model...')
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32 |
+
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33 |
+
SEQ_LEN = 4096 # Models seq len
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34 |
+
PAD_IDX = 2571 # Models pad index
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35 |
+
DEVICE = 'cuda' # 'cuda'
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36 |
+
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37 |
+
# instantiate the model
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38 |
+
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39 |
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model = TransformerWrapper(
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40 |
+
num_tokens = PAD_IDX+1,
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41 |
+
max_seq_len = SEQ_LEN,
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42 |
+
attn_layers = Decoder(dim = 2048, depth = 8, heads = 16, attn_flash = True)
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43 |
+
)
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44 |
+
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45 |
+
model = AutoregressiveWrapper(model, ignore_index = PAD_IDX)
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46 |
+
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47 |
+
model.to(DEVICE)
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48 |
+
print('=' * 70)
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49 |
+
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50 |
+
print('Loading model checkpoint...')
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51 |
+
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52 |
+
model.load_state_dict(
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53 |
+
torch.load('Text_to_Music_Transformer_Medium_Trained_Model_33934_steps_0.6093_loss_0.813_acc.pth',
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54 |
+
map_location=DEVICE))
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55 |
+
print('=' * 70)
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56 |
+
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57 |
+
model.eval()
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58 |
+
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59 |
+
if DEVICE == 'cpu':
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60 |
+
dtype = torch.bfloat16
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61 |
+
else:
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62 |
+
dtype = torch.float16
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63 |
+
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64 |
+
ctx = torch.amp.autocast(device_type=DEVICE, dtype=dtype)
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65 |
+
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66 |
+
print('Done!')
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67 |
+
print('=' * 70)
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68 |
+
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69 |
+
input_num_tokens = max(8, min(2048, input_num_tokens))
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70 |
+
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71 |
+
print('-' * 70)
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72 |
+
print('Input title:', input_title)
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73 |
+
print('Req num toks:', input_num_tokens)
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74 |
+
print('Open-ended prompt:', input_prompt_type)
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75 |
+
print('-' * 70)
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76 |
+
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77 |
+
#===============================================================================
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78 |
+
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79 |
+
print('Setting up model patches and loading helper functions...')
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80 |
+
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81 |
+
# @title Setup and load model channels MIDI patches
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82 |
+
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83 |
+
model_channel_0_piano_family = "Acoustic Grand" # @param ["Acoustic Grand", "Bright Acoustic", "Electric Grand", "Honky-Tonk", "Electric Piano 1", "Electric Piano 2", "Harpsichord", "Clav"]
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84 |
+
model_channel_1_chromatic_percussion_family = "Music Box" # @param ["Celesta", "Glockenspiel", "Music Box", "Vibraphone", "Marimba", "Xylophone", "Tubular Bells", "Dulcimer"]
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85 |
+
model_channel_2_organ_family = "Church Organ" # @param ["Drawbar Organ", "Percussive Organ", "Rock Organ", "Church Organ", "Reed Organ", "Accordion", "Harmonica", "Tango Accordion"]
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86 |
+
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"]
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87 |
+
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"]
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88 |
+
model_channel_5_strings_family = "Violin" # @param ["Violin", "Viola", "Cello", "Contrabass", "Tremolo Strings", "Pizzicato Strings", "Orchestral Harp", "Timpani"]
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89 |
+
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"]
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90 |
+
model_channel_7_brass_family = "Trumpet" # @param ["Trumpet", "Trombone", "Tuba", "Muted Trumpet", "French Horn", "Brass Section", "SynthBrass 1", "SynthBrass 2"]
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91 |
+
model_channel_8_reed_family = "Alto Sax" # @param ["Soprano Sax", "Alto Sax", "Tenor Sax", "Baritone Sax", "Oboe", "English Horn", "Bassoon", "Clarinet"]
|
92 |
+
model_channel_9_pipe_family = "Flute" # @param ["Piccolo", "Flute", "Recorder", "Pan Flute", "Blown Bottle", "Skakuhachi", "Whistle", "Ocarina"]
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93 |
+
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)"]
|
94 |
+
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)"]
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95 |
+
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)"]
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96 |
+
model_channel_13_ethnic_family = "Banjo" # @param ["Sitar", "Banjo", "Shamisen", "Koto", "Kalimba", "Bagpipe", "Fiddle", "Shanai"]
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97 |
+
model_channel_14_percussive_family = "Melodic Tom" # @param ["Tinkle Bell", "Agogo", "Steel Drums", "Woodblock", "Taiko Drum", "Melodic Tom", "Synth Drum", "Reverse Cymbal"]
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98 |
+
model_channel_15_sound_effects_family = "Bird Tweet" # @param ["Guitar Fret Noise", "Breath Noise", "Seashore", "Bird Tweet", "Telephone Ring", "Helicopter", "Applause", "Gunshot"]
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99 |
+
model_channel_16_drums_family = "Drums" # @param ["Drums"]
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100 |
+
|
101 |
+
print('=' * 70)
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102 |
+
print('Loading helper functions...')
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103 |
+
|
104 |
+
def txt2tokens(txt):
|
105 |
+
return [ord(char)+2440 if 0 < ord(char) < 128 else 0+2440 for char in txt.lower()]
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106 |
+
|
107 |
+
def tokens2txt(tokens):
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108 |
+
return [chr(tok-2440) for tok in tokens if 0+2440 < tok < 128+2440 ]
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109 |
+
|
110 |
+
print('=' * 70)
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111 |
+
print('Setting up patches...')
|
112 |
+
print('=' * 70)
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113 |
+
|
114 |
+
instruments = [v[1] for v in TMIDIX.Number2patch.items()]
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115 |
+
|
116 |
+
patches = [instruments.index(model_channel_0_piano_family),
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117 |
+
instruments.index(model_channel_1_chromatic_percussion_family),
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118 |
+
instruments.index(model_channel_2_organ_family),
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119 |
+
instruments.index(model_channel_3_guitar_family),
|
120 |
+
instruments.index(model_channel_4_bass_family),
|
121 |
+
instruments.index(model_channel_5_strings_family),
|
122 |
+
instruments.index(model_channel_6_ensemble_family),
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123 |
+
instruments.index(model_channel_7_brass_family),
|
124 |
+
instruments.index(model_channel_8_reed_family),
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125 |
+
9, # Drums patch
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126 |
+
instruments.index(model_channel_9_pipe_family),
|
127 |
+
instruments.index(model_channel_10_synth_lead_family),
|
128 |
+
instruments.index(model_channel_11_synth_pad_family),
|
129 |
+
instruments.index(model_channel_12_synth_effects_family),
|
130 |
+
instruments.index(model_channel_13_ethnic_family),
|
131 |
+
instruments.index(model_channel_15_sound_effects_family)
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132 |
+
]
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133 |
+
|
134 |
+
print('Done!')
|
135 |
+
print('=' * 70)
|
136 |
+
|
137 |
+
print('Generating...')
|
138 |
+
|
139 |
+
#@title Standard Text-to-Music Generator
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140 |
+
|
141 |
+
#@markdown Prompt settings
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142 |
+
|
143 |
+
song_title_prompt = input_title
|
144 |
+
open_ended_prompt = input_prompt_type
|
145 |
+
|
146 |
+
#@markdown Generation settings
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147 |
+
|
148 |
+
number_of_tokens_to_generate = input_num_tokens
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149 |
+
number_of_batches_to_generate = 1 #@param {type:"slider", min:1, max:16, step:1}
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150 |
+
temperature = 0.9 # @param {type:"slider", min:0.1, max:1, step:0.05}
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151 |
+
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152 |
+
print('=' * 70)
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153 |
+
print('Text-to-Music Model Generator')
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154 |
+
print('=' * 70)
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155 |
+
|
156 |
+
if song_title_prompt == '':
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157 |
+
outy = [2569]
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158 |
+
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159 |
+
else:
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160 |
+
if open_ended_prompt:
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161 |
+
outy = [2569] + txt2tokens(song_title_prompt)
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162 |
+
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163 |
+
else:
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164 |
+
outy = [2569] + txt2tokens(song_title_prompt) + [2570]
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165 |
+
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166 |
+
print('Selected prompt sequence:')
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167 |
+
print(outy[:12])
|
168 |
+
print('=' * 70)
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169 |
+
|
170 |
+
torch.cuda.empty_cache()
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171 |
+
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172 |
+
inp = [outy] * number_of_batches_to_generate
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173 |
+
|
174 |
+
inp = torch.LongTensor(inp).cuda()
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175 |
+
|
176 |
+
with ctx:
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177 |
+
out = model.generate(inp,
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178 |
+
number_of_tokens_to_generate,
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179 |
+
temperature=temperature,
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180 |
+
return_prime=True,
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181 |
+
verbose=False)
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182 |
+
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183 |
+
out0 = out.tolist()
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184 |
+
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185 |
+
print('=' * 70)
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186 |
+
print('Done!')
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187 |
+
print('=' * 70)
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188 |
+
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189 |
+
#===============================================================================
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190 |
+
print('Rendering results...')
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191 |
+
print('=' * 70)
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192 |
+
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193 |
+
out1 = out0[0]
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194 |
+
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195 |
+
print('Sample INTs', out1[:12])
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196 |
+
print('=' * 70)
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197 |
+
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198 |
+
generated_song_title = ''.join(tokens2txt(out1)).title()
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199 |
+
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200 |
+
print('Generated song title:', generated_song_title)
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201 |
+
print('=' * 70)
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202 |
+
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203 |
+
if len(out1) != 0:
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204 |
+
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205 |
+
song = out1
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206 |
+
song_f = []
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207 |
+
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208 |
+
time = 0
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209 |
+
dur = 0
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210 |
+
vel = 90
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211 |
+
pitch = 0
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212 |
+
channel = 0
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213 |
+
chan = 0
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214 |
+
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215 |
+
for ss in song:
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216 |
+
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217 |
+
if 0 <= ss < 128:
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218 |
+
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219 |
+
time += ss * 32
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220 |
+
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221 |
+
if 128 <= ss < 256:
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222 |
+
|
223 |
+
dur = (ss-128) * 32
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224 |
+
|
225 |
+
if 256 <= ss < 2432:
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226 |
+
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227 |
+
chan = (ss-256) // 128
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228 |
+
|
229 |
+
if chan < 9:
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230 |
+
channel = chan
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231 |
+
elif 9 < chan < 15:
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232 |
+
channel = chan+1
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233 |
+
elif chan == 15:
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234 |
+
channel = 15
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235 |
+
elif chan == 16:
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236 |
+
channel = 9
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237 |
+
|
238 |
+
pitch = (ss-256) % 128
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239 |
+
|
240 |
+
if 2432 <= ss < 2440:
|
241 |
+
|
242 |
+
vel = (((ss-2432)+1) * 15)-1
|
243 |
+
|
244 |
+
song_f.append(['note', time, dur, channel, pitch, vel, chan*8 ])
|
245 |
+
|
246 |
+
fn1 = "Text-to-Music-Transformer-Composition"
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247 |
+
|
248 |
+
detailed_stats = TMIDIX.Tegridy_ms_SONG_to_MIDI_Converter(song_f,
|
249 |
+
output_signature = 'Text-to-Music Transformer',
|
250 |
+
output_file_name = fn1,
|
251 |
+
track_name='Project Los Angeles',
|
252 |
+
list_of_MIDI_patches=patches
|
253 |
+
)
|
254 |
+
|
255 |
+
new_fn = fn1+'.mid'
|
256 |
+
|
257 |
+
|
258 |
+
audio = midi_to_colab_audio(new_fn,
|
259 |
+
soundfont_path=soundfont,
|
260 |
+
sample_rate=16000,
|
261 |
+
volume_scale=10,
|
262 |
+
output_for_gradio=True
|
263 |
+
)
|
264 |
+
|
265 |
+
print('Done!')
|
266 |
+
print('=' * 70)
|
267 |
+
|
268 |
+
#========================================================
|
269 |
+
|
270 |
+
output_midi_title = generated_song_title
|
271 |
+
output_midi_summary = str(song_f[:3])
|
272 |
+
output_midi = str(new_fn)
|
273 |
+
output_audio = (16000, audio)
|
274 |
+
|
275 |
+
output_plot = TMIDIX.plot_ms_SONG(song_f, plot_title=output_midi, return_plt=True)
|
276 |
+
|
277 |
+
print('Output MIDI file name:', output_midi)
|
278 |
+
print('Output MIDI title:', output_midi_title)
|
279 |
+
print('Output MIDI summary:', output_midi_summary)
|
280 |
+
print('=' * 70)
|
281 |
+
|
282 |
+
|
283 |
+
#========================================================
|
284 |
+
|
285 |
+
print('-' * 70)
|
286 |
+
print('Req end time: {:%Y-%m-%d %H:%M:%S}'.format(datetime.datetime.now(PDT)))
|
287 |
+
print('-' * 70)
|
288 |
+
print('Req execution time:', (reqtime.time() - start_time), 'sec')
|
289 |
+
|
290 |
+
return output_midi_title, output_midi_summary, output_midi, output_audio, output_plot
|
291 |
+
|
292 |
+
# =================================================================================================
|
293 |
+
|
294 |
+
if __name__ == "__main__":
|
295 |
+
|
296 |
+
PDT = timezone('US/Pacific')
|
297 |
+
|
298 |
+
print('=' * 70)
|
299 |
+
print('App start time: {:%Y-%m-%d %H:%M:%S}'.format(datetime.datetime.now(PDT)))
|
300 |
+
print('=' * 70)
|
301 |
+
|
302 |
+
soundfont = "SGM-v2.01-YamahaGrand-Guit-Bass-v2.7.sf2"
|
303 |
+
|
304 |
+
app = gr.Blocks()
|
305 |
+
with app:
|
306 |
+
gr.Markdown("<h1 style='text-align: center; margin-bottom: 1rem'>Text-to-Music Transformer</h1>")
|
307 |
+
gr.Markdown("<h1 style='text-align: center; margin-bottom: 1rem'>Generate music based on a title of your imagination :)</h1>")
|
308 |
+
gr.Markdown(
|
309 |
+
"![Visitors](https://api.visitorbadge.io/api/visitors?path=asigalov61.Text-to-Music-Transformer&style=flat)\n\n"
|
310 |
+
"Generate music based on a title of your imagination :)\n\n"
|
311 |
+
"Check out [Text-to-Music Transformer](https://github.com/asigalov61/Text-to-Music-Transformer) on GitHub!\n\n"
|
312 |
+
"[Open In Colab]"
|
313 |
+
"(https://colab.research.google.com/github/asigalov61/Text-to-Music-Transformer/blob/main/Text_to_Music_Transformer.ipynb)"
|
314 |
+
" for faster execution and endless generation"
|
315 |
+
)
|
316 |
+
gr.Markdown("## Enter any desired song title")
|
317 |
+
|
318 |
+
input_title = gr.Textbox(value="Nothing Else Matters", label="Song title")
|
319 |
+
input_prompt_type = gr.Checkbox(label="Open-ended prompt")
|
320 |
+
|
321 |
+
input_num_tokens = gr.Slider(8, 2048, value=512, step=8, label="Number of tokens to generate")
|
322 |
+
|
323 |
+
run_btn = gr.Button("generate", variant="primary")
|
324 |
+
|
325 |
+
gr.Markdown("## Generation results")
|
326 |
+
|
327 |
+
output_midi_title = gr.Textbox(label="Generated MIDI title")
|
328 |
+
output_midi_summary = gr.Textbox(label="Output MIDI summary")
|
329 |
+
output_audio = gr.Audio(label="Output MIDI audio", format="wav", elem_id="midi_audio")
|
330 |
+
output_plot = gr.Plot(label="Output MIDI score plot")
|
331 |
+
output_midi = gr.File(label="Output MIDI file", file_types=[".mid"])
|
332 |
+
|
333 |
+
|
334 |
+
run_event = run_btn.click(Text_to_Music, [input_title, input_num_tokens, input_prompt_type],
|
335 |
+
[output_midi_title, output_midi_summary, output_midi, output_audio, output_plot])
|
336 |
+
|
337 |
+
app.queue().launch()
|