app.py

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 GenerateMusic(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'>Descriptive Music Transformer</h1>")
        gr.Markdown("<h1 style='text-align: center; margin-bottom: 1rem'>A music transformer that describes music it generates</h1>")
        gr.Markdown(
            "![Visitors](https://api.visitorbadge.io/api/visitors?path=asigalov61.Descriptive-Music-Transformer&style=flat)\n\n"
            "Generate music based on a title of your imagination :)\n\n"
            "Check out [Annotated MIDI Dataset](https://huggingface.co/datasets/asigalov61/Annotated-MIDI-Dataset) on Hugging Face!\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(GenerateMusic, [input_title, input_num_tokens, input_prompt_type],
                                  [output_midi_title, output_midi_summary, output_midi, output_audio, output_plot])

        app.queue().launch()