Create app.py

app.py

@@ -0,0 +1,264 @@
+import argparse
+import glob
+import os.path
+
+import gradio as gr
+
+import tqdm
+import json
+
+import MIDI
+from midi_synthesizer import synthesis
+
+in_space = os.getenv("SYSTEM") == "spaces"
+
+
+def generate(model, prompt=None, max_len=512, temp=1.0, top_p=0.98, top_k=20,
+             disable_patch_change=False, disable_control_change=False, disable_channels=None):
+    if disable_channels is not None:
+        disable_channels = [tokenizer.parameter_ids["channel"][c] for c in disable_channels]
+    else:
+        disable_channels = []
+    max_token_seq = tokenizer.max_token_seq
+    if prompt is None:
+        input_tensor = np.full((1, max_token_seq), tokenizer.pad_id, dtype=np.int64)
+        input_tensor[0, 0] = tokenizer.bos_id  # bos
+    else:
+        prompt = prompt[:, :max_token_seq]
+        if prompt.shape[-1] < max_token_seq:
+            prompt = np.pad(prompt, ((0, 0), (0, max_token_seq - prompt.shape[-1])),
+                            mode="constant", constant_values=tokenizer.pad_id)
+        input_tensor = prompt
+    input_tensor = input_tensor[None, :, :]
+    cur_len = input_tensor.shape[1]
+    bar = tqdm.tqdm(desc="generating", total=max_len - cur_len, disable=in_space)
+    with bar:
+        while cur_len < max_len:
+            end = False
+            hidden = model[0].run(None, {'x': input_tensor})[0][:, -1]
+            next_token_seq = np.empty((1, 0), dtype=np.int64)
+            event_name = ""
+            for i in range(max_token_seq):
+                mask = np.zeros(tokenizer.vocab_size, dtype=np.int64)
+                if i == 0:
+                    mask_ids = list(tokenizer.event_ids.values()) + [tokenizer.eos_id]
+                    if disable_patch_change:
+                        mask_ids.remove(tokenizer.event_ids["patch_change"])
+                    if disable_control_change:
+                        mask_ids.remove(tokenizer.event_ids["control_change"])
+                    mask[mask_ids] = 1
+                else:
+                    param_name = tokenizer.events[event_name][i - 1]
+                    mask_ids = tokenizer.parameter_ids[param_name]
+                    if param_name == "channel":
+                        mask_ids = [i for i in mask_ids if i not in disable_channels]
+                    mask[mask_ids] = 1
+                logits = model[1].run(None, {'x': next_token_seq, "hidden": hidden})[0][:, -1:]
+                scores = softmax(logits / temp, -1) * mask
+                sample = sample_top_p_k(scores, top_p, top_k)
+                if i == 0:
+                    next_token_seq = sample
+                    eid = sample.item()
+                    if eid == tokenizer.eos_id:
+                        end = True
+                        break
+                    event_name = tokenizer.id_events[eid]
+                else:
+                    next_token_seq = np.concatenate([next_token_seq, sample], axis=1)
+                    if len(tokenizer.events[event_name]) == i:
+                        break
+            if next_token_seq.shape[1] < max_token_seq:
+                next_token_seq = np.pad(next_token_seq, ((0, 0), (0, max_token_seq - next_token_seq.shape[-1])),
+                                        mode="constant", constant_values=tokenizer.pad_id)
+            next_token_seq = next_token_seq[None, :, :]
+            input_tensor = np.concatenate([input_tensor, next_token_seq], axis=1)
+            cur_len += 1
+            bar.update(1)
+            yield next_token_seq.reshape(-1)
+            if end:
+                break
+
+
+def create_msg(name, data):
+    return {"name": name, "data": data}
+
+
+def run(model_name, tab, instruments, drum_kit, mid, midi_events, gen_events, temp, top_p, top_k, allow_cc):
+    mid_seq = []
+    gen_events = int(gen_events)
+    max_len = gen_events
+
+    disable_patch_change = False
+    disable_channels = None
+    if tab == 0:
+        i = 0
+        mid = [[tokenizer.bos_id] + [tokenizer.pad_id] * (tokenizer.max_token_seq - 1)]
+        patches = {}
+        for instr in instruments:
+            patches[i] = patch2number[instr]
+            i = (i + 1) if i != 8 else 10
+        if drum_kit != "None":
+            patches[9] = drum_kits2number[drum_kit]
+        for i, (c, p) in enumerate(patches.items()):
+            mid.append(tokenizer.event2tokens(["patch_change", 0, 0, i, c, p]))
+        mid_seq = mid
+        mid = np.asarray(mid, dtype=np.int64)
+        if len(instruments) > 0:
+            disable_patch_change = True
+            disable_channels = [i for i in range(16) if i not in patches]
+    elif mid is not None:
+        mid = tokenizer.tokenize(MIDI.midi2score(mid))
+        mid = np.asarray(mid, dtype=np.int64)
+        mid = mid[:int(midi_events)]
+        max_len += len(mid)
+        for token_seq in mid:
+            mid_seq.append(token_seq.tolist())
+    init_msgs = [create_msg("visualizer_clear", None)]
+    for tokens in mid_seq:
+        init_msgs.append(create_msg("visualizer_append", tokenizer.tokens2event(tokens)))
+    yield mid_seq, None, None, init_msgs
+    model = models[model_name]
+    generator = generate(model, mid, max_len=max_len, temp=temp, top_p=top_p, top_k=top_k,
+                         disable_patch_change=disable_patch_change, disable_control_change=not allow_cc,
+                         disable_channels=disable_channels)
+    for i, token_seq in enumerate(generator):
+        token_seq = token_seq.tolist()
+        mid_seq.append(token_seq)
+        event = tokenizer.tokens2event(token_seq)
+        yield mid_seq, None, None, [create_msg("visualizer_append", event), create_msg("progress", [i + 1, gen_events])]
+    mid = tokenizer.detokenize(mid_seq)
+    with open(f"output.mid", 'wb') as f:
+        f.write(MIDI.score2midi(mid))
+    audio = synthesis(MIDI.score2opus(mid), soundfont_path)
+    yield mid_seq, "output.mid", (44100, audio), [create_msg("visualizer_end", None)]
+
+
+def cancel_run(mid_seq):
+    if mid_seq is None:
+        return None, None
+    mid = tokenizer.detokenize(mid_seq)
+    with open(f"output.mid", 'wb') as f:
+        f.write(MIDI.score2midi(mid))
+    audio = synthesis(MIDI.score2opus(mid), soundfont_path)
+    return "output.mid", (44100, audio), [create_msg("visualizer_end", None)]
+
+
+def load_javascript(dir="javascript"):
+    scripts_list = glob.glob(f"{dir}/*.js")
+    javascript = ""
+    for path in scripts_list:
+        with open(path, "r", encoding="utf8") as jsfile:
+            javascript += f"\n<!-- {path} --><script>{jsfile.read()}</script>"
+    template_response_ori = gr.routes.templates.TemplateResponse
+
+    def template_response(*args, **kwargs):
+        res = template_response_ori(*args, **kwargs)
+        res.body = res.body.replace(
+            b'</head>', f'{javascript}</head>'.encode("utf8"))
+        res.init_headers()
+        return res
+
+    gr.routes.templates.TemplateResponse = template_response
+
+
+class JSMsgReceiver(gr.HTML):
+
+    def __init__(self, **kwargs):
+        super().__init__(elem_id="msg_receiver", visible=False, **kwargs)
+
+    def postprocess(self, y):
+        if y:
+            y = f"<p>{json.dumps(y)}</p>"
+        return super().postprocess(y)
+
+    def get_block_name(self) -> str:
+        return "html"
+
+
+number2drum_kits = {-1: "None", 0: "Standard", 8: "Room", 16: "Power", 24: "Electric", 25: "TR-808", 32: "Jazz",
+                    40: "Blush", 48: "Orchestra"}
+patch2number = {v: k for k, v in MIDI.Number2patch.items()}
+drum_kits2number = {v: k for k, v in number2drum_kits.items()}
+
+if __name__ == "__main__":
+    parser = argparse.ArgumentParser()
+    parser.add_argument("--share", action="store_true", default=False, help="share gradio app")
+    parser.add_argument("--port", type=int, default=7860, help="gradio server port")
+    parser.add_argument("--max-gen", type=int, default=1024, help="max")
+    opt = parser.parse_args()
+    soundfont_path = hf_hub_download(repo_id="skytnt/midi-model", filename="soundfont.sf2")
+    models_info = {"generic pretrain model": ["skytnt/midi-model", ""],
+                   "j-pop finetune model": ["skytnt/midi-model-ft", "jpop/"],
+                   "touhou finetune model": ["skytnt/midi-model-ft", "touhou/"]}
+    models = {}
+    tokenizer = MIDITokenizer()
+    providers = ['CUDAExecutionProvider', 'CPUExecutionProvider']
+    for name, (repo_id, path) in models_info.items():
+        model_base_path = hf_hub_download(repo_id=repo_id, filename=f"{path}onnx/model_base.onnx")
+        model_token_path = hf_hub_download(repo_id=repo_id, filename=f"{path}onnx/model_token.onnx")
+        model_base = rt.InferenceSession(model_base_path, providers=providers)
+        model_token = rt.InferenceSession(model_token_path, providers=providers)
+        models[name] = [model_base, model_token]
+
+    load_javascript()
+    app = gr.Blocks()
+    with app:
+        gr.Markdown("<h1 style='text-align: center; margin-bottom: 1rem'>Midi Composer</h1>")
+        gr.Markdown("![Visitors](https://api.visitorbadge.io/api/visitors?path=skytnt.midi-composer&style=flat)\n\n"
+                    "Midi event transformer for music generation\n\n"
+                    "Demo for [SkyTNT/midi-model](https://github.com/SkyTNT/midi-model)\n\n"
+                    "[Open In Colab]"
+                    "(https://colab.research.google.com/github/SkyTNT/midi-model/blob/main/demo.ipynb)"
+                    " for faster running and longer generation"
+                    )
+        js_msg = JSMsgReceiver()
+        input_model = gr.Dropdown(label="select model", choices=list(models.keys()),
+                                  type="value", value=list(models.keys())[0])
+        tab_select = gr.Variable(value=0)
+        with gr.Tabs():
+            with gr.TabItem("instrument prompt") as tab1:
+                input_instruments = gr.Dropdown(label="instruments (auto if empty)", choices=list(patch2number.keys()),
+                                                multiselect=True, max_choices=15, type="value")
+                input_drum_kit = gr.Dropdown(label="drum kit", choices=list(drum_kits2number.keys()), type="value",
+                                             value="None")
+                example1 = gr.Examples([
+                    [[], "None"],
+                    [["Acoustic Grand"], "None"],
+                    [["Acoustic Grand", "Violin", "Viola", "Cello", "Contrabass"], "Orchestra"],
+                    [["Flute", "Cello", "Bassoon", "Tuba"], "None"],
+                    [["Violin", "Viola", "Cello", "Contrabass", "Trumpet", "French Horn", "Brass Section",
+                      "Flute", "Piccolo", "Tuba", "Trombone", "Timpani"], "Orchestra"],
+                    [["Acoustic Guitar(nylon)", "Acoustic Guitar(steel)", "Electric Guitar(jazz)",
+                      "Electric Guitar(clean)", "Electric Guitar(muted)", "Overdriven Guitar", "Distortion Guitar",
+                      "Electric Bass(finger)"], "Standard"]
+                ], [input_instruments, input_drum_kit])
+            with gr.TabItem("midi prompt") as tab2:
+                input_midi = gr.File(label="input midi", file_types=[".midi", ".mid"], type="binary")
+                input_midi_events = gr.Slider(label="use first n midi events as prompt", minimum=1, maximum=512,
+                                              step=1,
+                                              value=128)
+                example2 = gr.Examples([[file, 128] for file in glob.glob("example/*.mid")],
+                                       [input_midi, input_midi_events])
+
+        tab1.select(lambda: 0, None, tab_select, queue=False)
+        tab2.select(lambda: 1, None, tab_select, queue=False)
+        input_gen_events = gr.Slider(label="generate n midi events", minimum=1, maximum=opt.max_gen,
+                                     step=1, value=opt.max_gen // 2)
+        with gr.Accordion("options", open=False):
+            input_temp = gr.Slider(label="temperature", minimum=0.1, maximum=1.2, step=0.01, value=1)
+            input_top_p = gr.Slider(label="top p", minimum=0.1, maximum=1, step=0.01, value=0.98)
+            input_top_k = gr.Slider(label="top k", minimum=1, maximum=20, step=1, value=12)
+            input_allow_cc = gr.Checkbox(label="allow midi cc event", value=True)
+            example3 = gr.Examples([[1, 0.98, 12], [1.2, 0.95, 8]], [input_temp, input_top_p, input_top_k])
+        run_btn = gr.Button("generate", variant="primary")
+        stop_btn = gr.Button("stop and output")
+        output_midi_seq = gr.Variable()
+        output_midi_visualizer = gr.HTML(elem_id="midi_visualizer_container")
+        output_audio = gr.Audio(label="output audio", format="mp3", elem_id="midi_audio")
+        output_midi = gr.File(label="output midi", file_types=[".mid"])
+        run_event = run_btn.click(run, [input_model, tab_select, input_instruments, input_drum_kit, input_midi,
+                                        input_midi_events, input_gen_events, input_temp, input_top_p, input_top_k,
+                                        input_allow_cc],
+                                  [output_midi_seq, output_midi, output_audio, js_msg])
+        stop_btn.click(cancel_run, output_midi_seq, [output_midi, output_audio, js_msg], cancels=run_event, queue=False)
+    app.queue(2).launch(server_port=opt.port, share=opt.share, inbrowser=True)