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