Delete run_inference.py

run_inference.py

@@ -1,186 +0,0 @@
-import gradio as gr
-import torch
-import random
-from unidecode import unidecode
-from transformers import GPT2LMHeadModel
-from samplings import top_p_sampling, temperature_sampling
-
-device = torch.device("cpu")
-
-description = """
-<div>
-<a style="display:inline-block" href='https://github.com/suno-ai/bark'><img src='https://img.shields.io/github/stars/suno-ai/bark?style=social' /></a>
-<a style='display:inline-block' href='https://discord.gg/J2B2vsjKuE'><img src='https://dcbadge.vercel.app/api/server/J2B2vsjKuE?compact=true&style=flat' /></a>
-<a style="display:inline-block; margin-left: 1em" href="https://huggingface.co/spaces/suno/bark?duplicate=true"><img src="https://img.shields.io/badge/-Duplicate%20Space%20to%20skip%20the%20queue-blue?labelColor=white&style=flat&logo=data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAABAAAAAQCAYAAAAf8/9hAAAAAXNSR0IArs4c6QAAAP5JREFUOE+lk7FqAkEURY+ltunEgFXS2sZGIbXfEPdLlnxJyDdYB62sbbUKpLbVNhyYFzbrrA74YJlh9r079973psed0cvUD4A+4HoCjsA85X0Dfn/RBLBgBDxnQPfAEJgBY+A9gALA4tcbamSzS4xq4FOQAJgCDwV2CPKV8tZAJcAjMMkUe1vX+U+SMhfAJEHasQIWmXNN3abzDwHUrgcRGmYcgKe0bxrblHEB4E/pndMazNpSZGcsZdBlYJcEL9Afo75molJyM2FxmPgmgPqlWNLGfwZGG6UiyEvLzHYDmoPkDDiNm9JR9uboiONcBXrpY1qmgs21x1QwyZcpvxt9NS09PlsPAAAAAElFTkSuQmCC&logoWidth=14" alt="Duplicate Space"></a>
-</div>
-Bark is a universal text-to-audio model created by [Suno](www.suno.ai), with code publicly available [here](https://github.com/suno-ai/bark). \
-Bark can generate highly realistic, multilingual speech as well as other audio - including music, background noise and simple sound effects. \
-This demo should be used for research purposes only. Commercial use is strictly prohibited. \
-The model output is not censored and the authors do not endorse the opinions in the generated content. \
-Use at your own risk.
-"""
-
-article = """
-## 🌎 Foreign Language
-Bark supports various languages out-of-the-box and automatically determines language from input text. \
-When prompted with code-switched text, Bark will even attempt to employ the native accent for the respective languages in the same voice.
-Try the prompt:
-```
-Buenos días Miguel. Tu colega piensa que tu alemán es extremadamente malo. But I suppose your english isn't terrible.
-```
-## 🤭 Non-Speech Sounds
-Below is a list of some known non-speech sounds, but we are finding more every day. \
-Please let us know if you find patterns that work particularly well on Discord!
-* [laughter]
-* [laughs]
-* [sighs]
-* [music]
-* [gasps]
-* [clears throat]
-* — or ... for hesitations
-* ♪ for song lyrics
-* capitalization for emphasis of a word
-* MAN/WOMAN: for bias towards speaker
-Try the prompt:
-```
-" [clears throat] Hello, my name is Suno. And, uh — and I like pizza. [laughs] But I also have other interests such as... ♪ singing ♪."
-```
-## 🎶 Music
-Bark can generate all types of audio, and, in principle, doesn't see a difference between speech and music. \
-Sometimes Bark chooses to generate text as music, but you can help it out by adding music notes around your lyrics.
-Try the prompt:
-```
-♪ In the jungle, the mighty jungle, the lion barks tonight ♪
-```
-## 🧬 Voice Cloning
-Bark has the capability to fully clone voices - including tone, pitch, emotion and prosody. \
-The model also attempts to preserve music, ambient noise, etc. from input audio. \
-However, to mitigate misuse of this technology, we limit the audio history prompts to a limited set of Suno-provided, fully synthetic options to choose from.
-## 👥 Speaker Prompts
-You can provide certain speaker prompts such as NARRATOR, MAN, WOMAN, etc. \
-Please note that these are not always respected, especially if a conflicting audio history prompt is given.
-Try the prompt:
-```
-WOMAN: I would like an oatmilk latte please.
-MAN: Wow, that's expensive!
-```
-## Details
-Bark model by [Suno](https://suno.ai/), including official [code](https://github.com/suno-ai/bark) and model weights. \
-Gradio demo supported by 🤗 Hugging Face. Bark is licensed under a non-commercial license: CC-BY 4.0 NC, see details on [GitHub](https://github.com/suno-ai/bark).
-"""
-
-# examples = [
-#     "Jazz standard in Minor key with a swing feel.",
-#     "Jazz standard in Major key with a fast tempo.",
-#     "Jazz standard in Blues form with a soulfoul melody.",
-#     "a painting of a starry night with the moon in the sky",
-#     "a green field with a blue sky and clouds",
-#     "a beach with a castle on top of it"
-# ]
-
-class ABCTokenizer():
-    def __init__(self):
-        self.pad_token_id = 0
-        self.bos_token_id = 2
-        self.eos_token_id = 3
-        self.merged_tokens = []
-        
-        for i in range(8):
-            self.merged_tokens.append('[SECS_'+str(i+1)+']')
-        for i in range(32):
-            self.merged_tokens.append('[BARS_'+str(i+1)+']')
-        for i in range(11):
-            self.merged_tokens.append('[SIM_'+str(i)+']')
-
-    def __len__(self):
-        return 128+len(self.merged_tokens)
-    
-    def encode(self, text):
-        encodings = {}
-        encodings['input_ids'] = torch.tensor(self.txt2ids(text, self.merged_tokens))
-        encodings['attention_mask'] = torch.tensor([1]*len(encodings['input_ids']))
-        return encodings
-
-    def decode(self, ids, skip_special_tokens=False):
-        txt = ""
-        for i in ids:
-            if i>=128:
-                if not skip_special_tokens:
-                    txt += self.merged_tokens[i-128]
-            elif i!=self.bos_token_id and i!=self.eos_token_id:
-                txt += chr(i)
-        return txt
-
-    def txt2ids(self, text, merged_tokens):
-        ids = ["\""+str(ord(c))+"\"" for c in text]
-        txt_ids = ' '.join(ids)
-        for t_idx, token in enumerate(merged_tokens):
-            token_ids = ["\""+str(ord(c))+"\"" for c in token]
-            token_txt_ids = ' '.join(token_ids)
-            txt_ids = txt_ids.replace(token_txt_ids, "\""+str(t_idx+128)+"\"")
-        
-        txt_ids = txt_ids.split(' ')
-        txt_ids = [int(i[1:-1]) for i in txt_ids]
-        return [self.bos_token_id]+txt_ids+[self.eos_token_id]
-
-def generate_abc(control_codes, prefix, num_tunes, max_length, top_p, temperature, seed):
-
-    prefix = unidecode(control_codes + prefix)
-    tokenizer = ABCTokenizer()
-    model = GPT2LMHeadModel.from_pretrained('sander-wood/tunesformer').to(device)
-
-    if prefix:
-        ids = tokenizer.encode(prefix)['input_ids'][:-1]
-    else:
-        ids = torch.tensor([tokenizer.bos_token_id])
-
-    random.seed(seed)
-    tunes = ""
-
-    for c_idx in range(num_tunes):
-        print("\nX:"+str(c_idx+1)+"\n", end="")
-        print(tokenizer.decode(ids[1:], skip_special_tokens=True), end="")
-        input_ids = ids.unsqueeze(0)
-        for t_idx in range(max_length):
-            if seed!=None:
-                n_seed = random.randint(0, 1000000)
-                random.seed(n_seed)
-            else:
-                n_seed = None
-
-            outputs = model(input_ids=input_ids.to(device))
-            probs = outputs.logits[0][-1]
-            probs = torch.nn.Softmax(dim=-1)(probs).cpu().detach().numpy()
-            sampled_id = temperature_sampling(probs=top_p_sampling(probs, 
-                                                                top_p=top_p, 
-                                                                seed=n_seed,
-                                                                return_probs=True),
-                                            seed=n_seed,
-                                            temperature=temperature)
-            input_ids = torch.cat((input_ids, torch.tensor([[sampled_id]])), 1)
-            if sampled_id!=tokenizer.eos_token_id:
-                print(tokenizer.decode([sampled_id], skip_special_tokens=True), end="")
-                continue
-            else:
-                tune = "X:"+str(c_idx+1)+"\n"+tokenizer.decode(input_ids.squeeze(), skip_special_tokens=True)
-                tunes += tune+"\n\n"
-                print("\n")
-                break
-    
-    return tunes
-
-input_control_codes = gr.inputs.Textbox(lines=5, label="Control Codes", default="[SECS_2][BARS_9][SIM_3][BARS_9]")
-input_prefix = gr.inputs.Textbox(lines=5, label="Prefix", default="L:1/8\nQ:1/4=114\nM:3/4\nK:D\nde | \"D\"")
-input_num_tunes = gr.inputs.Slider(minimum=1, maximum=10, step=1, default=3, label="Number of Tunes")
-input_max_length = gr.inputs.Slider(minimum=10, maximum=1000, step=10, default=500, label="Max Length")
-input_top_p = gr.inputs.Slider(minimum=0.0, maximum=1.0, step=0.05, default=0.9, label="Top P")
-input_temperature = gr.inputs.Slider(minimum=0.0, maximum=1.0, step=0.05, default=0.9, label="Temperature")
-input_seed = gr.inputs.Textbox(lines=1, label="Seed", default="None")
-output_abc = gr.outputs.Textbox(label="Generated Tunes")
-
-gr.Interface(generate_abc,
-                [input_control_codes, input_prefix, input_num_tunes, input_max_length, input_top_p, input_temperature, input_seed],
-                output_abc,
-            title="TunesFormer: Forming Tunes with Control Codes",
-            description=description,
-            article=article).launch()