zziang commited on
Commit
acf1687
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verified ·
1 Parent(s): 8e123db

radio: student reuses teacher frames; parse malformed script JSON

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Files changed (1) hide show
  1. kaggle/radio_demo.py +37 -12
kaggle/radio_demo.py CHANGED
@@ -93,10 +93,8 @@ def write_script() -> tuple[list[dict], str]:
93
  del model
94
  torch.cuda.empty_cache()
95
 
96
- m = re.search(r"\[.*\]", raw, re.S)
97
- rows = json.loads(m.group(0) if m else raw)
98
- rows = [r for r in rows if isinstance(r, dict) and r.get("text")]
99
- # Three usable lines is a valid answer; the previous >=4 gate rejected a
100
  # correct three-line script and silently used the fallback.
101
  if len(rows) >= 3:
102
  return rows[:8], "llm"
@@ -105,6 +103,28 @@ def write_script() -> tuple[list[dict], str]:
105
  return FALLBACK, "fallback"
106
 
107
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
108
  def cast(rows: list[dict]) -> list[dict]:
109
  """Assign a voice to each line and keep the plan explicit in the report."""
110
  out = []
@@ -145,7 +165,7 @@ def main() -> None:
145
  tts = MingTTS(str(MODEL), device="cuda", text_normalization=False)
146
  report = {"script_source": source, "lines": [], "renders": {}}
147
 
148
- def render(tag: str, use_student: bool) -> dict:
149
  import copy
150
 
151
  mm = tts.model
@@ -177,12 +197,15 @@ def main() -> None:
177
  latent, spk = tts.prepare_prompt(wav_path, use_spk_emb=True)
178
  latent = latent.to(device=device, dtype=dtype)
179
  spk = [x.to(device=device, dtype=dtype) for x in spk]
180
- ref = tts.synthesize(task="TTS", text=line["text"], language_id="Chinese",
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- prompt_wav_path=wav_path, prompt_text=v["prompt_text"],
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- use_spk_emb=True, raw_text=True,
183
- max_decode_steps=max(32, min(400, int(len(line["text"]) * 3.5))))
184
- ref = ref.cpu().numpy().reshape(-1)
185
- frames = max(16, int(round(ref.size / 3528)))
 
 
 
186
  y = _ar(mm, sampler, line["text"], task_prompt, latent,
187
  v["prompt_text"], spk, frames)
188
  else:
@@ -198,6 +221,7 @@ def main() -> None:
198
  p = OUT / "lines" / f"{tag}_{line['index']:02d}.wav"
199
  sf.write(str(p), y, SR)
200
  rows.append({**line, "seconds": round(y.size / SR, 2), "wall": round(wall, 1),
 
201
  "rtf": round(wall / max(1e-6, y.size / SR), 2),
202
  "wav": str(p)})
203
  log(f"{tag} {line['index']} {line['style']} {y.size/SR:.2f}s wall {wall:.1f}s")
@@ -216,7 +240,8 @@ def main() -> None:
216
  report["renders"]["teacher"] = teacher
217
  log(f"teacher segment: {teacher['seconds']}s, {len(teacher['rows'])} lines")
218
 
219
- student = render("student", use_student=True)
 
220
  report["renders"]["student"] = student
221
  log(f"student segment: {student['seconds']}s, {len(student['rows'])} lines")
222
 
 
93
  del model
94
  torch.cuda.empty_cache()
95
 
96
+ rows = parse_script(raw)
97
+ # Three usable lines is a valid answer; an earlier >=4 gate rejected a
 
 
98
  # correct three-line script and silently used the fallback.
99
  if len(rows) >= 3:
100
  return rows[:8], "llm"
 
103
  return FALLBACK, "fallback"
104
 
105
 
106
+ def parse_script(raw: str) -> list[dict]:
107
+ """Pull style/text pairs out of the model's answer.
108
+
109
+ A 1.5B instruct model reliably writes the fields but not reliably the
110
+ punctuation: one observed answer dropped a closing brace and the whole
111
+ array stopped being JSON. Scanning for the pairs survives that, while
112
+ `json.loads` cannot.
113
+ """
114
+ pairs = re.findall(r'"style"\s*:\s*"([^"]*)"\s*,\s*"text"\s*:\s*"([^"]*)"', raw)
115
+ if not pairs:
116
+ pairs = [(s, t) for t, s in re.findall(
117
+ r'"text"\s*:\s*"([^"]*)"\s*,\s*"style"\s*:\s*"([^"]*)"', raw)]
118
+ out = [{"style": s or "叙述", "text": t} for s, t in pairs if t.strip()]
119
+ if not out:
120
+ try:
121
+ rows = json.loads(re.search(r"\[.*\]", raw, re.S).group(0))
122
+ out = [r for r in rows if isinstance(r, dict) and r.get("text")]
123
+ except Exception:
124
+ pass
125
+ return out
126
+
127
+
128
  def cast(rows: list[dict]) -> list[dict]:
129
  """Assign a voice to each line and keep the plan explicit in the report."""
130
  out = []
 
165
  tts = MingTTS(str(MODEL), device="cuda", text_normalization=False)
166
  report = {"script_source": source, "lines": [], "renders": {}}
167
 
168
+ def render(tag: str, use_student: bool, frames_by_index: dict | None = None) -> dict:
169
  import copy
170
 
171
  mm = tts.model
 
197
  latent, spk = tts.prepare_prompt(wav_path, use_spk_emb=True)
198
  latent = latent.to(device=device, dtype=dtype)
199
  spk = [x.to(device=device, dtype=dtype) for x in spk]
200
+ # Reuse the teacher's own frame count. Synthesising the
201
+ # teacher again to measure length gives a different take -
202
+ # 25 frames vs 16 on a whisper line - and a wrong budget
203
+ # makes the student drift into a loop or into silence.
204
+ frames = (frames_by_index or {}).get(line["index"])
205
+ if not frames:
206
+ log(f"{tag} line {line['index']} skipped: no teacher frames")
207
+ continue
208
+ torch.manual_seed(SEED + line["index"])
209
  y = _ar(mm, sampler, line["text"], task_prompt, latent,
210
  v["prompt_text"], spk, frames)
211
  else:
 
221
  p = OUT / "lines" / f"{tag}_{line['index']:02d}.wav"
222
  sf.write(str(p), y, SR)
223
  rows.append({**line, "seconds": round(y.size / SR, 2), "wall": round(wall, 1),
224
+ "frames": max(1, int(round(y.size / 3528))),
225
  "rtf": round(wall / max(1e-6, y.size / SR), 2),
226
  "wav": str(p)})
227
  log(f"{tag} {line['index']} {line['style']} {y.size/SR:.2f}s wall {wall:.1f}s")
 
240
  report["renders"]["teacher"] = teacher
241
  log(f"teacher segment: {teacher['seconds']}s, {len(teacher['rows'])} lines")
242
 
243
+ frames = {r["index"]: r["frames"] for r in teacher["rows"]}
244
+ student = render("student", use_student=True, frames_by_index=frames)
245
  report["renders"]["student"] = student
246
  log(f"student segment: {student['seconds']}s, {len(student['rows'])} lines")
247