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b21cfae 0efd0f1 b21cfae 0efd0f1 b21cfae 0efd0f1 b21cfae 0efd0f1 b21cfae 0efd0f1 b21cfae 0efd0f1 b21cfae | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 117 118 119 120 121 122 123 124 125 126 127 128 129 130 131 132 133 134 135 136 137 138 139 140 141 142 143 144 145 146 147 148 149 150 151 152 153 154 155 156 157 158 159 160 161 162 163 164 165 166 167 168 169 170 171 172 173 174 175 176 177 178 179 180 181 182 183 184 185 186 187 188 189 190 191 192 193 194 195 196 197 198 199 200 201 202 203 204 205 206 207 208 209 210 211 212 213 214 215 216 217 218 219 220 221 222 223 224 225 226 | """Observe existing L15 results without changing TYGER inputs or decisions.
The GPU service remains the sole encoder caller. No second encoder, no extra
encoder pass, and no on-disk microphone features. Pilot requests reserve the
same session slot as the browser and are rejected while it is in use.
"""
import io
import asyncio
import numpy as np
from aiohttp import web
class ResearchLocked(web.HTTPClientError):
status_code=423
async def reserve_research(ears):
"""Allow the native GPU queue a few ms to finish releasing a closed slot."""
if ears is None:raise web.HTTPServiceUnavailable()
for _ in range(10):
if getattr(ears,'browser_waiting',0):raise ResearchLocked(text='Browser session has priority')
session=ears.open_session(ears.defaults)
if session is not None:return session
await asyncio.sleep(.005)
raise ResearchLocked(text='Live session or another research batch has priority')
def attach_feature_tap(ears):
engine=ears.service.engine
original_encode=engine.asr.encode
original_process=engine.process
capture={'states':None,'early':None,'owner':None}
def encode(wavs):
import threading
hooks=[];buffers={k:[] for k in (4,8,12)};groups={}
live=capture['owner']==threading.get_ident()
if live:
# Match NemotronAsr.encode's grouped batches, including its silence
# cache. Do not assume that the agent channel was actually encoded.
asr=engine.asr;owner=threading.get_ident()
for i,w in enumerate(wavs):
if len(w) in asr._zero_enc and not w.any():continue
groups.setdefault(len(w),[]).append(i)
def tap(layer):
def hook(module,args,out):
if threading.get_ident()==owner:
x=out[0] if isinstance(out,tuple) else out
buffers[layer].append(x[:,-4:].detach().clone())
return hook
for k in buffers:hooks.append(asr.enc.layers[k-1].register_forward_hook(tap(k)))
try:result=original_encode(wavs)
finally:
for hook in hooks:hook.remove()
early=[None]*len(wavs)
if live:
import torch
for g,indices in enumerate(groups.values()):
if any(g>=len(buffers[k]) or len(buffers[k][g])!=len(indices) for k in buffers):
raise RuntimeError('Live intermediate-layer grouping mismatch')
batch=torch.stack([buffers[k][g] for k in (4,8,12)],dim=1).float().cpu().numpy()
for j,index in enumerate(indices):early[index]=batch[j]
if live:
capture['states']=result
capture['early']=early
return result
def process(items):
import threading
capture['owner']=threading.get_ident()
try:result=original_process(items)
finally:capture['owner']=None
states=capture.pop('states',None)
early=capture.pop('early',None)
if states is not None:
from app.plugins.ears.tyger.rules import frame_energy
for i,(session,user,agent,mode) in enumerate(items):
h=states[2*i][-4:].detach().cpu().numpy().astype(np.float32)
energy=frame_energy(user)[-len(h):]
context=states[2*i][-38:].detach().cpu().numpy().astype(np.float32)
context_db=frame_energy(session.win_u)[-len(context):]
# Short growing encoder windows can contain one extra padded
# state. Match the exact same suffix/energy rule as V3/V5.
n=min(len(context),len(context_db));context=context[-n:];context_db=context_db[-n:]
layers=None if early is None or early[2*i] is None else np.concatenate([early[2*i],h[None]],axis=0)
result[session][0].append({'kind':'SPEAKER_FEATURES','features':h,'energy_db':energy,'audio16':user.copy(),
'layer_features':layers,'context_features':context,'context_energy_db':context_db,
'playback_rms':float(np.sqrt(np.mean(agent**2)))})
return result
engine.asr.encode=encode
engine.process=process
def local_only(request):
# A Cloudflare reverse proxy also connects over loopback: remote alone is
# NOT sufficient to keep expensive development routes off the public URL.
if (request.remote!='127.0.0.1' or request.host!='127.0.0.1:8793'
or any(k in request.headers for k in ('CF-Ray','CF-Connecting-IP','Forwarded','X-Forwarded-For'))):
raise web.HTTPForbidden()
async def transcribe_check(request,ears):
"""Private bounded ASR diagnostic; same frozen decoder, no LLM/TTS/write."""
local_only(request)
raw=await request.read()
if not raw or len(raw)%4:raise web.HTTPBadRequest(text='float32 mono 16-kHz PCM required')
audio=np.frombuffer(raw,'<f4')
if len(audio)>30*16000 or not np.isfinite(audio).all():raise web.HTTPBadRequest()
session=await reserve_research(ears)
try:
text=await asyncio.to_thread(ears.service.engine.asr.transcribe,[audio.copy()])
return web.json_response({'text':text[0] if text else '', 'seconds':len(audio)/16000})
finally:ears.close(session)
async def extract(request,ears):
local_only(request)
session=await reserve_research(ears)
try:
raw=await request.read()
if not raw or len(raw)%4:raise web.HTTPBadRequest(text='float32 LE mono 16 kHz PCM required')
audio=np.frombuffer(raw,'<f4')
if len(audio)>30*16000 or not np.isfinite(audio).all():raise web.HTTPBadRequest(text='Finite audio <=30 seconds required')
blocks=[]
for i in range(0,len(audio),5120):
hop=np.pad(audio[i:i+5120],(0,max(0,5120-len(audio[i:i+5120]))))
events=await ears.feed(session,hop,np.zeros(5120,np.float32),'speaking')
blocks.extend(e['features'] for e in events if e['kind']=='SPEAKER_FEATURES')
features=np.concatenate(blocks)
ends=np.arange(1,len(features)+1,dtype=np.float32)*.08
keep=ends<=len(audio)/16000+1e-5
buffer=io.BytesIO()
np.savez_compressed(buffer,features=features[keep].astype(np.float16),frame_end_s=ends[keep],
encoder_layer=np.int32(15),frame_ms=np.int32(80),hop_ms=np.int32(320))
return web.Response(body=buffer.getvalue(),content_type='application/x-npz')
finally:
ears.close(session)
async def extract_context(request,ears):
"""Offline-only selected clock steps: batch four 8-s causal windows.
Reserve the existing slot only for one short encoder batch. Browser sessions
win between calls. No second model, no GRU state change, no future audio.
"""
local_only(request)
# Default remains byte/shape compatible with the immutable V3 cache.
try: context_frames=int(request.query.get('frames','25'))
except ValueError:raise web.HTTPBadRequest(text='frames must be 25 or 38')
if context_frames not in (25,38):raise web.HTTPBadRequest(text='frames must be 25 or 38')
session=await reserve_research(ears)
try:
raw=await request.read()
if len(raw)%4:raise web.HTTPBadRequest()
values=np.frombuffer(raw,'<f4')
if not len(values) or len(values)%(8*16000) or len(values)>4*8*16000 or not np.isfinite(values).all():
raise web.HTTPBadRequest(text='1–4 float32 mono 8-second windows required')
waves=values.reshape(-1,128000)
def work():
import torch,time
from app.plugins.ears.tyger.rules import frame_energy
begin=time.perf_counter()
hidden=ears.service.engine.asr.encode(list(waves))
features=[];pools=[];energy=[]
for h,w in zip(hidden,waves):
x=h.detach().cpu().numpy().astype(np.float32)
db=frame_energy(w)[-len(x):]
n=min(len(db),len(x));x=x[-n:];db=db[-n:]
voiced=x[db>-50]
if not len(voiced):voiced=x
if n<context_frames:raise RuntimeError('Encoder returned insufficient causal states')
features.append(x[-context_frames:]);energy.append(db[-context_frames:])
pools.append(np.stack([voiced.mean(0),voiced.std(0)]))
torch.cuda.synchronize()
return np.stack(features),np.stack(pools),np.stack(energy),time.perf_counter()-begin
features,pools,energy,seconds=await asyncio.to_thread(work)
result=io.BytesIO()
np.savez_compressed(result,features=features.astype(np.float16),pool=pools.astype(np.float16),
energy=energy.astype(np.float16),encoder_seconds=np.float32(seconds),frame_ms=np.int32(80))
return web.Response(body=result.getvalue(),content_type='application/x-npz')
finally:ears.close(session)
async def extract_layers(request,ears):
"""Private research tap: L4/L8/L12/L15, newest four 80-ms states.
Temporary hooks observe this request's thread only. The native L15 stop
hook, ASR decoding thread, TYGER inputs and decisions are not modified.
"""
local_only(request)
session=await reserve_research(ears)
try:
raw=await request.read()
if len(raw)%4:raise web.HTTPBadRequest()
values=np.frombuffer(raw,'<f4')
if not len(values) or len(values)%128000 or len(values)>512000 or not np.isfinite(values).all():
raise web.HTTPBadRequest(text='1–4 finite eight-second mono float32 windows required')
waves=values.reshape(-1,128000)
def work():
import threading,time,torch
begin=time.perf_counter();asr=ears.service.engine.asr;owner=threading.get_ident();captured={};hooks=[]
def tap(layer):
def hook(module,args,out):
if threading.get_ident()==owner:
x=out[0] if isinstance(out,tuple) else out
captured[layer]=x[:,-4:].detach().clone()
return hook
try:
for layer in (4,8,12):hooks.append(asr.enc.layers[layer-1].register_forward_hook(tap(layer)))
# Direct equal-length encode also captures genuine zero windows;
# encode()'s L15-only silence cache cannot supply earlier layers.
from app.plugins.ears.tyger.asr import _StopAtL15
with torch.no_grad():
feats,mask=asr.features(list(waves));asr._tls.stop=True
try:asr.enc(input_features=feats,attention_mask=mask,num_lookahead_tokens=0)
except _StopAtL15:pass
finally:asr._tls.stop=False
captured[15]=asr._tls.h[:,-4:]
x=torch.stack([captured[layer] for layer in (4,8,12,15)],dim=1).float().cpu().numpy()
torch.cuda.synchronize();return x,time.perf_counter()-begin
finally:
for hook in hooks:hook.remove()
x,seconds=await asyncio.to_thread(work)
out=io.BytesIO();np.savez_compressed(out,features=x.astype(np.float16),layers=np.array([4,8,12,15]),encoder_seconds=seconds)
return web.Response(body=out.getvalue(),content_type='application/x-npz')
finally:ears.close(session)
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