legop3/MultiRoombaRover
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legop3
2026-09-28 14:18:35 -04:00
parent 923c04736b
commit eed88983ca
12 changed files with 411 additions and 59 deletions
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server/src/services/roverLearningService/workers/infer.py
+9 -2
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@@ -74,7 +74,9 @@ def main():
with mutex:
while observations and observations[0]['ts'] < stamp:
event = observations.popleft()
if event['kind'] == 'sensor':
if event['kind'] == 'settings':
args.threshold = max(.05, min(.99, float(event['threshold'])))
elif event['kind'] == 'sensor':
sensors, sensor_time = event['data'], event['ts']
elif event['kind'] == 'command':
try:
@@ -102,16 +104,19 @@ def main():
continue
before = time.perf_counter()
with torch.inference_mode():
logits, numeric = model(torch.from_numpy(np.stack([row[1] for row in selected])).unsqueeze(0).float() / 255,
logits, numeric, wheel_output = model(torch.from_numpy(np.stack([row[1] for row in selected])).unsqueeze(0).float() / 255,
torch.from_numpy(np.stack([row[2] for row in selected])).unsqueeze(0))
probabilities = logits[0].sigmoid().tolist()
predictions = numeric[0].tolist()
wheel_speeds = [round(value * 500) for value in wheel_output[0].tolist()]
if not all(math.isfinite(value) for value in probabilities):
raise ValueError('Nonfinite model output')
families = {}
active = set()
proposals = []
for slot, descriptor in enumerate(schema):
if descriptor['template']['type'] == 'drive':
continue
command = json.loads(json.dumps(descriptor['template']))
family = command['type']
if family == 'peripheral':
@@ -147,8 +152,10 @@ def main():
for _, _, slot, discrete in families.values():
if discrete:
latched.add(slot)
commands.insert(0, {'type': 'drive', 'driveDirect': dict(zip(('left', 'right'), wheel_speeds))})
print(json.dumps({'kind': 'prediction', 'frameAt': stamp, 'sensorAt': sensor_time,
'latencyMs': (time.perf_counter() - before) * 1000,
'wheelSpeeds': wheel_speeds, 'sensorPresent': sensor_vector(sensors)[32:].tolist(),
'commands': commands, 'proposals': proposals, 'threshold': args.threshold}, allow_nan=False), flush=True)