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This commit is contained in:
Fangjun Kuang 2022-05-20 00:38:44 +08:00
parent 4b59573473
commit bcd0e872b8
1 changed files with 13 additions and 3 deletions
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16
bin/offline_server.py
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@ -17,7 +17,7 @@
""" """
A server for offline ASR recognition. Offline means you send all the content A server for offline ASR recognition. Offline means you send all the content
of the audio for recognition. It supports multiple client sending at of the audio for recognition. It supports multiple clients sending at
the same time. the same time.
TODO(fangjun): Run CPU-bound tasks such as neural network computation and TODO(fangjun): Run CPU-bound tasks such as neural network computation and
@ -93,12 +93,14 @@ class OfflineServer:
bpe_model_filename: str, bpe_model_filename: str,
num_device: int, num_device: int,
feature_extractor_pool_size: int = 3, feature_extractor_pool_size: int = 3,
nn_pool_size: int = -1, nn_pool_size: int = 3,
): ):
""" """
Args: Args:
nn_model_filename: nn_model_filename:
Path to the torch script model. Path to the torch script model.
bpe_model_filename:
Path to the BPE model.
num_device: num_device:
If 0, use CPU for neural network computation and decoding. If 0, use CPU for neural network computation and decoding.
If positive, it means the number of GPUs to use for NN computation If positive, it means the number of GPUs to use for NN computation
@ -177,11 +179,15 @@ class OfflineServer:
async def loop(self, port: int): async def loop(self, port: int):
logging.info("started") logging.info("started")
asyncio.create_task(self.feature_consumer_task()) task = asyncio.create_task(self.feature_consumer_task())
# We can create multiple consumer tasks if needed
# asyncio.create_task(self.feature_consumer_task()) # asyncio.create_task(self.feature_consumer_task())
# asyncio.create_task(self.feature_consumer_task()) # asyncio.create_task(self.feature_consumer_task())
async with websockets.serve(self.handle_connection, "", port): async with websockets.serve(self.handle_connection, "", port):
await asyncio.Future() # run forever await asyncio.Future() # run forever
await task
async def recv_audio_samples( async def recv_audio_samples(
self, self,
@ -223,6 +229,10 @@ class OfflineServer:
return torch.frombuffer(received, dtype=torch.float32) return torch.frombuffer(received, dtype=torch.float32)
async def feature_consumer_task(self): async def feature_consumer_task(self):
"""This function extracts features from the feature_queue,
batches them up, sends them to the RNN-T model for computation
and decoding.
"""
sleep_time = 20 / 1000.0 # wait for 20ms sleep_time = 20 / 1000.0 # wait for 20ms
batch_size = 5 batch_size = 5
while True: while True: