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Adding fp16 mode whisper #244

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Adding fp16 mode whisper #244

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d837526
Adding fp16 mode whisper
kkontny Mar 27, 2024
95cef1a
Fix run.py script
kkontny May 7, 2024
eeeee1a
Add blank lines
kkontny May 7, 2024
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28 changes: 23 additions & 5 deletions speech_recognition/whisper/run.py
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Original file line number Diff line number Diff line change
Expand Up @@ -18,7 +18,7 @@
sys.exit(1)


def run_pytorch_fp32(model_name, num_runs, timeout, **kwargs):
def run_pytorch(model_name, num_runs, timeout, use_torch_fp16=False):
import os
import sys
import torch
Expand All @@ -32,6 +32,10 @@ def run_pytorch_fp32(model_name, num_runs, timeout, **kwargs):
from speech_recognition.whisper.whisper.whisper.transcribe import transcribe
model = load_model(model_name)
model.eval()
if use_torch_fp16:
model = model.half()
model._encoder.half()
model._decoder.half()

def single_pass_pytorch(_runner, _librispeech):
array = _librispeech.get_input_array()
Expand All @@ -40,8 +44,10 @@ def single_pass_pytorch(_runner, _librispeech):
_runner.run(batch_size * array.shape[0], audio)["text"].lstrip().replace(".", "").upper()
)

decode_options = {"fp16": use_torch_fp16}

def transcribe_wrapper(audio):
return transcribe(model, audio, no_speech_threshold=1.0, verbose=None)
return transcribe(model, audio, no_speech_threshold=1.0, verbose=None, **decode_options)

runner = PyTorchRunnerV2(transcribe_wrapper, throughput_only=True)
librispeech = LibriSpeech()
Expand All @@ -50,6 +56,14 @@ def transcribe_wrapper(audio):
return run_model(single_pass_pytorch, runner, librispeech, batch_size, num_runs, timeout)


def run_pytorch_fp32(model_name, num_runs, timeout):
return run_pytorch(model_name, num_runs, timeout, use_torch_fp16=False)


def run_pytorch_fp16(model_name, num_runs, timeout):
return run_pytorch(model_name, num_runs, timeout, use_torch_fp16=True)


def run_pytorch_cuda(model_name, num_runs, timeout, **kwargs):
import os
import sys
Expand Down Expand Up @@ -89,8 +103,12 @@ def transcribe_wrapper(audio):
whisper_variants = whisper_variants + [f"{name}.en" for name in whisper_variants[:4]]
parser = DefaultArgParser(["pytorch"])
parser.require_model_name(whisper_variants)
parser.add_argument("-p", "--precision", type=str, choices=["fp32", "fp16"], required=True)

args = vars(parser.parse())
if torch.cuda.is_available():
run_pytorch_cuda(**vars(parser.parse()))
else:
run_pytorch_fp32(**vars(parser.parse()))
run_pytorch_cuda(**args)
elif args["precision"] == "fp32":
run_pytorch_fp32(**args)
elif args["precision"] == "fp16":
run_pytorch_fp16(**args)