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whisper.cpp
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openvino : fix convert-whisper-to-openvino.py (#1890) 

Fix issue: Conversion from Whisper to OpenVino failed #1870

convert-whisper-to-openvino.py stopped working with OpenVINO version 2023.0.0-10926-b4452d56304-releases/2023/0 .

Error was: TypeError: load(): incompatible function arguments. The following argument types are supported:
    1. (self: openvino._pyopenvino.FrontEnd, path: object) -> ov::frontend::InputModel

Tested successfully with a large-v3 conversion.

Co-authored-by: Stefan Grundmann <grundmanns@sandiego.gov>
pull/1891/head
st-gr 2024-02-22 05:11:35 -08:00 committed by GitHub
parent c56344b509
commit eb23f4ef16
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1 changed files with 12 additions and 5 deletions
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17
models/convert-whisper-to-openvino.py
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@ -3,6 +3,7 @@ import torch
from whisper import load_model
import os
from openvino.tools import mo
from openvino.frontend import FrontEndManager
from openvino.runtime import serialize
import shutil
@ -11,7 +12,7 @@ def convert_encoder(hparams, encoder, mname):
mel = torch.zeros((1, hparams.n_mels, 3000))
onnx_folder=os.path.join(os.path.dirname(__file__),"onnx_encoder")
onnx_folder = os.path.join(os.path.dirname(__file__), "onnx_encoder")
#create a directory to store the onnx model, and other collateral that is saved during onnx export procedure
if not os.path.isdir(onnx_folder):
@ -19,6 +20,7 @@ def convert_encoder(hparams, encoder, mname):
onnx_path = os.path.join(onnx_folder, "whisper_encoder.onnx")
# Export the PyTorch model to ONNX
torch.onnx.export(
encoder,
mel,
@ -27,11 +29,16 @@ def convert_encoder(hparams, encoder, mname):
output_names=["output_features"]
)
# use model optimizer to convert onnx to OpenVINO IR format
encoder_model = mo.convert_model(onnx_path, compress_to_fp16=True)
serialize(encoder_model, xml_path=os.path.join(os.path.dirname(__file__),"ggml-" + mname + "-encoder-openvino.xml"))
# Convert ONNX to OpenVINO IR format using the frontend
fem = FrontEndManager()
onnx_fe = fem.load_by_framework("onnx")
onnx_model = onnx_fe.load(onnx_path)
ov_model = onnx_fe.convert(onnx_model)
#cleanup
# Serialize the OpenVINO model to XML and BIN files
serialize(ov_model, xml_path=os.path.join(os.path.dirname(__file__), "ggml-" + mname + "-encoder-openvino.xml"))
# Cleanup
if os.path.isdir(onnx_folder):
shutil.rmtree(onnx_folder)