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openvino : fix convert-whisper-to-openvino.py for v2023.0.0 (#1870) #1890

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Feb 22, 2024
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openvino : fix convert-whisper-to-openvino.py for v2023.0.0 (#1870) #1890

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17 changes: 12 additions & 5 deletions models/convert-whisper-to-openvino.py
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Original file line number Diff line number Diff line change
Expand Up @@ -3,6 +3,7 @@
from whisper import load_model
import os
from openvino.tools import mo
from openvino.frontend import FrontEndManager
from openvino.runtime import serialize
import shutil

Expand All @@ -11,14 +12,15 @@ 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):
os.makedirs(onnx_folder)

onnx_path = os.path.join(onnx_folder, "whisper_encoder.onnx")

# Export the PyTorch model to ONNX
torch.onnx.export(
encoder,
mel,
Expand All @@ -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)

Expand Down