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"""Callback that compresses a trained model by first exporting to .onnx format, and then converting to OpenVINO IR."""
# Copyright (C) 2020 Intel Corporation
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing,
# software distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions
# and limitations under the License.
import logging
import os
from typing import Tuple
from pytorch_lightning import Callback
from anomalib.deploy import export_convert
from anomalib.models.components import AnomalyModule
logger = logging.getLogger(__name__)
class OpenVINOCallback(Callback):
"""Callback to compresses a trained model.
Model is first exported to ``.onnx`` format, and then converted to OpenVINO IR.
Args:
input_size (Tuple[int, int]): Tuple of image height, width
dirpath (str): Path for model output
filename (str): Name of output model
"""
def __init__(self, input_size: Tuple[int, int], dirpath: str, filename: str):
self.input_size = input_size
self.dirpath = dirpath
self.filename = filename
def on_train_end(self, trainer, pl_module: AnomalyModule) -> None: # pylint: disable=W0613
"""Call when the train ends.
Converts the model to ``onnx`` format and then calls OpenVINO's model optimizer to get the
``.xml`` and ``.bin`` IR files.
"""
logger.info("Exporting the model to OpenVINO")
os.makedirs(self.dirpath, exist_ok=True)
onnx_path = os.path.join(self.dirpath, self.filename + ".onnx")
export_convert(
model=pl_module,
input_size=self.input_size,
onnx_path=onnx_path,
export_path=self.dirpath,
)
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