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# Copyright (c) 2022 PaddlePaddle Authors. All Rights Reserved.
#
# 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 os
import argparse
from ast import literal_eval
from paddlers.tasks import load_model
def get_parser():
parser = argparse.ArgumentParser()
parser.add_argument(
'--model_dir',
'-m',
type=str,
default=None,
help='model directory path')
parser.add_argument(
'--save_dir',
'-s',
type=str,
default=None,
help='path to save inference model')
parser.add_argument(
'--fixed_input_shape',
'-fs',
type=str,
default=None,
help="export inference model with fixed input shape: [w,h] or [n,c,w,h]")
return parser
if __name__ == '__main__':
parser = get_parser()
args = parser.parse_args()
# Get input shape
fixed_input_shape = None
if args.fixed_input_shape is not None:
# Try to interpret the string as a list.
fixed_input_shape = literal_eval(args.fixed_input_shape)
# Check validaty
if not isinstance(fixed_input_shape, list):
raise ValueError(
"fixed_input_shape should be of None or list type.")
if len(fixed_input_shape) not in (2, 4):
raise ValueError(
"fixed_input_shape contains an incorrect number of elements.")
if fixed_input_shape[-1] <= 0 or fixed_input_shape[-2] <= 0:
raise ValueError(
"Input width and height must be positive integers.")
if len(fixed_input_shape) == 4 and fixed_input_shape[1] <= 0:
raise ValueError(
"The number of input channels must be a positive integer.")
# Set environment variables
os.environ['PADDLEX_EXPORT_STAGE'] = 'True'
os.environ['PADDLESEG_EXPORT_STAGE'] = 'True'
# Load model from directory
model = load_model(args.model_dir)
# Do dynamic-to-static cast
# XXX: Invoke a protected (single underscore) method outside of subclasses.
model._export_inference_model(args.save_dir, fixed_input_shape)