# Copyright 2020 Huawei Technologies Co., Ltd # # 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. # ============================================================================ """ ##############export checkpoint file into air, onnx, mindir models################# python export.py """ import numpy as np from mindspore import Tensor, load_checkpoint, load_param_into_net, export, context from utils.config import config from src.textcnn import TextCNN from src.dataset import MovieReview, SST2, Subjectivity context.set_context(mode=context.GRAPH_MODE, device_target=config.device_target) if config.device_target == "Ascend": context.set_context(device_id=config.device_id) if __name__ == '__main__': if config.dataset == 'MR': instance = MovieReview(root_dir=config.data_path, maxlen=config.word_len, split=0.9) elif config.dataset == 'SUBJ': instance = Subjectivity(root_dir=config.data_path, maxlen=config.word_len, split=0.9) elif config.dataset == 'SST2': instance = SST2(root_dir=config.data_path, maxlen=config.word_len, split=0.9) else: raise ValueError("dataset is not support.") net = TextCNN(vocab_len=instance.get_dict_len(), word_len=config.word_len, num_classes=config.num_classes, vec_length=config.vec_length) param_dict = load_checkpoint(config.ckpt_file) load_param_into_net(net, param_dict) input_arr = Tensor(np.ones([config.batch_size, config.word_len], np.int32)) export(net, input_arr, file_name=config.file_name, file_format=config.file_format)