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1# Copyright 2020 Huawei Technologies Co., Ltd
2#
3# Licensed under the Apache License, Version 2.0 (the "License");
4# you may not use this file except in compliance with the License.
5# You may obtain a copy of the License at
6#
7# http://www.apache.org/licenses/LICENSE-2.0
8#
9# Unless required by applicable law or agreed to in writing, software
10# distributed under the License is distributed on an "AS IS" BASIS,
11# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
12# See the License for the specific language governing permissions and
13# limitations under the License.
14# ============================================================================
15""" infer """
16from argparse import ArgumentParser
17import numpy as np
18
19from mindspore import Tensor
20from ....dataset_mock import MindData
21
22__factory = {
23    "resnet50": resnet50(),
24}
25
26
27def parse_args():
28    """ parse_args """
29    parser = ArgumentParser(description="resnet50 example")
30
31    parser.add_argument("--model", type=str, default="resnet50",
32                        help="the network architecture for training or testing")
33    parser.add_argument("--phase", type=str, default="test",
34                        help="the phase of the model, default is test.")
35    parser.add_argument("--file_path", type=str, default="/data/file/test1.txt",
36                        help="data directory of training or testing")
37    parser.add_argument("--batch_size", type=int, default=1,
38                        help="batch size for training or testing ")
39
40    return parser.parse_args()
41
42
43def get_model(name):
44    """ get_model """
45    if name not in __factory:
46        raise KeyError("unknown model:", name)
47    return __factory[name]
48
49
50def get_dataset(batch_size=32):
51    """ get_dataset """
52    dataset_types = np.float32
53    dataset_shapes = (batch_size, 3, 224, 224)
54
55    dataset = MindData(size=2, batch_size=batch_size,
56                       np_types=dataset_types,
57                       output_shapes=dataset_shapes,
58                       input_indexs=(0, 1))
59    return dataset
60
61
62# pylint: disable=unused-argument
63def test(name, file_path, batch_size):
64    """ test """
65    network = get_model(name)
66
67    batch = get_dataset(batch_size=batch_size)
68
69    data_list = []
70    for data in batch:
71        data_list.append(data.asnumpy())
72    batch_data = np.concatenate(data_list, axis=0).transpose((0, 3, 1, 2))
73    input_tensor = Tensor(batch_data)
74    print(input_tensor.shape)
75    network(input_tensor)
76
77
78if __name__ == '__main__':
79    args = parse_args()
80    if args.phase == "train":
81        raise NotImplementedError
82    test(args.model, args.file_path, args.batch_size)
83