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79 lines
2.4 KiB
79 lines
2.4 KiB
# Copyright (c) 2022 PaddlePaddle Authors. All Rights Reserved. |
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# |
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# Licensed under the Apache License, Version 2.0 (the "License"); |
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# you may not use this file except in compliance with the License. |
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# You may obtain a copy of the License at |
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# |
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# http://www.apache.org/licenses/LICENSE-2.0 |
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# |
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# Unless required by applicable law or agreed to in writing, software |
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# distributed under the License is distributed on an "AS IS" BASIS, |
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# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. |
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# See the License for the specific language governing permissions and |
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# limitations under the License. |
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import inspect |
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import paddle |
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import paddlers |
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from paddlers.tasks.change_detector import BaseChangeDetector |
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from attach_tools import Attach |
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attach = Attach.to(paddlers.tasks.change_detector) |
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def make_trainer(net_type, *args, **kwargs): |
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def _init_func(self, |
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num_classes=2, |
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use_mixed_loss=False, |
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losses=None, |
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**params): |
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sig = inspect.signature(net_type.__init__) |
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net_params = { |
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k: p.default |
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for k, p in sig.parameters.items() if not p.default is p.empty |
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} |
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net_params.pop('self', None) |
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net_params.pop('num_classes', None) |
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net_params.update(params) |
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super(trainer_type, self).__init__( |
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model_name=net_type.__name__, |
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num_classes=num_classes, |
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use_mixed_loss=use_mixed_loss, |
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losses=losses, |
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**net_params) |
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if not issubclass(net_type, paddle.nn.Layer): |
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raise TypeError("net must be a subclass of paddle.nn.Layer") |
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trainer_name = net_type.__name__ |
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trainer_type = type(trainer_name, (BaseChangeDetector, ), |
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{'__init__': _init_func}) |
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return trainer_type(*args, **kwargs) |
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@attach |
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class CustomTrainer(BaseChangeDetector): |
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def __init__(self, |
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num_classes=2, |
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use_mixed_loss=False, |
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losses=None, |
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in_channels=3, |
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att_types='ct', |
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use_dropout=False, |
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**params): |
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params.update({ |
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'in_channels': in_channels, |
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'att_types': att_types, |
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'use_dropout': use_dropout |
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}) |
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super().__init__( |
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model_name='CustomModel', |
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num_classes=num_classes, |
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use_mixed_loss=use_mixed_loss, |
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losses=losses, |
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**params)
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