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56 lines
1.8 KiB
56 lines
1.8 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 paddlers |
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from rs_models.test_model import TestModel |
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__all__ = ['TestFarSegModel'] |
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class TestSegModel(TestModel): |
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DEFAULT_HW = (512, 512) |
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def check_output(self, output, target): |
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self.assertIsInstance(output, list) |
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self.check_output_equal(len(output), len(target)) |
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for o, t in zip(output, target): |
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o = o.numpy() |
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self.check_output_equal(o.shape[0], t.shape[0]) |
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self.check_output_equal(len(o.shape), 4) |
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self.check_output_equal(o.shape[2:], t.shape[2:]) |
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def set_inputs(self): |
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def _gen_data(specs): |
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for spec in specs: |
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c = spec.get('in_channels', 3) |
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yield self.get_randn_tensor(c) |
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self.inputs = _gen_data(self.specs) |
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def set_targets(self): |
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def _gen_data(specs): |
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for spec in specs: |
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c = spec.get('num_classes', 2) |
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yield [self.get_zeros_array(c)] |
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self.targets = _gen_data(self.specs) |
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class TestFarSegModel(TestSegModel): |
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MODEL_CLASS = paddlers.custom_models.seg.FarSeg |
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def set_specs(self): |
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self.specs = [ |
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dict(), dict(num_classes=20), dict(encoder_pretrained=False) |
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]
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