41 lines
1.3 KiB
Python
41 lines
1.3 KiB
Python
# Copyright The PyTorch Lightning team.
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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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from torch.utils.data import DataLoader
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from tests.base.datasets import TrialMNIST
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class ModelTemplateData:
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def dataloader(self, train: bool, num_samples: int = 100):
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dataset = TrialMNIST(root=self.data_root, train=train, num_samples=num_samples, download=True)
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loader = DataLoader(
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dataset=dataset,
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batch_size=self.batch_size,
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num_workers=0,
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shuffle=train,
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)
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return loader
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class ModelTemplateUtils:
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def get_output_metric(self, output, name):
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if isinstance(output, dict):
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val = output[name]
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else: # if it is 2level deep -> per dataloader and per batch
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val = sum(out[name] for out in output) / len(output)
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return val
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