29 lines
723 B
Python
29 lines
723 B
Python
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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hparams: ...
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def dataloader(self, train):
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dataset = TrialMNIST(root=self.data_root, train=train, 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=3,
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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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