41 lines
1.1 KiB
Python
41 lines
1.1 KiB
Python
import math
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from abc import ABC
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from collections import OrderedDict
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import torch
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class TrainingStepVariations(ABC):
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"""
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Houses all variations of training steps
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"""
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test_step_inf_loss = float('inf')
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def training_step(self, batch, batch_idx, optimizer_idx=None):
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"""Lightning calls this inside the training loop"""
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# forward pass
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x, y = batch
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x = x.view(x.size(0), -1)
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y_hat = self(x)
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# calculate loss
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loss_val = self.loss(y, y_hat)
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# alternate possible outputs to test
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output = OrderedDict({
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'loss': loss_val,
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'progress_bar': {'some_val': loss_val * loss_val},
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'log': {'train_some_val': loss_val * loss_val},
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})
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return output
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def training_step__inf_loss(self, batch, batch_idx, optimizer_idx=None):
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output = self.training_step(batch, batch_idx, optimizer_idx)
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if batch_idx == self.test_step_inf_loss:
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if isinstance(output, dict):
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output['loss'] *= torch.tensor(math.inf) # make loss infinite
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else:
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output /= 0
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return output
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