mirror of
https://github.com/wassname/pytorch-lightning.git
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Jirka BorovecandWilliam Falcon
2a2f303ae9
* refactor default model * drop redundant seeds * refactor dataloaders tests * fix multiple * fix conf * flake8 * Apply suggestions from code review Co-authored-by: William Falcon <waf2107@columbia.edu> Co-authored-by: William Falcon <waf2107@columbia.edu>
94 lines
2.5 KiB
Python
94 lines
2.5 KiB
Python
from abc import ABC
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from collections import OrderedDict
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import torch
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class TestStepVariations(ABC):
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"""
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Houses all variations of test steps
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"""
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def test_step(self, batch, batch_idx, *args, **kwargs):
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"""
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Default, baseline test_step
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:param batch:
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:return:
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"""
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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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loss_test = self.loss(y, y_hat)
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# acc
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labels_hat = torch.argmax(y_hat, dim=1)
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test_acc = torch.sum(y == labels_hat).item() / (len(y) * 1.0)
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test_acc = torch.tensor(test_acc)
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test_acc = test_acc.type_as(x)
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# alternate possible outputs to test
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if batch_idx % 1 == 0:
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output = OrderedDict({
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'test_loss': loss_test,
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'test_acc': test_acc,
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})
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return output
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if batch_idx % 2 == 0:
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return test_acc
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if batch_idx % 3 == 0:
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output = OrderedDict({
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'test_loss': loss_test,
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'test_acc': test_acc,
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'test_dic': {'test_loss_a': loss_test}
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})
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return output
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def test_step__multiple_dataloaders(self, batch, batch_idx, dataloader_idx, **kwargs):
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"""
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Default, baseline test_step
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:param batch:
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:return:
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"""
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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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loss_test = self.loss(y, y_hat)
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# acc
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labels_hat = torch.argmax(y_hat, dim=1)
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test_acc = torch.sum(y == labels_hat).item() / (len(y) * 1.0)
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test_acc = torch.tensor(test_acc)
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test_acc = test_acc.type_as(x)
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# alternate possible outputs to test
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if batch_idx % 1 == 0:
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output = OrderedDict({
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'test_loss': loss_test,
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'test_acc': test_acc,
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})
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return output
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if batch_idx % 2 == 0:
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return test_acc
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if batch_idx % 3 == 0:
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output = OrderedDict({
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'test_loss': loss_test,
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'test_acc': test_acc,
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'test_dic': {'test_loss_a': loss_test}
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})
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return output
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if batch_idx % 5 == 0:
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output = OrderedDict({
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f'test_loss_{dataloader_idx}': loss_test,
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f'test_acc_{dataloader_idx}': test_acc,
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})
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return output
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def test_step__empty(self, batch, batch_idx, *args, **kwargs):
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return {}
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