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hotfix to unblock hparams and OmniConf - removes auto_register_init_args by default (#2025)

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* ogc install

* cleaned up tests

* hot fix

* hot fix

* hot fix

* hot fix

* hot fix

* hot fix

* hot fix

* hot fix

* hot fix
This commit is contained in:
William Falcon
2020-05-31 08:29:51 -04:00
committed by GitHub
parent 9893681859
commit 0e37e8c4d2
8 changed files with 120 additions and 98 deletions
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tests/base/model_valid_steps.py
+13 -58
View File
@@ -23,33 +23,14 @@ class ValidationStepVariations(ABC):
# acc
labels_hat = torch.argmax(y_hat, dim=1)
val_acc = torch.sum(y == labels_hat).item() / (len(y) * 1.0)
val_acc = torch.tensor(val_acc)
val_acc = torch.tensor(val_acc).type_as(x)
if self.on_gpu:
val_acc = val_acc.cuda(loss_val.device.index)
# in DP mode (default) make sure if result is scalar, there's another dim in the beginning
if self.trainer.use_dp:
loss_val = loss_val.unsqueeze(0)
val_acc = val_acc.unsqueeze(0)
# alternate possible outputs to test
if batch_idx % 1 == 0:
output = OrderedDict({
'val_loss': loss_val,
'val_acc': val_acc,
})
return output
if batch_idx % 2 == 0:
return val_acc
if batch_idx % 3 == 0:
output = OrderedDict({
'val_loss': loss_val,
'val_acc': val_acc,
'test_dic': {'val_loss_a': loss_val}
})
return output
output = OrderedDict({
'val_loss': loss_val,
'val_acc': val_acc,
'test_dic': {'val_loss_a': loss_val}
})
return output
def validation_step__multiple_dataloaders(self, batch, batch_idx, dataloader_idx, **kwargs):
"""
@@ -66,36 +47,10 @@ class ValidationStepVariations(ABC):
# acc
labels_hat = torch.argmax(y_hat, dim=1)
val_acc = torch.sum(y == labels_hat).item() / (len(y) * 1.0)
val_acc = torch.tensor(val_acc)
val_acc = torch.tensor(val_acc).type_as(x)
if self.on_gpu:
val_acc = val_acc.cuda(loss_val.device.index)
# in DP mode (default) make sure if result is scalar, there's another dim in the beginning
if self.trainer.use_dp:
loss_val = loss_val.unsqueeze(0)
val_acc = val_acc.unsqueeze(0)
# alternate possible outputs to test
if batch_idx % 1 == 0:
output = OrderedDict({
'val_loss': loss_val,
'val_acc': val_acc,
})
return output
if batch_idx % 2 == 0:
return val_acc
if batch_idx % 3 == 0:
output = OrderedDict({
'val_loss': loss_val,
'val_acc': val_acc,
'test_dic': {'val_loss_a': loss_val}
})
return output
if batch_idx % 5 == 0:
output = OrderedDict({
f'val_loss_{dataloader_idx}': loss_val,
f'val_acc_{dataloader_idx}': val_acc,
})
return output
output = OrderedDict({
f'val_loss_{dataloader_idx}': loss_val,
f'val_acc_{dataloader_idx}': val_acc,
})
return output