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updated docs

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William Falcon
2019-07-25 11:35:11 -04:00
parent 9fa8120805
commit 0f79e9d74e
1 changed files with 29 additions and 45 deletions
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docs/LightningModule/RequiredTrainerInterface.md
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@@ -248,22 +248,16 @@ Pytorch DataLoader
**Example**
``` {.python}
@property
@ptl.data_loader
def tng_dataloader(self):
if self._tng_dataloader is None:
try:
transform = transforms.Compose([transforms.ToTensor(), transforms.Normalize((0.5,), (1.0,))])
dataset = MNIST(root='/path/to/mnist/', train=True, transform=transform, download=True)
loader = torch.utils.data.DataLoader(
dataset=dataset,
batch_size=self.hparams.batch_size,
shuffle=True
)
self._tng_dataloader = loader
except Exception as e:
raise e
return self._tng_dataloader
transform = transforms.Compose([transforms.ToTensor(), transforms.Normalize((0.5,), (1.0,))])
dataset = MNIST(root='/path/to/mnist/', train=True, transform=transform, download=True)
loader = torch.utils.data.DataLoader(
dataset=dataset,
batch_size=self.hparams.batch_size,
shuffle=True
)
return loader
```
---
@@ -281,22 +275,17 @@ Pytorch DataLoader
**Example**
``` {.python}
@property
@ptl.data_loader
def val_dataloader(self):
if self._val_dataloader is None:
try:
transform = transforms.Compose([transforms.ToTensor(), transforms.Normalize((0.5,), (1.0,))])
dataset = MNIST(root='/path/to/mnist/', train=False, transform=transform, download=True)
loader = torch.utils.data.DataLoader(
dataset=dataset,
batch_size=self.hparams.batch_size,
shuffle=True
)
self._val_dataloader = loader
except Exception as e:
raise e
return self._val_dataloader
transform = transforms.Compose([transforms.ToTensor(), transforms.Normalize((0.5,), (1.0,))])
dataset = MNIST(root='/path/to/mnist/', train=False, transform=transform, download=True)
loader = torch.utils.data.DataLoader(
dataset=dataset,
batch_size=self.hparams.batch_size,
shuffle=True
)
return loader
```
---
@@ -314,22 +303,17 @@ Pytorch DataLoader
**Example**
``` {.python}
@property
@ptl.data_loader
def test_dataloader(self):
if self._test_dataloader is None:
try:
transform = transforms.Compose([transforms.ToTensor(), transforms.Normalize((0.5,), (1.0,))])
dataset = MNIST(root='/path/to/mnist/', train=False, transform=transform, download=True)
loader = torch.utils.data.DataLoader(
dataset=dataset,
batch_size=self.hparams.batch_size,
shuffle=True
)
self._test_dataloader = loader
except Exception as e:
raise e
return self._test_dataloader
transform = transforms.Compose([transforms.ToTensor(), transforms.Normalize((0.5,), (1.0,))])
dataset = MNIST(root='/path/to/mnist/', train=False, transform=transform, download=True)
loader = torch.utils.data.DataLoader(
dataset=dataset,
batch_size=self.hparams.batch_size,
shuffle=True
)
return loader
```
---