No validation checks when overfit_pct is set
🐛 Bug
When setting the overfit_pct to any value between 0 and 1 (exclusive) in trainer, the validation checks are disabled.
To Reproduce
I have worked on a minimal example to reproduce the bug:
import pytorch_lightning as pl
import torch

class Dataset(torch.utils.data.Dataset):

    def __init__(self, input_dim, output_dim):
        super(Dataset, self).__init__()
        self.input_dim = input_dim
        self.output_dim = output_dim

    def __getitem__(self, idx):
        X = torch.rand(1, self.input_dim)
        y = torch.randint(0, self.output_dim, (1,))
        return X, y

    def __len__(self):
        return 1000

class Model(pl.LightningModule):

    def __init__(self, input_dim, output_dim):
        super(Model, self).__init__()
        self.layer = torch.nn.Linear(input_dim, output_dim)
        self.dataset = Dataset(input_dim, output_dim)

    def forward(self, x, y):
        yhat = torch.softmax(self.layer(x), -1)
        return F.nll_loss(logits, y)

    def train_dataloader(self):
        return torch.utils.data.DataLoader(self.dataset, batch_size=64)

    def configure_optimizers(self):
        return torch.optim.Adam(self.parameters(), lr=1e-3)

    def training_step(self, batch, batch_idx):
        loss = self.forward(*batch)
        return {'loss': loss, 'log': {'loss': loss}}

    def validation_step(self, batch, batch_idx):
        loss = self.forward(*batch)
        return {'val_loss': loss, 'log': {'val_loss': loss}}


if __name__ == '__main__':
    model = Model(100, 10)
    trainer = pl.Trainer(overfit_pct=.01)
    trainer.fit(model)
Expected behavior
Validation checks occur normally
Environment
PyTorch version: 1.4.0
Is debug build: No
CUDA used to build PyTorch: 10.1

OS: Manjaro Linux
GCC version: (GCC) 8.3.0
CMake version: Could not collect

Python version: 3.7
Is CUDA available: No
CUDA runtime version: 10.2.89
GPU models and configuration: Could not collect
Nvidia driver version: Could not collect
cuDNN version: /usr/lib/libcudnn.so.7.6.5

Versions of relevant libraries:
[pip] numpy==1.18.1
[pip] pytorch-lightning==0.7.1
[pip] torch==1.4.0
[pip] torchvision==0.5.0
[conda] mkl                       2020.0                      166  
[conda] pytorch                   1.4.0           py3.7_cuda10.1.243_cudnn7.6.3_0    pytorch
[conda] pytorch-lightning         0.7.1                    pypi_0    pypi
[conda] torchvision               0.5.0                py37_cu101    pytorch