Incompatible Trainer.test()
🐛 Bug
Trainer.test() stops on missing definitions of train & validation dataloaders methods.
To Reproduce
Steps to reproduce the behavior:

Define LightningModule without train & validation dataloaders
Train such model with data loaders provided to Trainer.fit(...) method
Load model from checkpoint and test it with Trainer.test(...) method

test failes on :
'No `train_dataloader()` method defined. Lightning `Trainer` expects as minimum a'
pytorch_lightning.utilities.exceptions.MisconfigurationException: No `train_dataloader()` method defined. Lightning `Trainer` expects as minimum a `training_step()`, `training_dataloader()` and `configure_optimizers()` to be defined.
Code sample
test_data = data_loader(...)
estimator = MyEstimator.load_from_checkpoint(checkpoint_path=CKPT_PATH)
trainer = pl.Trainer(...)
trainer.test(model=estimator, test_dataloaders=test_data)
Expected behaviour
Run the test with provided test data loader, and do not stop on condition related to missing train & validation dataloaders which actually are not mandatory.
Environment
* Packages:
        - numpy:             1.18.4
        - pyTorch_debug:     False
        - pyTorch_version:   1.5.0
        - pytorch-lightning: 0.7.5
        - tensorboard:       2.2.1
        - tqdm:              4.46.0
* System:
        - OS:                Linux
        - architecture:
                - 64bit
                - ELF
        - processor:         
        - python:            3.8.2
        - version:           #1 SMP Wed, 29 Apr 2020 16:23:03 +0000