Adding non-layer param count to summary

[rhiga2]

What does this PR do?

This PR adds the count of parameters not associated to any layer to the model summary. The new model summary should add an extra row to the summary table that specifies the count of params that have not been reported by any layer summary.

Fixes #12736

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[awaelchli]

@rhiga2 Could you take a look at your implementation again for this case:

import torch
from torch.utils.data import DataLoader, Dataset
from lightning.pytorch import LightningModule, Trainer


class RandomDataset(Dataset):
    def __init__(self, size, length):
        self.len = length
        self.data = torch.randn(length, size)

    def __getitem__(self, index):
        return self.data[index]

    def __len__(self):
        return self.len


class BoringModel(LightningModule):
    def __init__(self):
        super().__init__()
        self.layer = torch.nn.Linear(32, 2)
        self.param = torch.nn.Parameter(torch.rand(3))  # this parameter is unused

    def forward(self, x):
        return self.layer(x)

    def training_step(self, batch, batch_idx):
        return self(batch).sum()

    def train_dataloader(self):
        return DataLoader(RandomDataset(32, 64), batch_size=2)

    def configure_optimizers(self):
        return torch.optim.SGD(self.layer.parameters(), lr=0.1)


def run():
    model = BoringModel()
    trainer = Trainer(max_steps=1)
    trainer.fit(model)


if __name__ == "__main__":
    run()

which errors out with

  File "/Users/adrian/repositories/lightning/src/lightning/pytorch/utilities/model_summary/model_summary.py", line 317, in _add_leftover_params_to_summary
    layer_summaries["In sizes"].append(NOT_APPLICABLE)
KeyError: 'In sizes'

[awaelchli]

Overall approach LGTM, but we are missing the regular use case when no example input array is provided. Let's extend the test case for that and handle the optional columns correctly.