Person segmentation using torch lightning

Summary:
Add option to train Person Instance Segmentation using lightning instead of D2 (https://github.com/facebookresearch/d2go/commit/7992f91324aee6ae59795063a007c6837e60cdb8).
This is needed because we want to try PIS with SuperNet and our SuperNet based training is implemented in d2go lightning task

Reviewed By: zhanghang1989

Differential Revision: D33281437

fbshipit-source-id: e1b6567f3c77ce51240fb50d81350bc97735713a

d2go/utils/testing/lightning_train_helper.py

+#!/usr/bin/env python3
+# Copyright (c) Facebook, Inc. and its affiliates. All Rights Reserved
+import pytorch_lightning as pl  # type: ignore
+from detectron2.utils.events import EventStorage
+from pytorch_lightning.callbacks.model_checkpoint import ModelCheckpoint
+
+
+def get_lt_trainer(output_dir: str, cfg):
+    checkpoint_callback = ModelCheckpoint(dirpath=output_dir, save_last=True)
+    return pl.Trainer(
+        max_epochs=10 ** 8,
+        max_steps=cfg.SOLVER.MAX_ITER,
+        val_check_interval=cfg.TEST.EVAL_PERIOD
+        if cfg.TEST.EVAL_PERIOD > 0
+        else cfg.SOLVER.MAX_ITER,
+        callbacks=[checkpoint_callback],
+        logger=None,
+    )
+
+
+def lt_train(task, trainer):
+    with EventStorage() as storage:
+        task.storage = storage
+        trainer.fit(task)
+
+
+def lt_test(task, trainer):
+    with EventStorage() as storage:
+        task.storage = storage
+        trainer.test(task)
+        return task.eval_res