shrink_group implementation to expose ncclCommShrink API (#164518)

Closes #164529

To expose the new [ncclCommShrink](https://docs.nvidia.com/deeplearning/nccl/user-guide/docs/api/comms.html#ncclcommshrink) API to PyTorch.

This is useful when you need to exclude certain GPUs or nodes from a collective operation, for example in fault tolerance scenarios or when dynamically adjusting resource utilization.

For more info:  [Shrinking a communicator](https://docs.nvidia.com/deeplearning/nccl/user-guide/docs/usage/communicators.html#shrinking-a-communicator)

Pull Request resolved: https://github.com/pytorch/pytorch/pull/164518
Approved by: https://github.com/Skylion007, https://github.com/syed-ahmed, https://github.com/kwen2501

test/distributed/logging_utils.py

@@ -0,0 +1,43 @@
+import logging
+import time
+
+
+_start_time = time.time()
+_logger = logging.getLogger(__name__)
+
+
+def _ts():
+    return time.time() - _start_time
+
+
+def configure(level=logging.INFO, force=False):
+    try:
+        logging.basicConfig(
+            level=level,
+            format="%(asctime)s %(name)s %(levelname)s: %(message)s",
+            force=force,
+        )
+    except TypeError:
+        logging.basicConfig(
+            level=level, format="%(asctime)s %(name)s %(levelname)s: %(message)s"
+        )
+
+
+def log_test_info(rank, message):
+    _logger.info("[%7.3fs][Rank %s] %s", _ts(), rank, message)
+
+
+def log_test_success(rank, message):
+    _logger.info("[%7.3fs][Rank %s] ✅ %s", _ts(), rank, message)
+
+
+def log_test_validation(rank, message):
+    _logger.info("[%7.3fs][Rank %s] ✓ %s", _ts(), rank, message)
+
+
+def log_test_warning(rank, message):
+    _logger.warning("[%7.3fs][Rank %s] ⚠️ %s", _ts(), rank, message)
+
+
+def log_test_error(rank, message):
+    _logger.error("[%7.3fs][Rank %s] ✗ %s", _ts(), rank, message)