Merge branch 'main' into upgrade-torch

configs/experiment/RandLaNet_base_run_FR-2x3GPUs.yaml

@@ -0,0 +1,18 @@
+# @package _global_
+defaults:
+  - RandLaNet_base_run_FR.yaml
+
+logger:
+  comet:
+    experiment_name: "RandLaNet_base_run_FR-2x3GPUs"
+
+
+# 2 nodes x 3 GPUs - No gradient accumulation. 
+# This is equivalent to training with 2 GPUs with gradients accumulated 3 times.
+# Setting precision=16 did not bring any speed improvement for Lidar HD data and RandLa-Net model.
+trainer:
+  strategy: ddp_find_unused_parameters_false
+  accelerator: gpu
+  num_nodes: 2
+  devices: 3
+  accumulate_grad_batches: 1

configs/experiment/RandLaNet_base_run_FR-MultiGPU.yaml

@@ -4,9 +4,10 @@ defaults:
 
 logger:
   comet:
-    experiment_name: "Pyg RandLaNet - FR Data - 2xGPUs"
+    experiment_name: "RandLaNet_base_run_FR-2xGPUs"
 
 trainer:
   strategy: ddp_find_unused_parameters_false
+  # Replace by cpu to simulate multi-cpus training.
   accelerator: gpu
   devices: 2