multinode

RWKV-v4neo/src/binidx.py

@@ -8,12 +8,13 @@ from functools import lru_cache
 from itertools import accumulate
 
 def print_rank_0(*message):
-    """If distributed is initialized print only on rank 0."""
-    if torch.distributed.is_initialized():
-        if torch.distributed.get_rank() == 0:
-            print(*message, flush=True)
-    else:
-        print(*message, flush=True)
+    pass
+    # """If distributed is initialized print only on rank 0."""
+    # if torch.distributed.is_initialized():
+    #     if torch.distributed.get_rank() == 0:
+    #         print(*message, flush=True)
+    # else:
+    #     print(*message, flush=True)
 
 def _warmup_mmap_file(path):
     pass

RWKV-v4neo/src/trainer.py

@@ -71,7 +71,7 @@ class train_callback(pl.Callback):
         args = self.args
         if trainer.is_global_zero:  # logging
             t_now = time.time_ns()
-            token_per_step = args.ctx_len * float(args.devices) * args.micro_bsz
+            token_per_step = args.ctx_len * args.real_bsz
             real_step = trainer.global_step + args.epoch_begin * args.epoch_steps
             try:
                 t_cost = (t_now - trainer.my_time_ns) / 1e9
@@ -101,6 +101,7 @@ class train_callback(pl.Callback):
         dataset.global_rank = trainer.global_rank
         dataset.real_epoch = int(args.epoch_begin + trainer.current_epoch)
         dataset.world_size = trainer.world_size
+        # print(f'########## world_size {dataset.world_size} global_rank {dataset.global_rank} real_epoch {dataset.real_epoch} ##########')
 
     def on_train_epoch_end(self, trainer, pl_module):
         args = self.args

RWKV-v4neo/train.py

@@ -3,7 +3,7 @@
 ########################################################################################################
 
 if __name__ == "__main__":
-    print("\n!!! work in progress !!!\n")
+    print("########## work in progress ##########")
     import os, warnings, math, datetime, sys, time
     import numpy as np
     from argparse import ArgumentParser
@@ -108,7 +108,7 @@ if __name__ == "__main__":
     args.log_every_n_steps = int(1e20)
     args.max_epochs = -1  # continue forever
     args.betas = (args.beta1, args.beta2)
-    args.real_bsz = int(args.devices) * args.micro_bsz
+    args.real_bsz = int(args.num_nodes) * int(args.devices) * args.micro_bsz
     os.environ["RWKV_T_MAX"] = str(args.ctx_len)
 
     if not os.path.exists(args.proj_dir):
@@ -164,7 +164,7 @@ if __name__ == "__main__":
         f"""
 ############################################################################
 #
-# RWKV-4 {args.precision.upper()} on {args.devices}x{args.accelerator.upper()}, bsz {args.devices}x{args.micro_bsz}={args.real_bsz}, {args.strategy} {'with grad_cp' if args.grad_cp > 0 else ''}
+# RWKV-4 {args.precision.upper()} on {args.num_nodes}x{args.devices} {args.accelerator.upper()}, bsz {args.num_nodes}x{args.devices}x{args.micro_bsz}={args.real_bsz}, {args.strategy} {'with grad_cp' if args.grad_cp > 0 else ''}
 #
 # Data = {args.data_file} ({args.data_type}), ProjDir = {args.proj_dir}
 #