Remove redundant code from TrainingArgs (#24401)

Remove redundant code

src/transformers/training_args.py

@@ -1815,15 +1815,10 @@ class TrainingArguments:
         The number of processes used in parallel.
         """
         requires_backends(self, ["torch"])
-
-        if is_torch_tpu_available():
-            return xm.xrt_world_size()
+        if self.distributed_state is not None:
+            return self.distributed_state.num_processes
         elif is_sagemaker_mp_enabled():
             return smp.dp_size() if not smp.state.cfg.prescaled_batch else smp.rdp_size()
-        elif is_sagemaker_dp_enabled():
-            return dist.get_world_size()
-        elif self.parallel_mode == ParallelMode.DISTRIBUTED:
-            return torch.distributed.get_world_size()
         return 1
 
     @property
@@ -1832,14 +1827,10 @@ class TrainingArguments:
         The index of the current process used.
         """
         requires_backends(self, ["torch"])
-        if is_torch_tpu_available():
-            return xm.get_ordinal()
+        if self.distributed_state is not None:
+            return self.distributed_state.process_index
         elif is_sagemaker_mp_enabled():
             return smp.dp_rank() if not smp.state.cfg.prescaled_batch else smp.rdp_rank()
-        elif is_sagemaker_dp_enabled():
-            return dist.get_rank()
-        elif self.parallel_mode == ParallelMode.DISTRIBUTED:
-            return torch.distributed.get_rank()
         return 0
 
     @property
@@ -1848,14 +1839,11 @@ class TrainingArguments:
         The index of the local process used.
         """
         requires_backends(self, ["torch"])
-        if is_torch_tpu_available():
-            return xm.get_local_ordinal()
+
+        if self.distributed_state is not None:
+            return self.distributed_state.local_process_index
         elif is_sagemaker_mp_enabled():
             return smp.local_rank()
-        elif is_sagemaker_dp_enabled():
-            return dist.get_rank()
-        elif self.parallel_mode == ParallelMode.DISTRIBUTED:
-            return self.local_rank
         return 0
 
     @property
@@ -1944,19 +1932,19 @@ class TrainingArguments:
 
         """
         if is_torch_available() and self.world_size > 1:
-            main_process_desc = "main process"
-            if local:
-                is_main_process = self.local_process_index == 0
-                main_process_desc = "main local process"
+            main_process_desc = "main local process" if local else "main process"
+            if self.distributed_state is not None:
+                is_main_process = (
+                    self.distributed_state.is_local_main_process if local else self.distributed_state.is_main_process
+                )
             elif is_sagemaker_mp_enabled():
                 is_main_process = smp.rank() == 0
-            else:
-                is_main_process = self.process_index == 0
 
             try:
                 if not is_main_process:
                     # tell all replicas to wait
                     logger.debug(f"{self.process_index}: waiting for the {main_process_desc} to perform {desc}")
+
                     if is_torch_tpu_available():
                         xm.rendezvous(desc)
                     else: