diff --git a/src/accelerate/accelerator.py b/src/accelerate/accelerator.py
index 7eb3e65d099..0eea266c962 100755
--- a/src/accelerate/accelerator.py
+++ b/src/accelerate/accelerator.py
@@ -102,10 +102,10 @@
     save_fsdp_optimizer,
     wait_for_everyone,
 )
+from .utils import parallel_state as mpu
 from .utils.constants import FSDP_PYTORCH_VERSION
 from .utils.modeling import get_state_dict_offloaded_model
 from .utils.other import is_compiled_module
-from .utils import parallel_state as mpu
 
 
 if is_deepspeed_available():
diff --git a/src/accelerate/data_loader.py b/src/accelerate/data_loader.py
index f9f45ccf04b..a0396b16e51 100644
--- a/src/accelerate/data_loader.py
+++ b/src/accelerate/data_loader.py
@@ -17,7 +17,7 @@
 from typing import Callable, List, Optional, Union
 
 import torch
-from torch.utils.data import BatchSampler, DataLoader, IterableDataset, RandomSampler
+from torch.utils.data import BatchSampler, DataLoader, DistributedSampler, IterableDataset, RandomSampler
 
 from .logging import get_logger
 from .state import AcceleratorState, DistributedType, GradientState, is_torch_xla_available
@@ -34,7 +34,6 @@
     slice_tensors,
     synchronize_rng_states,
 )
-from torch.utils.data import DistributedSampler
 
 
 logger = get_logger(__name__)
@@ -942,7 +941,7 @@ def prepare_data_loader(
         generator = torch.Generator().manual_seed(42)
         dataloader.generator = generator
         dataloader.sampler.generator = generator
-    
+
     is_distributed_sampler = isinstance(
         dataloader.sampler.sampler if sampler_is_batch_sampler else dataloader.sampler,
         DistributedSampler
diff --git a/src/accelerate/utils/parallel_state.py b/src/accelerate/utils/parallel_state.py
index b7000cba489..f47f354329b 100644
--- a/src/accelerate/utils/parallel_state.py
+++ b/src/accelerate/utils/parallel_state.py
@@ -1,4 +1,6 @@
 # Copyright (c) 2022, NVIDIA CORPORATION. All rights reserved.
+from torch import distributed as dist
+
 
 """Model and data parallel groups."""
 
@@ -9,9 +11,8 @@
 
 
 # Intra-layer model parallel group that the current rank belongs to.
-import torch
-from torch import distributed as dist
-from typing import Optional
+
+
 _TENSOR_MODEL_PARALLEL_GROUP = None
 # Inter-layer model parallel group that the current rank belongs to.
 _PIPELINE_MODEL_PARALLEL_GROUP = None
@@ -165,7 +166,7 @@ def initialize_model_parallel(
 
     num_tensor_model_parallel_groups: int = world_size // tensor_model_parallel_size
     num_pipeline_model_parallel_groups: int = world_size // pipeline_model_parallel_size
-    num_data_parallel_groups: int = world_size // data_parallel_size
+    # num_data_parallel_groups: int = world_size // data_parallel_size
     num_sequence_parallel_groups: int = world_size // sequence_parallel_size
     num_sequence_data_parallel_groups: int = world_size // sequence_parallel_size // data_parallel_size
 
@@ -211,7 +212,7 @@ def initialize_model_parallel(
                 _DATA_PARALLEL_GROUP = group
                 _DATA_PARALLEL_GROUP_GLOO = group_gloo
                 _DATA_PARALLEL_GLOBAL_RANKS = ranks
-    
+
     global _DATA_PARALLEL_ALL_GROUP_RANKS
     _DATA_PARALLEL_ALL_GROUP_RANKS = all_data_parallel_group_ranks