diff --git a/pyproject.toml b/pyproject.toml
index 11bb3d1..364efe5 100644
--- a/pyproject.toml
+++ b/pyproject.toml
@@ -1,6 +1,6 @@
 [project]
 name = "vector-quantize-pytorch"
-version = "1.18.7"
+version = "1.18.8"
 description = "Vector Quantization - Pytorch"
 authors = [
     { name = "Phil Wang", email = "lucidrains@gmail.com" }
diff --git a/vector_quantize_pytorch/residual_fsq.py b/vector_quantize_pytorch/residual_fsq.py
index d57b594..a837f5d 100644
--- a/vector_quantize_pytorch/residual_fsq.py
+++ b/vector_quantize_pytorch/residual_fsq.py
@@ -185,7 +185,7 @@ def forward(
             # check if seed is manually passed in
 
             if not exists(rand_quantize_dropout_fixed_seed):
-                rand_quantize_dropout_fixed_seed = get_maybe_sync_seed()
+                rand_quantize_dropout_fixed_seed = get_maybe_sync_seed(device)
 
             rand = random.Random(rand_quantize_dropout_fixed_seed)
 
@@ -296,7 +296,7 @@ def forward(
         x,
         return_all_codes = False
     ):
-        shape, split_dim = x.shape, self.split_dim
+        shape, split_dim, device = x.shape, self.split_dim, x.device
         assert shape[split_dim] == self.dim
 
         # split the feature dimension into groups
@@ -305,7 +305,7 @@ def forward(
 
         forward_kwargs = dict(
             return_all_codes = return_all_codes,
-            rand_quantize_dropout_fixed_seed = get_maybe_sync_seed()
+            rand_quantize_dropout_fixed_seed = get_maybe_sync_seed(device)
         )
 
         # invoke residual vq on each group
diff --git a/vector_quantize_pytorch/residual_lfq.py b/vector_quantize_pytorch/residual_lfq.py
index 2ea6407..98bdc54 100644
--- a/vector_quantize_pytorch/residual_lfq.py
+++ b/vector_quantize_pytorch/residual_lfq.py
@@ -31,8 +31,8 @@ def round_up_multiple(num, mult):
 def is_distributed():
     return dist.is_initialized() and dist.get_world_size() > 1
 
-def get_maybe_sync_seed(max_size = 10_000):
-    rand_int = torch.randint(0, max_size, ())
+def get_maybe_sync_seed(device, max_size = 10_000):
+    rand_int = torch.randint(0, max_size, (), device = device)
 
     if is_distributed():
         dist.all_reduce(rand_int)
@@ -162,7 +162,7 @@ def forward(
             # check if seed is manually passed in
 
             if not exists(rand_quantize_dropout_fixed_seed):
-                rand_quantize_dropout_fixed_seed = get_maybe_sync_seed()
+                rand_quantize_dropout_fixed_seed = get_maybe_sync_seed(device)
 
             rand = random.Random(rand_quantize_dropout_fixed_seed)
 
@@ -262,7 +262,7 @@ def forward(
         mask = None,
         return_all_codes = False
     ):
-        shape, split_dim = x.shape, self.split_dim
+        shape, split_dim, device = x.shape, self.split_dim, x.device
         assert shape[split_dim] == self.dim
 
         # split the feature dimension into groups
@@ -272,7 +272,7 @@ def forward(
         forward_kwargs = dict(
             mask = mask,
             return_all_codes = return_all_codes,
-            rand_quantize_dropout_fixed_seed = get_maybe_sync_seed()
+            rand_quantize_dropout_fixed_seed = get_maybe_sync_seed(device)
         )
 
         # invoke residual vq on each group
diff --git a/vector_quantize_pytorch/residual_vq.py b/vector_quantize_pytorch/residual_vq.py
index 768ceab..3e70ae2 100644
--- a/vector_quantize_pytorch/residual_vq.py
+++ b/vector_quantize_pytorch/residual_vq.py
@@ -36,8 +36,8 @@ def round_up_multiple(num, mult):
 def is_distributed():
     return dist.is_initialized() and dist.get_world_size() > 1
 
-def get_maybe_sync_seed(max_size = 10_000):
-    rand_int = torch.randint(0, max_size, ())
+def get_maybe_sync_seed(device, max_size = 10_000):
+    rand_int = torch.randint(0, max_size, (), device = device)
 
     if is_distributed():
         dist.all_reduce(rand_int)
@@ -296,7 +296,7 @@ def forward(
             # check if seed is manually passed in
 
             if not exists(rand_quantize_dropout_fixed_seed):
-                rand_quantize_dropout_fixed_seed = get_maybe_sync_seed()
+                rand_quantize_dropout_fixed_seed = get_maybe_sync_seed(device)
 
             rand = random.Random(rand_quantize_dropout_fixed_seed)
 
@@ -452,7 +452,7 @@ def forward(
         freeze_codebook = False,
         mask = None,
     ):
-        shape, split_dim = x.shape, self.split_dim
+        shape, split_dim, device = x.shape, self.split_dim, x.device
         assert shape[split_dim] == self.dim
 
         # split the feature dimension into groups
@@ -468,7 +468,7 @@ def forward(
             sample_codebook_temp = sample_codebook_temp,
             mask = mask,
             freeze_codebook = freeze_codebook,
-            rand_quantize_dropout_fixed_seed = get_maybe_sync_seed()
+            rand_quantize_dropout_fixed_seed = get_maybe_sync_seed(device)
         )
 
         # invoke residual vq on each group