only sync seed during training

Author: lucidrains

pyproject.toml

@@ -1,6 +1,6 @@
 [project]
 name = "vector-quantize-pytorch"
-version = "1.19.2"
+version = "1.19.3"
 description = "Vector Quantization - Pytorch"
 authors = [
     { name = "Phil Wang", email = "lucidrains@gmail.com" }

vector_quantize_pytorch/residual_fsq.py

@@ -305,7 +305,7 @@ def forward(
 
         forward_kwargs = dict(
             return_all_codes = return_all_codes,
-            rand_quantize_dropout_fixed_seed = get_maybe_sync_seed(device)
+            rand_quantize_dropout_fixed_seed = get_maybe_sync_seed(device) if self.training else None
         )
 
         # invoke residual vq on each group

vector_quantize_pytorch/residual_lfq.py

@@ -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(device)
+            rand_quantize_dropout_fixed_seed = get_maybe_sync_seed(device) if self.training else None
         )
 
         # invoke residual vq on each group

vector_quantize_pytorch/residual_vq.py

@@ -328,7 +328,6 @@ def forward(
 
             rand = random.Random(rand_quantize_dropout_fixed_seed)
 
-
             rand_quantize_dropout_index = rand.randrange(self.quantize_dropout_cutoff_index, num_quant)
 
             if quant_dropout_multiple_of != 1:
@@ -496,7 +495,7 @@ def forward(
             sample_codebook_temp = sample_codebook_temp,
             mask = mask,
             freeze_codebook = freeze_codebook,
-            rand_quantize_dropout_fixed_seed = get_maybe_sync_seed(device)
+            rand_quantize_dropout_fixed_seed = get_maybe_sync_seed(device) if self.training else None
         )
 
         # invoke residual vq on each group