diff --git a/dalle2_pytorch/train_configs.py b/dalle2_pytorch/train_configs.py
index 6c5bee8..cc133fa 100644
--- a/dalle2_pytorch/train_configs.py
+++ b/dalle2_pytorch/train_configs.py
@@ -307,6 +307,7 @@ class DecoderTrainConfig(BaseModel):
     wd: SingularOrIterable[float] = 0.01
     warmup_steps: Optional[SingularOrIterable[int]] = None
     find_unused_parameters: bool = True
+    static_graph: bool = True
     max_grad_norm: SingularOrIterable[float] = 0.5
     save_every_n_samples: int = 100000
     n_sample_images: int = 6                       # The number of example images to produce when sampling the train and test dataset
diff --git a/train_decoder.py b/train_decoder.py
index a13bfaf..e2212c4 100644
--- a/train_decoder.py
+++ b/train_decoder.py
@@ -556,7 +556,7 @@ def initialize_training(config: TrainDecoderConfig, config_path):
     torch.manual_seed(config.seed)
 
     # Set up accelerator for configurable distributed training
-    ddp_kwargs = DistributedDataParallelKwargs(find_unused_parameters=config.train.find_unused_parameters)
+    ddp_kwargs = DistributedDataParallelKwargs(find_unused_parameters=config.train.find_unused_parameters, static_graph=config.train.static_graph)
     init_kwargs = InitProcessGroupKwargs(timeout=timedelta(seconds=60*60))
     accelerator = Accelerator(kwargs_handlers=[ddp_kwargs, init_kwargs])