Update default value for TorchCompileConfig to be None

Summary:
If we set dynamics to False, then automatic_dynamic_shapes will not take effect. This is not ideal because for sparse arch compilation, we expect that there are a number of dynamic shapes, if we do not apply automatic_dynamic_shapes, compiler will quit compilation after 8 trials.

Thus, we change it to None in this diff which is also the default setting for `torch.compile`:

https://www.internalfb.com/code/fbsource/[08c8192803b22f831329c8f736a3f7c6093ea4a8]/fbcode/caffe2/torch/__init__.py?lines=2321

Differential Revision: D63476875

torchrec/distributed/train_pipeline/train_pipelines.py

@@ -84,15 +84,15 @@ class TorchCompileConfig:
     Configs for torch.compile
 
     fullgraph: bool = False, whether to compile the whole graph or not
-    dynamic: bool = False, whether to use dynamic shapes or not
+    dynamic: Optional[bool] = None, whether to use dynamic shapes or not, if None, automatic_dynamic_shapes will apply
     backend: str = "inductor", which compiler to use (either inductor or aot)
     compile_on_iter: int = 3, compile the model on which iteration
         this is useful when we want to profile the first few iterations of training
         and then start using compiled model from iteration #3 onwards
     """
 
     fullgraph: bool = False
-    dynamic: bool = False
+    dynamic: Optional[bool] = None
     backend: str = "inductor"
     compile_on_iter: int = 3