Do not warn on jax usage when workarounds are available

torch_xla/_internal/jax_workarounds.py

@@ -58,7 +58,7 @@ def maybe_get_torchax():
     return None
 
 
-def maybe_get_jax():
+def maybe_get_jax(log=True):
   try:
     jax_import_guard()
     with jax_env_context():
@@ -67,6 +67,8 @@ def maybe_get_jax():
       jax.config.update('jax_use_shardy_partitioner', False)
       return jax
   except (ModuleNotFoundError, ImportError):
-    logging.warn('You are trying to use a feature that requires jax/pallas.'
-                 'You can install Jax/Pallas via pip install torch_xla[pallas]')
-    return None
+    if log:
+      logging.warning(
+          'You are trying to use a feature that requires jax/pallas.'
+          'You can install Jax/Pallas via pip install torch_xla[pallas]')
+    return None

torch_xla/debug/profiler.py

@@ -131,7 +131,7 @@ def __enter__(self):
 
     self._jax_scope = None
     # Also enter the JAX named scope, to support torchax lowering.
-    if jax := maybe_get_jax():
+    if jax := maybe_get_jax(log=False):
       self._jax_scope = jax.named_scope(self.name)
       self._jax_scope.__enter__()
 

torch_xla/distributed/spmd/xla_sharding.py

@@ -646,7 +646,8 @@ def mark_sharding(t: Union[torch.Tensor, XLAShardedTensor], mesh: Mesh,
     f"Partition spec length ({len(partition_spec)}) should be equal to the input rank ({len(t.shape)})."
 
   tx = maybe_get_torchax()
-  jax = maybe_get_jax()
+  # Do not log jax warnings when workarounds are available.
+  jax = maybe_get_jax(log=False)
   if (jax is not None) and (tx is not None) and isinstance(t, tx.tensor.Tensor):
     from jax.sharding import PartitionSpec as P, NamedSharding
     jmesh = mesh.get_jax_mesh()