fix: Avoid setting pin_memory in tests (deepmodeling#4919)

Avoid specifying pin_memory for test DataLoaders to eliminate warnings
when no accelerator is available.
deepmodeling#4874

<!-- This is an auto-generated comment: release notes by coderabbit.ai
-->

## Summary by CodeRabbit

* **Tests**
* Updated test configurations to rely on default memory pinning behavior
in data loading, improving compatibility across environments.
* Simplified test setup parameters to reduce potential flakiness and
align with framework defaults.

<!-- end of auto-generated comment: release notes by coderabbit.ai -->

Author: caic99

source/tests/pt/model/test_saveload_dpa1.py

@@ -69,7 +69,6 @@ def setUp(self) -> None:
             batch_size=None,
             num_workers=0,  # setting to 0 diverges the behavior of its iterator; should be >=1
             drop_last=False,
-            pin_memory=True,
         )
 
         def cycle_iterator(iterable):

source/tests/pt/model/test_saveload_se_e2_a.py

@@ -69,7 +69,6 @@ def setUp(self) -> None:
             batch_size=None,
             num_workers=0,  # setting to 0 diverges the behavior of its iterator; should be >=1
             drop_last=False,
-            pin_memory=True,
         )
 
         def cycle_iterator(iterable):

source/tests/pt/test_sampler.py

@@ -62,7 +62,6 @@ def test_sampler_debug_info(self) -> None:
             batch_size=None,
             num_workers=0,  # setting to 0 diverges the behavior of its iterator; should be >=1
             drop_last=False,
-            pin_memory=True,
         )
         with torch.device("cpu"):
             batch_data = next(iter(dataloader))