Add some helpful debugging notes to TROUBLESHOOTING docs

TROUBLESHOOTING.md

@@ -285,6 +285,11 @@ We don't expect users to use tools in this section to debug their models. But we
 them when you submit a bug report since they provide additional information that metrics report
 doesn't have.
 
+* ```print(torch_xla._XLAC._get_xla_tensors_text([res]))``` where `res` is the result tensor prints out the IR.
+* ```print(torch_xla._XLAC._get_xla_tensors_hlo([res]))``` where `res` is the result tensor prints out the generated XLA HLO.
+
+Note these functions must be called prior to `mark_step()`, otherwise the tensor will already be materialized.
+
 ### Environment Variables
 
 There are also a number of environment variables which control the behavior of the _PyTorch/XLA_
@@ -371,3 +376,16 @@ only be enabled for debugging.
   ```
   TF_CPP_MIN_LOG_LEVEL=0 TF_CPP_VMODULE="xla_graph_executor=5,pjrt_computation_client=3"
   ```
+
+### Reproducing PyTorch/XLA CI/CD unit test failures.
+
+You may see some test failures for a PR such as:
+
+```
+To execute this test, run the following from the base repo dir:
+    PYTORCH_TEST_WITH_SLOW=1 python ../test/test_torch.py -k test_put_xla_uint8
+```
+
+Running this directly in the command line does not work. You need to set the environment variable `TORCH_TEST_DEVICES` to your local `pytorch/xla/test/pytorch_test_base.py`. For example:
+
+`TORCH_TEST_DEVICES='/path/to/pytorch/xla/test/pytorch_test_base.py PYTORCH_TEST_WITH_SLOW=1 python ../test/test_torch.py -k test_put_xla_uint8` should work.