fix loggers error

Author: deependujha

tests/tests_pytorch/conftest.py

@@ -265,6 +265,11 @@ def xla_available(monkeypatch: pytest.MonkeyPatch) -> None:
     mock_xla_available(monkeypatch)
 
 
+@pytest.fixture
+def xla_not_available(monkeypatch: pytest.MonkeyPatch) -> None:
+    mock_xla_available(monkeypatch, False)
+
+
 def mock_tpu_available(monkeypatch: pytest.MonkeyPatch, value: bool = True) -> None:
     mock_xla_available(monkeypatch, value)
     monkeypatch.setattr(lightning.fabric.accelerators.xla.XLAAccelerator, "is_available", lambda: value)

tests/tests_pytorch/graveyard/test_tpu.py

@@ -35,7 +35,7 @@ def test_graveyard_single_tpu(import_path, name):
         ("lightning.pytorch.plugins.precision.xlabf16", "XLABf16PrecisionPlugin"),
     ],
 )
-def test_graveyard_no_device(import_path, name):
+def test_graveyard_no_device(import_path, name, xla_not_available):
     module = import_module(import_path)
     cls = getattr(module, name)
     with pytest.deprecated_call(match="is deprecated"), pytest.raises(ModuleNotFoundError, match="torch_xla"):

tests/tests_pytorch/loggers/test_all.py

@@ -107,8 +107,9 @@ def log_metrics(self, metrics, step):
 
     if logger_class == CometLogger:
         logger.experiment.id = "foo"
-        logger._comet_config.offline_directory = None
-        logger._project_name = "bar"
+        # TODO: Verify with @justusschock if this is accepted approach to test experiment creation
+        logger.logger_impl._comet_config.offline_directory = None
+        logger.logger_impl._project_name = "bar"
         logger.experiment.get_key.return_value = "SOME_KEY"
 
     if logger_class == NeptuneLogger:
@@ -358,6 +359,7 @@ def test_logger_default_name(mlflow_mock, monkeypatch, tmp_path):
     logger = _instantiate_logger(MLFlowLogger, save_dir=tmp_path)
 
     _ = logger.experiment
-    logger._mlflow_client.create_experiment.assert_called_with(name="lightning_logs", artifact_location=ANY)
+    # TODO: Verify with @justusschock if this is accepted approach to test experiment creation
+    logger.logger_impl._mlflow_client.create_experiment.assert_called_with(name="lightning_logs", artifact_location=ANY)
     # on MLFLowLogger `name` refers to the experiment id
     # assert logger.experiment.get_experiment(logger.name).name == "lightning_logs"

tests/tests_pytorch/trainer/connectors/test_accelerator_connector.py

@@ -20,6 +20,7 @@
 from unittest.mock import Mock
 
 import pytest
+import pytorch_lightning_enterprise.plugins.precision.bitsandbytes
 import torch
 import torch.distributed
 
@@ -968,6 +969,7 @@ def test_precision_selection(precision_str, strategy_str, expected_precision_cls
 
 def test_bitsandbytes_precision_cuda_required(monkeypatch):
     monkeypatch.setattr(lightning.fabric.plugins.precision.bitsandbytes, "_BITSANDBYTES_AVAILABLE", True)
+    monkeypatch.setattr(pytorch_lightning_enterprise.plugins.precision.bitsandbytes, "_BITSANDBYTES_AVAILABLE", True)
     monkeypatch.setitem(sys.modules, "bitsandbytes", Mock())
     with pytest.raises(RuntimeError, match="Bitsandbytes is only supported on CUDA GPUs"):
         _AcceleratorConnector(accelerator="cpu", plugins=BitsandbytesPrecision(mode="int8"))