update

Author: justusschock

src/lightning/fabric/utilities/imports.py

@@ -41,6 +41,12 @@
 _TORCHMETRICS_GREATER_EQUAL_1_0_0 = compare_version("torchmetrics", operator.ge, "1.0.0")
 _PYTHON_GREATER_EQUAL_3_10_0 = (sys.version_info.major, sys.version_info.minor) >= (3, 10)
 
+_WANDB_AVAILABLE = RequirementCache("wandb>=0.12.10")
+_COMET_AVAILABLE = RequirementCache("comet-ml>=3.44.4")
+_MLFLOW_AVAILABLE = RequirementCache("mlflow>=1.0.0")
+_MLFLOW_SYNCHRONOUS_AVAILABLE = RequirementCache("mlflow>=2.8.0")
+_NEPTUNE_AVAILABLE = RequirementCache("neptune>=1.0")
+
 _DEEPSPEED_AVAILABLE = RequirementCache("deepspeed")
 _DEEPSPEED_GREATER_EQUAL_0_16 = RequirementCache("deepspeed>=0.16.0")
 _ENTERPRISE_AVAILABLE = RequirementCache("pytorch_lightning_enterprise")

src/lightning/pytorch/plugins/precision/deepspeed.py

@@ -43,7 +43,7 @@ class DeepSpeedPrecision(Precision):
     """
 
     def __init__(self, precision: _PRECISION_INPUT) -> None:
-        super().__init__(precision)
+        super().__init__()
         _raise_enterprise_not_available()
         from pytorch_lightning_enterprise.plugins.precision.deepspeed import (
             DeepSpeedPrecisionTrainer as EnterpriseDeepSpeedPrecision,

src/lightning/pytorch/utilities/deepspeed.py

@@ -20,8 +20,8 @@
 
 import torch
 
+from lightning.fabric.utilities.imports import _DEEPSPEED_AVAILABLE
 from lightning.fabric.utilities.types import _PATH
-from lightning.pytorch.strategies.deepspeed import _DEEPSPEED_AVAILABLE
 
 CPU_DEVICE = torch.device("cpu")
 

tests/tests_pytorch/loggers/test_mlflow.py

@@ -17,12 +17,11 @@
 
 import pytest
 
+from lightning.fabric.utilities.imports import _MLFLOW_AVAILABLE
 from lightning.pytorch import Trainer
 from lightning.pytorch.demos.boring_classes import BoringModel
 from lightning.pytorch.loggers.mlflow import (
-    _MLFLOW_AVAILABLE,
     MLFlowLogger,
-    _get_resolve_tags,
 )
 
 
@@ -96,6 +95,7 @@ def test_mlflow_run_name_setting(tmp_path):
         pytest.skip("test for explicit file creation requires mlflow dependency to be installed.")
 
     from mlflow.utils.mlflow_tags import MLFLOW_RUN_NAME
+    from pytorch_lightning_enterprise.loggers.mlflow import _get_resolve_tags
 
     resolve_tags = _get_resolve_tags()
     tags = resolve_tags({MLFLOW_RUN_NAME: "run-name-1"})