FIX Cast to string _flatten_dict

CHANGELOG.md

@@ -30,6 +30,8 @@ The format is based on [Keep a Changelog](http://keepachangelog.com/en/1.0.0/).
 - Disabled checkpointing, earlystopping and logger with `fast_dev_run` ([#5277](https://github.com/PyTorchLightning/pytorch-lightning/pull/5277))
 
 
+- Fixed casted key to string in `_flatten_dict` ([#5354](https://github.com/PyTorchLightning/pytorch-lightning/pull/5354))
+
 
 ## [1.1.2] - 2020-12-23
 

pytorch_lightning/loggers/base.py

@@ -207,7 +207,7 @@ def _sanitize_callable(val):
         return {key: _sanitize_callable(val) for key, val in params.items()}
 
     @staticmethod
-    def _flatten_dict(params: Dict[str, Any], delimiter: str = '/') -> Dict[str, Any]:
+    def _flatten_dict(params: Dict[Any, Any], delimiter: str = '/') -> Dict[str, Any]:
         """
         Flatten hierarchical dict, e.g. ``{'a': {'b': 'c'}} -> {'a/b': 'c'}``.
 
@@ -223,12 +223,15 @@ def _flatten_dict(params: Dict[str, Any], delimiter: str = '/') -> Dict[str, Any
             {'a/b': 'c'}
             >>> LightningLoggerBase._flatten_dict({'a': {'b': 123}})
             {'a/b': 123}
+            >>> LightningLoggerBase._flatten_dict({5: {'a': 123}})
+            {'5/a': 123}
         """
 
         def _dict_generator(input_dict, prefixes=None):
             prefixes = prefixes[:] if prefixes else []
             if isinstance(input_dict, MutableMapping):
                 for key, value in input_dict.items():
+                    key = str(key)
                     if isinstance(value, (MutableMapping, Namespace)):
                         value = vars(value) if isinstance(value, Namespace) else value
                         for d in _dict_generator(value, prefixes + [key]):

tests/loggers/test_tensorboard.py

@@ -22,7 +22,7 @@
 from omegaconf import OmegaConf
 from tensorboard.backend.event_processing.event_accumulator import EventAccumulator
 
-from pytorch_lightning import Trainer, seed_everything
+from pytorch_lightning import seed_everything, Trainer
 from pytorch_lightning.loggers import TensorBoardLogger
 from tests.base import BoringModel, EvalModelTemplate
 
@@ -102,7 +102,7 @@ def test_tensorboard_named_version(tmpdir):
     expected_version = "2020-02-05-162402"
 
     logger = TensorBoardLogger(save_dir=tmpdir, name=name, version=expected_version)
-    logger.log_hyperparams({"a": 1, "b": 2})  # Force data to be written
+    logger.log_hyperparams({"a": 1, "b": 2, 123: 3, 3.5: 4, 5j: 5})  # Force data to be written
 
     assert logger.version == expected_version
     assert os.listdir(tmpdir / name) == [expected_version]
@@ -113,7 +113,7 @@ def test_tensorboard_named_version(tmpdir):
 def test_tensorboard_no_name(tmpdir, name):
     """Verify that None or empty name works"""
     logger = TensorBoardLogger(save_dir=tmpdir, name=name)
-    logger.log_hyperparams({"a": 1, "b": 2})  # Force data to be written
+    logger.log_hyperparams({"a": 1, "b": 2, 123: 3, 3.5: 4, 5j: 5})  # Force data to be written
     assert logger.root_dir == tmpdir
     assert os.listdir(tmpdir / "version_0")