Support hierarchical dict (#1152)

* Add support for hierarchical dict

* Support nested Namespace

* Add docstring

* Migrate hparam flattening to each logger

* Modify URLs in CHANGELOG

* typo

* Simplify the conditional branch about Namespace

Co-Authored-By: Jirka Borovec <Borda@users.noreply.github.com>

* Update CHANGELOG.md

Co-Authored-By: Jirka Borovec <Borda@users.noreply.github.com>

* added examples section to docstring

* renamed _dict -> input_dict

Co-authored-by: Jirka Borovec <Borda@users.noreply.github.com>

CHANGELOG.md

@@ -8,6 +8,7 @@ The format is based on [Keep a Changelog](http://keepachangelog.com/en/1.0.0/).
 
 ### Added
 
+- Added support for hierarchical `dict` ([#1152](https://github.com/PyTorchLightning/pytorch-lightning/pull/1152))
 - Added `TrainsLogger` class ([#1122](https://github.com/PyTorchLightning/pytorch-lightning/pull/1122))
 - Added type hints to `pytorch_lightning.core` ([#946](https://github.com/PyTorchLightning/pytorch-lightning/pull/946))
 - Added support for IterableDataset in validation and testing ([#1104](https://github.com/PyTorchLightning/pytorch-lightning/pull/1104))

pytorch_lightning/loggers/base.py

@@ -53,6 +53,39 @@ class LightningLoggerBase(ABC):
 
         return params
 
+    @staticmethod
+    def _flatten_dict(params: Dict[str, Any], delimiter: str = '/') -> Dict[str, Any]:
+        """Flatten hierarchical dict e.g. {'a': {'b': 'c'}} -> {'a/b': 'c'}.
+
+        Args:
+            params: Dictionary contains hparams
+            delimiter: Delimiter to express the hierarchy. Defaults to '/'.
+
+        Returns:
+            Flatten dict.
+
+        Examples:
+            >>> LightningLoggerBase._flatten_dict({'a': {'b': 'c'}})
+            {'a/b': 'c'}
+            >>> LightningLoggerBase._flatten_dict({'a': {'b': 123}})
+            {'a/b': 123}
+        """
+
+        def _dict_generator(input_dict, prefixes=None):
+            prefixes = prefixes[:] if prefixes else []
+            if isinstance(input_dict, dict):
+                for key, value in input_dict.items():
+                    if isinstance(value, (dict, Namespace)):
+                        value = vars(value) if isinstance(value, Namespace) else value
+                        for d in _dict_generator(value, prefixes + [key]):
+                            yield d
+                    else:
+                        yield prefixes + [key, value if value is not None else str(None)]
+            else:
+                yield prefixes + [input_dict if input_dict is None else str(input_dict)]
+
+        return {delimiter.join(keys): val for *keys, val in _dict_generator(params)}
+
     @staticmethod
     def _sanitize_params(params: Dict[str, Any]) -> Dict[str, Any]:
         """Returns params with non-primitvies converted to strings for logging

pytorch_lightning/loggers/comet.py

@@ -163,6 +163,7 @@ class CometLogger(LightningLoggerBase):
     @rank_zero_only
     def log_hyperparams(self, params: Union[Dict[str, Any], Namespace]) -> None:
         params = self._convert_params(params)
+        params = self._flatten_dict(params)
         self.experiment.log_parameters(params)
 
     @rank_zero_only

pytorch_lightning/loggers/mlflow.py

@@ -89,6 +89,7 @@ class MLFlowLogger(LightningLoggerBase):
     @rank_zero_only
     def log_hyperparams(self, params: Union[Dict[str, Any], Namespace]) -> None:
         params = self._convert_params(params)
+        params = self._flatten_dict(params)
         for k, v in params.items():
             self.experiment.log_param(self.run_id, k, v)
 

pytorch_lightning/loggers/neptune.py

@@ -222,6 +222,7 @@ class NeptuneLogger(LightningLoggerBase):
     @rank_zero_only
     def log_hyperparams(self, params: Union[Dict[str, Any], Namespace]) -> None:
         params = self._convert_params(params)
+        params = self._flatten_dict(params)
         for key, val in params.items():
             self.experiment.set_property(f'param__{key}', val)
 

pytorch_lightning/loggers/tensorboard.py

@@ -99,6 +99,7 @@ class TensorBoardLogger(LightningLoggerBase):
     @rank_zero_only
     def log_hyperparams(self, params: Union[Dict[str, Any], Namespace]) -> None:
         params = self._convert_params(params)
+        params = self._flatten_dict(params)
         sanitized_params = self._sanitize_params(params)
 
         if parse_version(torch.__version__) < parse_version("1.3.0"):

pytorch_lightning/loggers/test_tube.py

@@ -96,6 +96,7 @@ class TestTubeLogger(LightningLoggerBase):
         # TODO: HACK figure out where this is being set to true
         self.experiment.debug = self.debug
         params = self._convert_params(params)
+        params = self._flatten_dict(params)
         self.experiment.argparse(Namespace(**params))
 
     @rank_zero_only

pytorch_lightning/loggers/trains.py

@@ -130,10 +130,10 @@ class TrainsLogger(LightningLoggerBase):
             return None
         if not params:
             return
-        if isinstance(params, dict):
-            self._trains.connect(params)
-        else:
-            self._trains.connect(vars(params))
+
+        params = self._convert_params(params)
+        params = self._flatten_dict(params)
+        self._trains.connect(params)
 
     @rank_zero_only
     def log_metrics(self, metrics: Dict[str, float], step: Optional[int] = None) -> None:

tests/loggers/test_tensorboard.py

@@ -108,8 +108,9 @@ def test_tensorboard_log_hyperparams(tmpdir):
         "int": 1,
         "string": "abc",
         "bool": True,
+        "dict": {'a': {'b': 'c'}},
         "list": [1, 2, 3],
-        "namespace": Namespace(foo=3),
+        "namespace": Namespace(foo=Namespace(bar='buzz')),
         "layer": torch.nn.BatchNorm1d
     }
     logger.log_hyperparams(hparams)