Fix inspection of unspecified args for container hparams (#9125)

* Update parsing.py

* add todo (for single arg)

* unblock non container single arg

* init test

* [pre-commit.ci] auto fixes from pre-commit.com hooks

for more information, see https://pre-commit.ci

* Update CHANGELOG.md

* pep8 line length

* Update pytorch_lightning/utilities/parsing.py

* remove dict namespace conversion

* add omegaconf support

* [pre-commit.ci] auto fixes from pre-commit.com hooks

for more information, see https://pre-commit.ci

* add dict test

* [pre-commit.ci] auto fixes from pre-commit.com hooks

for more information, see https://pre-commit.ci

* add omegaconf test

* Update CHANGELOG.md

* Update pytorch_lightning/utilities/parsing.py

Co-authored-by: Jirka Borovec <[email protected]>

* Update pytorch_lightning/utilities/parsing.py

Co-authored-by: Jirka Borovec <[email protected]>

Co-authored-by: pre-commit-ci[bot] <66853113+pre-commit-ci[bot]@users.noreply.github.com>
Co-authored-by: Jirka Borovec <[email protected]>

Author: 3 people

CHANGELOG.md

@@ -37,6 +37,8 @@ The format is based on [Keep a Changelog](http://keepachangelog.com/en/1.0.0/).
 - Fixed error handling in DDP process reconciliation when `_sync_dir` was not initialized ([#9267](https://github.com/PyTorchLightning/pytorch-lightning/pull/9267))
 
 
+- Fixed inspection of other args when a container is specified in `save_hyperparameters` ([#9125](https://github.com/PyTorchLightning/pytorch-lightning/pull/9125))
+
 ## [1.4.5] - 2021-08-31
 
 - Fixed reduction using `self.log(sync_dict=True, reduce_fx={mean,max})` ([#9142](https://github.com/PyTorchLightning/pytorch-lightning/pull/9142))

pytorch_lightning/utilities/parsing.py

@@ -22,8 +22,12 @@
 from typing_extensions import Literal
 
 import pytorch_lightning as pl
+from pytorch_lightning.utilities import _OMEGACONF_AVAILABLE
 from pytorch_lightning.utilities.warnings import rank_zero_warn
 
+if _OMEGACONF_AVAILABLE:
+    from omegaconf.dictconfig import DictConfig
+
 
 def str_to_bool_or_str(val: str) -> Union[str, bool]:
     """Possibly convert a string representation of truth to bool.
@@ -204,46 +208,57 @@ def save_hyperparameters(
     obj: Any, *args: Any, ignore: Optional[Union[Sequence[str], str]] = None, frame: Optional[types.FrameType] = None
 ) -> None:
     """See :meth:`~pytorch_lightning.LightningModule.save_hyperparameters`"""
-
+    hparams_container_types = [Namespace, dict]
+    if _OMEGACONF_AVAILABLE:
+        hparams_container_types.append(DictConfig)
+    # empty container
     if len(args) == 1 and not isinstance(args, str) and not args[0]:
-        # args[0] is an empty container
         return
-
-    if not frame:
-        current_frame = inspect.currentframe()
-        # inspect.currentframe() return type is Optional[types.FrameType]: current_frame.f_back called only if available
-        if current_frame:
-            frame = current_frame.f_back
-    if not isinstance(frame, types.FrameType):
-        raise AttributeError("There is no `frame` available while being required.")
-
-    if is_dataclass(obj):
-        init_args = {f.name: getattr(obj, f.name) for f in fields(obj)}
-    else:
-        init_args = get_init_args(frame)
-    assert init_args, "failed to inspect the obj init"
-
-    if ignore is not None:
-        if isinstance(ignore, str):
-            ignore = [ignore]
-        if isinstance(ignore, (list, tuple)):
-            ignore = [arg for arg in ignore if isinstance(arg, str)]
-        init_args = {k: v for k, v in init_args.items() if k not in ignore}
-
-    if not args:
-        # take all arguments
-        hp = init_args
-        obj._hparams_name = "kwargs" if hp else None
+    # container
+    elif len(args) == 1 and isinstance(args[0], tuple(hparams_container_types)):
+        hp = args[0]
+        obj._hparams_name = "hparams"
+        obj._set_hparams(hp)
+        obj._hparams_initial = copy.deepcopy(obj._hparams)
+        return
+    # non-container args parsing
     else:
-        # take only listed arguments in `save_hparams`
-        isx_non_str = [i for i, arg in enumerate(args) if not isinstance(arg, str)]
-        if len(isx_non_str) == 1:
-            hp = args[isx_non_str[0]]
-            cand_names = [k for k, v in init_args.items() if v == hp]
-            obj._hparams_name = cand_names[0] if cand_names else None
+        if not frame:
+            current_frame = inspect.currentframe()
+            # inspect.currentframe() return type is Optional[types.FrameType]
+            # current_frame.f_back called only if available
+            if current_frame:
+                frame = current_frame.f_back
+        if not isinstance(frame, types.FrameType):
+            raise AttributeError("There is no `frame` available while being required.")
+
+        if is_dataclass(obj):
+            init_args = {f.name: getattr(obj, f.name) for f in fields(obj)}
+        else:
+            init_args = get_init_args(frame)
+        assert init_args, f"failed to inspect the obj init - {frame}"
+
+        if ignore is not None:
+            if isinstance(ignore, str):
+                ignore = [ignore]
+            if isinstance(ignore, (list, tuple, set)):
+                ignore = [arg for arg in ignore if isinstance(arg, str)]
+            init_args = {k: v for k, v in init_args.items() if k not in ignore}
+
+        if not args:
+            # take all arguments
+            hp = init_args
+            obj._hparams_name = "kwargs" if hp else None
         else:
-            hp = {arg: init_args[arg] for arg in args if isinstance(arg, str)}
-            obj._hparams_name = "kwargs"
+            # take only listed arguments in `save_hparams`
+            isx_non_str = [i for i, arg in enumerate(args) if not isinstance(arg, str)]
+            if len(isx_non_str) == 1:
+                hp = args[isx_non_str[0]]
+                cand_names = [k for k, v in init_args.items() if v == hp]
+                obj._hparams_name = cand_names[0] if cand_names else None
+            else:
+                hp = {arg: init_args[arg] for arg in args if isinstance(arg, str)}
+                obj._hparams_name = "kwargs"
 
     # `hparams` are expected here
     if hp:

tests/core/test_datamodules.py

@@ -12,17 +12,20 @@
 # See the License for the specific language governing permissions and
 # limitations under the License.
 import pickle
-from argparse import ArgumentParser
+from argparse import ArgumentParser, Namespace
+from dataclasses import dataclass
 from typing import Any, Dict
 from unittest import mock
 from unittest.mock import call, PropertyMock
 
 import pytest
 import torch
+from omegaconf import OmegaConf
 
 from pytorch_lightning import LightningDataModule, Trainer
 from pytorch_lightning.callbacks import ModelCheckpoint
 from pytorch_lightning.utilities import AttributeDict
+from pytorch_lightning.utilities.exceptions import MisconfigurationException
 from pytorch_lightning.utilities.model_helpers import is_overridden
 from tests.helpers import BoringDataModule, BoringModel
 from tests.helpers.datamodules import ClassifDataModule
@@ -532,12 +535,101 @@ def test_dm_init_from_datasets_dataloaders(iterable):
         )
 
 
-class DataModuleWithHparams(LightningDataModule):
+# all args
+class DataModuleWithHparams_0(LightningDataModule):
     def __init__(self, arg0, arg1, kwarg0=None):
         super().__init__()
         self.save_hyperparameters()
 
 
-def test_simple_hyperparameters_saving():
-    data = DataModuleWithHparams(10, "foo", kwarg0="bar")
+# single arg
+class DataModuleWithHparams_1(LightningDataModule):
+    def __init__(self, arg0, *args, **kwargs):
+        super().__init__()
+        self.save_hyperparameters(arg0)
+
+
+def test_hyperparameters_saving():
+    data = DataModuleWithHparams_0(10, "foo", kwarg0="bar")
     assert data.hparams == AttributeDict({"arg0": 10, "arg1": "foo", "kwarg0": "bar"})
+
+    data = DataModuleWithHparams_1(Namespace(**{"hello": "world"}), "foo", kwarg0="bar")
+    assert data.hparams == AttributeDict({"hello": "world"})
+
+    data = DataModuleWithHparams_1({"hello": "world"}, "foo", kwarg0="bar")
+    assert data.hparams == AttributeDict({"hello": "world"})
+
+    data = DataModuleWithHparams_1(OmegaConf.create({"hello": "world"}), "foo", kwarg0="bar")
+    assert data.hparams == OmegaConf.create({"hello": "world"})
+
+
+def test_define_as_dataclass():
+    # makes sure that no functionality is broken and the user can still manually make
+    # super().__init__ call with parameters
+    # also tests all the dataclass features that can be enabled without breaking anything
+    @dataclass(init=True, repr=True, eq=True, order=True, unsafe_hash=True, frozen=False)
+    class BoringDataModule1(LightningDataModule):
+        batch_size: int
+        dims: int = 2
+
+        def __post_init__(self):
+            super().__init__(dims=self.dims)
+
+    # asserts for the different dunder methods added by dataclass, when __init__ is implemented, i.e.
+    # __repr__, __eq__, __lt__, __le__, etc.
+    assert BoringDataModule1(batch_size=64).dims == 2
+    assert BoringDataModule1(batch_size=32)
+    assert hasattr(BoringDataModule1, "__repr__")
+    assert BoringDataModule1(batch_size=32) == BoringDataModule1(batch_size=32)
+
+    # asserts inherent calling of super().__init__ in case user doesn't make the call
+    @dataclass
+    class BoringDataModule2(LightningDataModule):
+        batch_size: int
+
+    # asserts for the different dunder methods added by dataclass, when super class is inherently initialized, i.e.
+    # __init__, __repr__, __eq__, __lt__, __le__, etc.
+    assert BoringDataModule2(batch_size=32)
+    assert hasattr(BoringDataModule2, "__repr__")
+    assert BoringDataModule2(batch_size=32).prepare_data() is None
+    assert BoringDataModule2(batch_size=32) == BoringDataModule2(batch_size=32)
+
+    # checking for all the different multilevel inhertiance scenarios, for init call on LightningDataModule
+    @dataclass
+    class BoringModuleBase1(LightningDataModule):
+        num_features: int
+
+    class BoringModuleBase2(LightningDataModule):
+        def __init__(self, num_features: int):
+            self.num_features = num_features
+
+    @dataclass
+    class BoringModuleDerived1(BoringModuleBase1):
+        ...
+
+    class BoringModuleDerived2(BoringModuleBase1):
+        def __init__(self):
+            ...
+
+    @dataclass
+    class BoringModuleDerived3(BoringModuleBase2):
+        ...
+
+    class BoringModuleDerived4(BoringModuleBase2):
+        def __init__(self):
+            ...
+
+    assert hasattr(BoringModuleDerived1(num_features=2), "_has_prepared_data")
+    assert hasattr(BoringModuleDerived2(), "_has_prepared_data")
+    assert hasattr(BoringModuleDerived3(), "_has_prepared_data")
+    assert hasattr(BoringModuleDerived4(), "_has_prepared_data")
+
+
+def test_inconsistent_prepare_data_per_node(tmpdir):
+    with pytest.raises(MisconfigurationException, match="Inconsistent settings found for `prepare_data_per_node`."):
+        model = BoringModel()
+        dm = BoringDataModule()
+        trainer = Trainer(prepare_data_per_node=False)
+        trainer.model = model
+        trainer.datamodule = dm
+        trainer.data_connector.prepare_data()