remove frame inspection on self.hparams (#2253)

* remove frame inspection on self.hparams

* remove frame inspection on self.hparams

* remove frame inspection on self.hparams

* remove frame inspection on self.hparams

* remove frame inspection on self.hparams

* remove frame inspection on self.hparams

pytorch_lightning/core/lightning.py

@@ -1,6 +1,7 @@
 import collections
 import inspect
 import os
+import re
 from abc import ABC, abstractmethod
 from argparse import Namespace
 from typing import Any, Callable, Dict, List, Optional, Tuple, Union, Sequence
@@ -1692,4 +1693,20 @@ class LightningModule(ABC, DeviceDtypeModuleMixin, GradInformation, ModelIO, Mod
 
     @hparams.setter
     def hparams(self, hp: Union[dict, Namespace, Any]):
-        self.save_hyperparameters(hp, frame=inspect.currentframe().f_back.f_back)
+        hparams_assignment_name = self.__get_hparams_assignment_variable()
+        self._hparams_name = hparams_assignment_name
+        self._set_hparams(hp)
+
+    def __get_hparams_assignment_variable(self):
+        """
+        looks at the code of the class to figure out what the user named self.hparams
+        this only happens when the user explicitly sets self.hparams
+        """
+        class_code = inspect.getsource(self.__class__)
+        lines = class_code.split('\n')
+        for line in lines:
+            line = re.sub(r"\s+", "", line, flags=re.UNICODE)
+            if 'self.hparams=' in line:
+                return line.split('=')[1]
+
+        return None

pytorch_lightning/core/saving.py

@@ -176,14 +176,18 @@ class ModelIO(object):
         # pass in the values we saved automatically
         if cls.CHECKPOINT_HYPER_PARAMS_KEY in checkpoint:
             model_args = {}
+
             # add some back compatibility, the actual one shall be last
             for hparam_key in CHECKPOINT_PAST_HPARAMS_KEYS + (cls.CHECKPOINT_HYPER_PARAMS_KEY,):
                 if hparam_key in checkpoint:
                     model_args.update(checkpoint[hparam_key])
+
             if cls.CHECKPOINT_HYPER_PARAMS_TYPE in checkpoint:
                 model_args = checkpoint[cls.CHECKPOINT_HYPER_PARAMS_TYPE](model_args)
+
             args_name = checkpoint.get(cls.CHECKPOINT_HYPER_PARAMS_NAME)
             init_args_name = inspect.signature(cls).parameters.keys()
+
             if args_name == 'kwargs':
                 cls_kwargs = {k: v for k, v in model_args.items() if k in init_args_name}
                 kwargs.update(**cls_kwargs)

tests/models/test_hparams.py

@@ -39,7 +39,7 @@ def _run_standard_hparams_test(tmpdir, model, cls, try_overwrite=False):
     assert model.hparams.test_arg == 14
 
     # verify we can train
-    trainer = Trainer(default_root_dir=tmpdir, max_epochs=1, overfit_batches=0.5)
+    trainer = Trainer(default_root_dir=tmpdir, max_epochs=1, overfit_batches=2)
     trainer.fit(model)
 
     # make sure the raw checkpoint saved the properties