-- Added seed_everything

-- updated history

Author: manujosephv

docs/history.md

@@ -29,3 +29,12 @@ History
 ------------------
 -   Added more documentation
 -   Added Zenodo citation
+
+0.6.0 (2021-06-21)
+------------------
+-   Upgraded versions of PyTorch Lightning to 1.3.6
+-   Changed the way `gpus` parameter is handled to avoid confusion. `None` is CPU, `-1` is all GPUs, `int` is number of GPUs
+-   Added a few more Trainer Params like `deterministic`, `auto_select_gpus`
+-   Some bug fixes and changes to docs
+-   Added `seed_everything` to the fit method to ensure reproducibility
+-   Refactored data_aware_initialization to be part of the BaseModel. Inherited Models can override the method to implement data aware initialization techniques

pytorch_tabular/config/config.py

@@ -576,6 +576,12 @@ class ModelConfig:
             "help": "The range in which we should limit the output variable. Currently ignored for multi-target regression. Typically used for Regression problems. If left empty, will not apply any restrictions"
         },
     )
+    seed: int = field(
+        default=42,
+        metadata={
+            "help": "The seed for reproducibility. Defaults to 42"
+        },
+    )
 
     def __post_init__(self):
         if self.task == "regression":

pytorch_tabular/tabular_model.py

@@ -3,6 +3,7 @@
 # For license information, see LICENSE.TXT
 """Tabular Model"""
 from collections import defaultdict
+from pytorch_lightning.utilities.seed import seed_everything
 import logging
 import os
 from typing import Callable, Dict, Iterable, List, Optional, Tuple, Union
@@ -19,6 +20,7 @@
 from sklearn.base import TransformerMixin
 from torch import nn
 from tqdm.autonotebook import tqdm
+from pytorch_tabular import config
 
 import pytorch_tabular.models as models
 from pytorch_tabular.config import (
@@ -335,7 +337,7 @@ def _pre_fit(
         target_transform: Optional[Union[TransformerMixin, Tuple]],
         max_epochs: int,
         min_epochs: int,
-        reset: bool,
+        reset: bool
     ):
         """Prepares the dataloaders, trainer, and model for the fit process"""
         if target_transform is not None:
@@ -381,6 +383,7 @@ def fit(
         max_epochs: Optional[int] = None,
         min_epochs: Optional[int] = None,
         reset: bool = False,
+        seed: Optional[int] = None,
     ) -> None:
         """The fit method which takes in the data and triggers the training
 
@@ -414,7 +417,10 @@ def fit(
             min_epochs (Optional[int]): Overwrite minimum number of epochs to be run
 
             reset: (bool): Flag to reset the model and train again from scratch
+
+            seed: (int): If you have to override the default seed set as part of of ModelConfig
         """
+        seed_everything(seed if seed is not None else self.config.seed)
         train_loader, val_loader = self._pre_fit(
             train,
             validation,