get help from docstring

CHANGELOG.md

@@ -21,6 +21,9 @@ The format is based on [Keep a Changelog](http://keepachangelog.com/en/1.0.0/).
 - Added `fsspec` support for profilers ([#4162](https://github.com/PyTorchLightning/pytorch-lightning/pull/4162))
 
 
+- Added autogenerated helptext to `Trainer.add_argparse_args`. ([#4344](https://github.com/PyTorchLightning/pytorch-lightning/pull/4344))
+
+
 ### Changed
 
 

pytorch_lightning/utilities/argparse_utils.py

@@ -14,7 +14,7 @@
 import inspect
 import os
 from argparse import ArgumentParser, Namespace
-from typing import Union, List, Tuple, Any
+from typing import Dict, Union, List, Tuple, Any
 from pytorch_lightning.utilities import parsing
 
 
@@ -160,7 +160,7 @@ def add_argparse_args(cls, parent_parser: ArgumentParser) -> ArgumentParser:
 
     allowed_types = (str, int, float, bool)
 
-    # TODO: get "help" from docstring :)
+    args_help = parse_args_from_docstring(cls.__init__.__doc__ or cls.__doc__)
     for arg, arg_types, arg_default in (
         at for at in get_init_arguments_and_types(cls) if at[0] not in depr_arg_names
     ):
@@ -200,13 +200,36 @@ def add_argparse_args(cls, parent_parser: ArgumentParser) -> ArgumentParser:
             dest=arg,
             default=arg_default,
             type=use_type,
-            help='autogenerated by pl.Trainer',
+            help=args_help.get(arg),
             **arg_kwargs,
         )
 
     return parser
 
 
+def parse_args_from_docstring(docstring: str) -> Dict[str, str]:
+    arg_block_indent = None
+    current_arg = None
+    parsed = {}
+    for line in docstring.split("\n"):
+        stripped = line.lstrip()
+        if not stripped:
+            continue
+        line_indent = len(line) - len(stripped)
+        if stripped.startswith(('Args:', 'Arguments:', 'Parameters:')):
+            arg_block_indent = line_indent + 4
+        elif arg_block_indent is None:
+            continue
+        elif line_indent < arg_block_indent:
+            break
+        elif line_indent == arg_block_indent:
+            current_arg, arg_description = stripped.split(':', maxsplit=1)
+            parsed[current_arg] = arg_description.lstrip()
+        elif line_indent > arg_block_indent:
+            parsed[current_arg] += f' {stripped}'
+    return parsed
+
+
 def _gpus_allowed_type(x) -> Union[int, str]:
     if ',' in x:
         return str(x)

tests/utilities/test_argparse_utils.py

@@ -0,0 +1,50 @@
+from pytorch_lightning.utilities.argparse_utils import parse_args_from_docstring
+
+
+def test_parse_args_from_docstring_normal():
+    args_help = parse_args_from_docstring(
+        """Constrain image dataset
+
+        Args:
+            root: Root directory of dataset where ``MNIST/processed/training.pt``
+                and  ``MNIST/processed/test.pt`` exist.
+            train: If ``True``, creates dataset from ``training.pt``,
+                otherwise from ``test.pt``.
+            normalize: mean and std deviation of the MNIST dataset.
+            download: If true, downloads the dataset from the internet and
+                puts it in root directory. If dataset is already downloaded, it is not
+                downloaded again.
+            num_samples: number of examples per selected class/digit
+            digits: list selected MNIST digits/classes
+
+        Examples:
+            >>> dataset = TrialMNIST(download=True)
+            >>> len(dataset)
+            300
+            >>> sorted(set([d.item() for d in dataset.targets]))
+            [0, 1, 2]
+            >>> torch.bincount(dataset.targets)
+            tensor([100, 100, 100])
+        """
+    )
+
+    expected_args = ['root', 'train', 'normalize', 'download', 'num_samples', 'digits']
+    assert len(args_help.keys()) == len(expected_args)
+    assert all([x == y for x, y in zip(args_help.keys(), expected_args)])
+    assert args_help['root'] == 'Root directory of dataset where ``MNIST/processed/training.pt``' \
+                                ' and  ``MNIST/processed/test.pt`` exist.'
+    assert args_help['normalize'] == 'mean and std deviation of the MNIST dataset.'
+
+
+def test_parse_args_from_docstring_empty():
+    args_help = parse_args_from_docstring(
+        """Constrain image dataset
+
+        Args:
+
+        Returns:
+
+        Examples:
+        """
+    )
+    assert len(args_help.keys()) == 0