ref: separate argparse

pytorch_lightning/trainer/trainer.py

@@ -488,112 +488,7 @@ def parse_argparser(cls, arg_parser: Union[ArgumentParser, Namespace]) -> Namesp
 
     @classmethod
     def add_argparse_args(cls, parent_parser: ArgumentParser) -> ArgumentParser:
-        r"""Extends existing argparse by default `Trainer` attributes.
-
-        Args:
-            parent_parser:
-                The custom cli arguments parser, which will be extended by
-                the Trainer default arguments.
-
-        Only arguments of the allowed types (str, float, int, bool) will
-        extend the `parent_parser`.
-
-        Examples:
-            >>> import argparse
-            >>> import pprint
-            >>> parser = argparse.ArgumentParser()
-            >>> parser = Trainer.add_argparse_args(parser)
-            >>> args = parser.parse_args([])
-            >>> pprint.pprint(vars(args))  # doctest: +ELLIPSIS +NORMALIZE_WHITESPACE
-            {...
-             'check_val_every_n_epoch': 1,
-             'checkpoint_callback': True,
-             'default_root_dir': None,
-             'deterministic': False,
-             'distributed_backend': None,
-             'early_stop_callback': False,
-             ...
-             'logger': True,
-             'max_epochs': 1000,
-             'max_steps': None,
-             'min_epochs': 1,
-             'min_steps': None,
-             ...
-             'profiler': None,
-             'progress_bar_refresh_rate': 1,
-             ...}
-
-        """
-        parser = ArgumentParser(parents=[parent_parser], add_help=False,)
-
-        blacklist = ['kwargs']
-        depr_arg_names = cls.get_deprecated_arg_names() + blacklist
-
-        allowed_types = (str, int, float, bool)
-
-        # TODO: get "help" from docstring :)
-        for arg, arg_types, arg_default in (
-            at for at in argparse_utils.get_init_arguments_and_types(cls) if at[0] not in depr_arg_names
-        ):
-            arg_types = [at for at in allowed_types if at in arg_types]
-            if not arg_types:
-                # skip argument with not supported type
-                continue
-            arg_kwargs = {}
-            if bool in arg_types:
-                arg_kwargs.update(nargs="?", const=True)
-                # if the only arg type is bool
-                if len(arg_types) == 1:
-                    use_type = parsing.str_to_bool
-                # if only two args (str, bool)
-                elif len(arg_types) == 2 and set(arg_types) == {str, bool}:
-                    use_type = parsing.str_to_bool_or_str
-                else:
-                    # filter out the bool as we need to use more general
-                    use_type = [at for at in arg_types if at is not bool][0]
-            else:
-                use_type = arg_types[0]
-
-            if arg == 'gpus' or arg == 'tpu_cores':
-                use_type = Trainer._gpus_allowed_type
-                arg_default = Trainer._gpus_arg_default
-
-            # hack for types in (int, float)
-            if len(arg_types) == 2 and int in set(arg_types) and float in set(arg_types):
-                use_type = Trainer._int_or_float_type
-
-            # hack for track_grad_norm
-            if arg == 'track_grad_norm':
-                use_type = float
-
-            parser.add_argument(
-                f'--{arg}',
-                dest=arg,
-                default=arg_default,
-                type=use_type,
-                help='autogenerated by pl.Trainer',
-                **arg_kwargs,
-            )
-
-        return parser
-
-    def _gpus_allowed_type(x) -> Union[int, str]:
-        if ',' in x:
-            return str(x)
-        else:
-            return int(x)
-
-    def _gpus_arg_default(x) -> Union[int, str]:
-        if ',' in x:
-            return str(x)
-        else:
-            return int(x)
-
-    def _int_or_float_type(x) -> Union[int, float]:
-        if '.' in str(x):
-            return float(x)
-        else:
-            return int(x)
+        return argparse_utils.add_argparse_args(cls, parent_parser)
 
     @property
     def num_gpus(self) -> int:

pytorch_lightning/utilities/argparse_utils.py

@@ -1,6 +1,7 @@
 import inspect
 from argparse import ArgumentParser, Namespace
 from typing import Union, List, Tuple, Any
+from pytorch_lightning.utilities import parsing
 
 
 def from_argparse_args(cls, args: Union[Namespace, ArgumentParser], **kwargs):
@@ -107,3 +108,116 @@ def get_init_arguments_and_types(cls) -> List[Tuple[str, Tuple, Any]]:
         name_type_default.append((arg, arg_types, arg_default))
 
     return name_type_default
+
+
+def add_argparse_args(cls, parent_parser: ArgumentParser) -> ArgumentParser:
+    r"""Extends existing argparse by default `Trainer` attributes.
+
+    Args:
+        parent_parser:
+            The custom cli arguments parser, which will be extended by
+            the Trainer default arguments.
+
+    Only arguments of the allowed types (str, float, int, bool) will
+    extend the `parent_parser`.
+
+    Examples:
+        >>> import argparse
+        >>> import pprint
+        >>> from pytorch_lightning import Trainer
+        >>> parser = argparse.ArgumentParser()
+        >>> parser = Trainer.add_argparse_args(parser)
+        >>> args = parser.parse_args([])
+        >>> pprint.pprint(vars(args))  # doctest: +ELLIPSIS +NORMALIZE_WHITESPACE
+        {...
+         'check_val_every_n_epoch': 1,
+         'checkpoint_callback': True,
+         'default_root_dir': None,
+         'deterministic': False,
+         'distributed_backend': None,
+         'early_stop_callback': False,
+         ...
+         'logger': True,
+         'max_epochs': 1000,
+         'max_steps': None,
+         'min_epochs': 1,
+         'min_steps': None,
+         ...
+         'profiler': None,
+         'progress_bar_refresh_rate': 1,
+         ...}
+
+    """
+    parser = ArgumentParser(parents=[parent_parser], add_help=False,)
+
+    blacklist = ['kwargs']
+    depr_arg_names = cls.get_deprecated_arg_names() + blacklist
+
+    allowed_types = (str, int, float, bool)
+
+    # TODO: get "help" from docstring :)
+    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
+    ):
+        arg_types = [at for at in allowed_types if at in arg_types]
+        if not arg_types:
+            # skip argument with not supported type
+            continue
+        arg_kwargs = {}
+        if bool in arg_types:
+            arg_kwargs.update(nargs="?", const=True)
+            # if the only arg type is bool
+            if len(arg_types) == 1:
+                use_type = parsing.str_to_bool
+            # if only two args (str, bool)
+            elif len(arg_types) == 2 and set(arg_types) == {str, bool}:
+                use_type = parsing.str_to_bool_or_str
+            else:
+                # filter out the bool as we need to use more general
+                use_type = [at for at in arg_types if at is not bool][0]
+        else:
+            use_type = arg_types[0]
+
+        if arg == 'gpus' or arg == 'tpu_cores':
+            use_type = _gpus_allowed_type
+            arg_default = _gpus_arg_default
+
+        # hack for types in (int, float)
+        if len(arg_types) == 2 and int in set(arg_types) and float in set(arg_types):
+            use_type = _int_or_float_type
+
+        # hack for track_grad_norm
+        if arg == 'track_grad_norm':
+            use_type = float
+
+        parser.add_argument(
+            f'--{arg}',
+            dest=arg,
+            default=arg_default,
+            type=use_type,
+            help='autogenerated by pl.Trainer',
+            **arg_kwargs,
+        )
+
+    return parser
+
+
+def _gpus_allowed_type(x) -> Union[int, str]:
+    if ',' in x:
+        return str(x)
+    else:
+        return int(x)
+
+
+def _gpus_arg_default(x) -> Union[int, str]:
+    if ',' in x:
+        return str(x)
+    else:
+        return int(x)
+
+
+def _int_or_float_type(x) -> Union[int, float]:
+    if '.' in str(x):
+        return float(x)
+    else:
+        return int(x)