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Expanding on docstrings in BoTorch Model #1496

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Expanding on docstrings in BoTorch Model #1496

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693cfbc
Expanding on docstrings in BoTorch `Model`
esantorella Nov 11, 2022
f66b780
Fixed URL; improved wording based on GH comments
esantorella Nov 11, 2022
e62ec36
one more minor wording change
esantorella Nov 11, 2022
9335ba9
removed one space
esantorella Nov 11, 2022
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23 changes: 17 additions & 6 deletions botorch/models/model.py
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Original file line number Diff line number Diff line change
Expand Up @@ -6,8 +6,8 @@

r"""Abstract base module for all BoTorch models.

Contains `Model`, the abstract base class for all BoTorch models, and
`ModelList`, a container for a list of Models.
This module contains `Model`, the abstract base class for all BoTorch models,
and `ModelList`, a container for a list of Models.
"""

from __future__ import annotations
Expand Down Expand Up @@ -46,8 +46,18 @@
class Model(Module, ABC):
r"""Abstract base class for BoTorch models.

Model cannot be used directly; it only defines an API for other BoTorch
models.
The `Model` base class cannot be used directly; it only defines an API for other
BoTorch models.

`Model` subclasses `torch.nn.Module`. While a `Module` is most typically
encountered as a representation of a neural network layer, it can be used more
generally: see
`documentation <https://pytorch.org/tutorials/beginner/examples_nn/polynomial_module.html>`_
on custom NN Modules.

`Module` provides several pieces of useful functionality: A `Model`'s attributes of
`Tensor` or `Module` type are automatically registered so they can be moved and/or
cast with the `to` method, automatically differentiated, and used with CUDA.

Args:
_has_transformed_inputs: A boolean denoting whether `train_inputs` are currently
Expand All @@ -56,7 +66,7 @@ class Model(Module, ABC):
`_revert_to_original_inputs`. Note that this is necessary since
transform / untransform cycle introduces numerical errors which lead
to upstream errors during training.
"""
""" # noqa: E501

_has_transformed_inputs: bool = False
_original_train_inputs: Optional[Tensor] = None
Expand Down Expand Up @@ -215,7 +225,8 @@ def eval(self) -> Model:
return super().eval()

def train(self, mode: bool = True) -> Model:
r"""Puts the model in `train` mode and reverts to the original inputs.
r"""Put the model in `train` mode. Reverts to the original inputs if in `train`
mode (`mode=True`) or sets transformed inputs if in `eval` mode (`mode=False`).

Args:
mode: A boolean denoting whether to put in `train` or `eval` mode.
Expand Down