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torch/nn/modules/linear.py: docs: improvements (#138484)

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torch/nn/modules/linear.py: docs: improvements
Pull Request resolved: https://github.com/pytorch/pytorch/pull/138484
Approved by: https://github.com/mikaylagawarecki
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Alexander Kurakin 2025-01-10 20:03:40 +00:00 committed by PyTorch MergeBot
parent 7a81ba18b9
commit 68dad26b95
1 changed files with 8 additions and 8 deletions
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torch/nn/modules/linear.py
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@ -61,10 +61,10 @@ class Linear(Module):
Default: ``True``
Shape:
- Input: :math:`(*, H_{in})` where :math:`*` means any number of
dimensions including none and :math:`H_{in} = \text{in\_features}`.
- Output: :math:`(*, H_{out})` where all but the last dimension
are the same shape as the input and :math:`H_{out} = \text{out\_features}`.
- Input: :math:`(*, H_\text{in})` where :math:`*` means any number of
dimensions including none and :math:`H_\text{in} = \text{in\_features}`.
- Output: :math:`(*, H_\text{out})` where all but the last dimension
are the same shape as the input and :math:`H_\text{out} = \text{out\_features}`.
Attributes:
weight: the learnable weights of the module of shape
@ -154,15 +154,15 @@ class Bilinear(Module):
in1_features: size of each first input sample
in2_features: size of each second input sample
out_features: size of each output sample
bias: If set to False, the layer will not learn an additive bias.
bias: If set to ``False``, the layer will not learn an additive bias.
Default: ``True``
Shape:
- Input1: :math:`(*, H_{in1})` where :math:`H_{in1}=\text{in1\_features}` and
- Input1: :math:`(*, H_\text{in1})` where :math:`H_\text{in1}=\text{in1\_features}` and
:math:`*` means any number of additional dimensions including none. All but the last dimension
of the inputs should be the same.
- Input2: :math:`(*, H_{in2})` where :math:`H_{in2}=\text{in2\_features}`.
- Output: :math:`(*, H_{out})` where :math:`H_{out}=\text{out\_features}`
- Input2: :math:`(*, H_\text{in2})` where :math:`H_\text{in2}=\text{in2\_features}`.
- Output: :math:`(*, H_\text{out})` where :math:`H_\text{out}=\text{out\_features}`
and all but the last dimension are the same shape as the input.
Attributes: