[Doc] Fix rendering of the unicode characters (#134597)

https://github.com/pytorch/pytorch/pull/124771 introduced unicode escape sequences inside raw strings, which were not rendered correctly. Also fix typo in `\uue0 ` escape sequence (should have been `\u00e0`)
Fix it by relying on [string literal concatenation](https://docs.python.org/3/reference/lexical_analysis.html#string-literal-concatenation) to join raw and regular strings together during lexical analysis stage

Fixes https://github.com/pytorch/pytorch/issues/134422

Pull Request resolved: https://github.com/pytorch/pytorch/pull/134597
Approved by: https://github.com/aorenste, https://github.com/Skylion007

torch/nn/modules/adaptive.py

@@ -18,13 +18,13 @@ _ASMoutput = namedtuple("_ASMoutput", ["output", "loss"])
 
 
 class AdaptiveLogSoftmaxWithLoss(Module):
-    r"""Efficient softmax approximation.
+    """Efficient softmax approximation.
 
     As described in
     `Efficient softmax approximation for GPUs by Edouard Grave, Armand Joulin,
     Moustapha Ciss\u00e9, David Grangier, and Herv\u00e9 J\u00e9gou
     <https://arxiv.org/abs/1609.04309>`__.
-
+""" r"""
     Adaptive softmax is an approximate strategy for training models with large
     output spaces. It is most effective when the label distribution is highly
     imbalanced, for example in natural language modelling, where the word

torch/nn/modules/conv.py

@@ -241,11 +241,13 @@ class Conv1d(_ConvNd):
     * :attr:`padding` controls the amount of padding applied to the input. It
       can be either a string {{'valid', 'same'}} or a tuple of ints giving the
       amount of implicit padding applied on both sides.
-
+"""
+        """
     * :attr:`dilation` controls the spacing between the kernel points; also
-      known as the \uue0 trous algorithm. It is harder to describe, but this `link`_
+      known as the \u00e0 trous algorithm. It is harder to describe, but this `link`_
       has a nice visualization of what :attr:`dilation` does.
-
+"""
+        r"""
     {groups_note}
 
     Note:
@@ -404,10 +406,13 @@ class Conv2d(_ConvNd):
     * :attr:`padding` controls the amount of padding applied to the input. It
       can be either a string {{'valid', 'same'}} or an int / a tuple of ints giving the
       amount of implicit padding applied on both sides.
-
+"""
+        """
     * :attr:`dilation` controls the spacing between the kernel points; also
       known as the \u00e0 trous algorithm. It is harder to describe, but this `link`_
       has a nice visualization of what :attr:`dilation` does.
+"""
+        r"""
 
     {groups_note}
 
@@ -574,9 +579,12 @@ class Conv3d(_ConvNd):
     * :attr:`padding` controls the amount of padding applied to the input. It
       can be either a string {{'valid', 'same'}} or a tuple of ints giving the
       amount of implicit padding applied on both sides.
-
+"""
+        """
     * :attr:`dilation` controls the spacing between the kernel points; also known as the \u00e0 trous algorithm.
       It is harder to describe, but this `link`_ has a nice visualization of what :attr:`dilation` does.
+"""
+        r"""
 
     {groups_note}
 
@@ -834,10 +842,12 @@ class ConvTranspose1d(_ConvTransposeNd):
 
     * :attr:`output_padding` controls the additional size added to one side
       of the output shape. See note below for details.
-
+"""
+        """
     * :attr:`dilation` controls the spacing between the kernel points; also known as the \u00e0 trous algorithm.
       It is harder to describe, but the link `here`_ has a nice visualization of what :attr:`dilation` does.
-
+"""
+        r"""
     {groups_note}
 
     Note:
@@ -996,10 +1006,12 @@ class ConvTranspose2d(_ConvTransposeNd):
 
     * :attr:`output_padding` controls the additional size added to one side
       of the output shape. See note below for details.
-
+"""
+        """
     * :attr:`dilation` controls the spacing between the kernel points; also known as the \u00e0 trous algorithm.
       It is harder to describe, but the link `here`_ has a nice visualization of what :attr:`dilation` does.
-
+"""
+        r"""
     {groups_note}
 
     The parameters :attr:`kernel_size`, :attr:`stride`, :attr:`padding`, :attr:`output_padding`
@@ -1184,10 +1196,12 @@ class ConvTranspose3d(_ConvTransposeNd):
 
     * :attr:`output_padding` controls the additional size added to one side
       of the output shape. See note below for details.
-
+"""
+        """
     * :attr:`dilation` controls the spacing between the kernel points; also known as the \u00e0 trous algorithm.
       It is harder to describe, but the link `here`_ has a nice visualization of what :attr:`dilation` does.
-
+"""
+        r"""
     {groups_note}
 
     The parameters :attr:`kernel_size`, :attr:`stride`, :attr:`padding`, :attr:`output_padding`

torch/nn/modules/fold.py

@@ -42,10 +42,10 @@ class Fold(Module):
     * :attr:`padding` controls the amount of implicit zero-paddings on both
       sides for :attr:`padding` number of points for each dimension before
       reshaping.
-
+""" """
     * :attr:`dilation` controls the spacing between the kernel points; also known as the \u00e0 trous algorithm.
       It is harder to describe, but this `link`_ has a nice visualization of what :attr:`dilation` does.
-
+""" r"""
     Args:
         output_size (int or tuple): the shape of the spatial dimensions of the
                                     output (i.e., ``output.sizes()[2:]``)
@@ -194,10 +194,10 @@ class Unfold(Module):
     * :attr:`padding` controls the amount of implicit zero-paddings on both
       sides for :attr:`padding` number of points for each dimension before
       reshaping.
-
+""" """
     * :attr:`dilation` controls the spacing between the kernel points; also known as the \u00e0 trous algorithm.
       It is harder to describe, but this `link`_ has a nice visualization of what :attr:`dilation` does.
-
+""" r"""
     Args:
         kernel_size (int or tuple): the size of the sliding blocks
         dilation (int or tuple, optional): a parameter that controls the