Commit f0f2062f authored by Vadim Bereznyuk's avatar Vadim Bereznyuk
Browse files

typos

parent 33fa08d2
...@@ -13,7 +13,7 @@ def nearest(x, y, batch_x=None, batch_y=None): ...@@ -13,7 +13,7 @@ def nearest(x, y, batch_x=None, batch_y=None):
x (Tensor): Node feature matrix x (Tensor): Node feature matrix
:math:`\mathbf{X} \in \mathbb{R}^{N \times F}`. :math:`\mathbf{X} \in \mathbb{R}^{N \times F}`.
y (Tensor): Node feature matrix y (Tensor): Node feature matrix
:math:`\mathbf{X} \in \mathbb{R}^{M \times F}`. :math:`\mathbf{Y} \in \mathbb{R}^{M \times F}`.
batch_x (LongTensor, optional): Batch vector batch_x (LongTensor, optional): Batch vector
:math:`\mathbf{b} \in {\{ 0, \ldots, B-1\}}^N`, which assigns each :math:`\mathbf{b} \in {\{ 0, \ldots, B-1\}}^N`, which assigns each
node to a specific example. (default: :obj:`None`) node to a specific example. (default: :obj:`None`)
...@@ -31,7 +31,7 @@ def nearest(x, y, batch_x=None, batch_y=None): ...@@ -31,7 +31,7 @@ def nearest(x, y, batch_x=None, batch_y=None):
>>> x = torch.Tensor([[-1, -1], [-1, 1], [1, -1], [1, 1]]) >>> x = torch.Tensor([[-1, -1], [-1, 1], [1, -1], [1, 1]])
>>> batch_x = torch.tensor([0, 0, 0, 0]) >>> batch_x = torch.tensor([0, 0, 0, 0])
>>> y = torch.Tensor([[-1, 0], [1, 0]]) >>> y = torch.Tensor([[-1, 0], [1, 0]])
>>> batch_x = torch.tensor([0, 0]) >>> batch_y = torch.tensor([0, 0])
>>> cluster = nearest(x, y, batch_x, batch_y) >>> cluster = nearest(x, y, batch_x, batch_y)
""" """
......
...@@ -13,7 +13,7 @@ def radius(x, y, r, batch_x=None, batch_y=None, max_num_neighbors=32): ...@@ -13,7 +13,7 @@ def radius(x, y, r, batch_x=None, batch_y=None, max_num_neighbors=32):
x (Tensor): Node feature matrix x (Tensor): Node feature matrix
:math:`\mathbf{X} \in \mathbb{R}^{N \times F}`. :math:`\mathbf{X} \in \mathbb{R}^{N \times F}`.
y (Tensor): Node feature matrix y (Tensor): Node feature matrix
:math:`\mathbf{X} \in \mathbb{R}^{M \times F}`. :math:`\mathbf{Y} \in \mathbb{R}^{M \times F}`.
r (float): The radius. r (float): The radius.
batch_x (LongTensor, optional): Batch vector batch_x (LongTensor, optional): Batch vector
:math:`\mathbf{b} \in {\{ 0, \ldots, B-1\}}^N`, which assigns each :math:`\mathbf{b} \in {\{ 0, \ldots, B-1\}}^N`, which assigns each
...@@ -38,7 +38,7 @@ def radius(x, y, r, batch_x=None, batch_y=None, max_num_neighbors=32): ...@@ -38,7 +38,7 @@ def radius(x, y, r, batch_x=None, batch_y=None, max_num_neighbors=32):
>>> x = torch.Tensor([[-1, -1], [-1, 1], [1, -1], [1, 1]]) >>> x = torch.Tensor([[-1, -1], [-1, 1], [1, -1], [1, 1]])
>>> batch_x = torch.tensor([0, 0, 0, 0]) >>> batch_x = torch.tensor([0, 0, 0, 0])
>>> y = torch.Tensor([[-1, 0], [1, 0]]) >>> y = torch.Tensor([[-1, 0], [1, 0]])
>>> batch_x = torch.tensor([0, 0]) >>> batch_y = torch.tensor([0, 0])
>>> assign_index = radius(x, y, 1.5, batch_x, batch_y) >>> assign_index = radius(x, y, 1.5, batch_x, batch_y)
""" """
......
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