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OpenDAS
torch-cluster
Commits
f0f2062f
Commit
f0f2062f
authored
Apr 04, 2019
by
Vadim Bereznyuk
Browse files
typos
parent
33fa08d2
Changes
2
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4 deletions
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-4
torch_cluster/nearest.py
torch_cluster/nearest.py
+2
-2
torch_cluster/radius.py
torch_cluster/radius.py
+2
-2
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torch_cluster/nearest.py
View file @
f0f2062f
...
@@ -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)
"""
"""
...
...
torch_cluster/radius.py
View file @
f0f2062f
...
@@ -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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