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Commit 2c883ba3 authored by rusty1s's avatar rusty1s
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fixed print statements

parent ee2d323d
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Showing with 14 additions and 11 deletions
README.md
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...@@ -81,7 +81,7 @@ from torch_sparse import coalesce ...@@ -81,7 +81,7 @@ from torch_sparse import coalesce
index = torch.tensor([[1, 0, 1, 0, 2, 1], index = torch.tensor([[1, 0, 1, 0, 2, 1],
[0, 1, 1, 1, 0, 0]]) [0, 1, 1, 1, 0, 0]])
value = torch.tensor([[1, 2], [2, 3], [3, 4], [4, 5], [5, 6], [6, 7]]) value = torch.Tensor([[1, 2], [2, 3], [3, 4], [4, 5], [5, 6], [6, 7]])
index, value = coalesce(index, value, m=3, n=2) index, value = coalesce(index, value, m=3, n=2)
``` ```
...@@ -91,7 +91,10 @@ print(index) ...@@ -91,7 +91,10 @@ print(index)
tensor([[0, 1, 1, 2], tensor([[0, 1, 1, 2],
[1, 0, 1, 0]]) [1, 0, 1, 0]])
print(value) print(value)
tensor([[6, 8], [7, 9], [3, 4], [5, 6]]) tensor([[6.0, 8.0],
[7.0, 9.0],
[3.0, 4.0],
[5.0, 6.0]])
``` ```
## Transpose ## Transpose
...@@ -121,7 +124,7 @@ from torch_sparse import transpose ...@@ -121,7 +124,7 @@ from torch_sparse import transpose
index = torch.tensor([[1, 0, 1, 0, 2, 1], index = torch.tensor([[1, 0, 1, 0, 2, 1],
[0, 1, 1, 1, 0, 0]]) [0, 1, 1, 1, 0, 0]])
value = torch.tensor([[1, 2], [2, 3], [3, 4], [4, 5], [5, 6], [6, 7]]) value = torch.Tensor([[1, 2], [2, 3], [3, 4], [4, 5], [5, 6], [6, 7]])
index, value = transpose(index, value, 3, 2) index, value = transpose(index, value, 3, 2)
``` ```
...@@ -131,10 +134,10 @@ print(index) ...@@ -131,10 +134,10 @@ print(index)
tensor([[0, 0, 1, 1], tensor([[0, 0, 1, 1],
[1, 2, 0, 1]]) [1, 2, 0, 1]])
print(value) print(value)
tensor([[7, 9], tensor([[7.0, 9.0],
[5, 6], [5.0, 6.0],
[6, 8], [6.0, 8.0],
[3, 4]]) [3.0, 4.0]])
``` ```
## Sparse Dense Matrix Multiplication ## Sparse Dense Matrix Multiplication
...@@ -163,8 +166,8 @@ from torch_sparse import spmm ...@@ -163,8 +166,8 @@ from torch_sparse import spmm
index = torch.tensor([[0, 0, 1, 2, 2], index = torch.tensor([[0, 0, 1, 2, 2],
[0, 2, 1, 0, 1]]) [0, 2, 1, 0, 1]])
value = torch.tensor([1, 2, 4, 1, 3], dtype=torch.float) value = torch.Tensor([1, 2, 4, 1, 3])
matrix = torch.tensor([[1, 4], [2, 5], [3, 6]], dtype=torch.float) matrix = torch.Tensor([[1, 4], [2, 5], [3, 6]])
out = spmm(index, value, 3, matrix) out = spmm(index, value, 3, matrix)
``` ```
...@@ -206,10 +209,10 @@ Both input sparse matrices need to be **coalesced**. ...@@ -206,10 +209,10 @@ Both input sparse matrices need to be **coalesced**.
from torch_sparse import spspmm from torch_sparse import spspmm
indexA = torch.tensor([[0, 0, 1, 2, 2], [1, 2, 0, 0, 1]]) indexA = torch.tensor([[0, 0, 1, 2, 2], [1, 2, 0, 0, 1]])
valueA = torch.tensor([1, 2, 3, 4, 5], dtype=torch.float) valueA = torch.Tensor([1, 2, 3, 4, 5])
indexB = torch.tensor([[0, 2], [1, 0]]) indexB = torch.tensor([[0, 2], [1, 0]])
valueB = torch.tensor([2, 4], dtype=torch.float) valueB = torch.Tensor([2, 4])
indexC, valueC = spspmm(indexA, valueA, indexB, valueB, 3, 3, 2) indexC, valueC = spspmm(indexA, valueA, indexB, valueB, 3, 3, 2)
``` ```
......
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