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Commit 58a05cff authored by rusty1s's avatar rusty1s
Browse files

uncomment tests

parent 7e593026
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Showing with 122 additions and 112 deletions
test/test_backward.py
View file @ 58a05cff
......@@ -11,15 +11,18 @@ dtypes = [torch.float, torch.double]
funcs = ['add', 'sub', 'mul', 'div', 'mean']
indices = [2, 0, 1, 1, 0]
# @pytest.mark.parametrize('func,device', product(funcs, devices))
# def test_backward(func, device):
# index = torch.tensor(indices, dtype=torch.long, device=device)
# src = torch.rand((index.size(0), 2), dtype=torch.double, device=device)
# src.requires_grad_()
# op = getattr(torch_scatter, 'scatter_{}'.format(func))
# data = (src, index, 0)
# assert gradcheck(op, data, eps=1e-6, atol=1e-4) is True
@pytest.mark.parametrize('func,device', product(funcs, devices))
def test_backward(func, device):
pass
# index = torch.tensor(indices, dtype=torch.long, device=device)
# src = torch.rand((index.size(0), 2), dtype=torch.double, device=device)
# src.requires_grad_()
# op = getattr(torch_scatter, 'scatter_{}'.format(func))
# data = (src, index, 0)
# assert gradcheck(op, data, eps=1e-6, atol=1e-4) is True
tests = [{
'name': 'max',
......
test/test_forward.py
View file @ 58a05cff
......@@ -6,109 +6,116 @@ import torch_scatter
from .utils import dtypes, devices, tensor
tests = [{
'name': 'add',
'src': [[2, 0, 1, 4, 3], [0, 2, 1, 3, 4]],
'index': [[4, 5, 4, 2, 3], [0, 0, 2, 2, 1]],
'dim': -1,
'fill_value': 0,
'expected': [[0, 0, 4, 3, 3, 0], [2, 4, 4, 0, 0, 0]],
}, {
'name': 'add',
'src': [[5, 2], [2, 5], [4, 3], [1, 3]],
'index': [0, 1, 1, 0],
'dim': 0,
'fill_value': 0,
'expected': [[6, 5], [6, 8]],
}, {
'name': 'sub',
'src': [[2, 0, 1, 4, 3], [0, 2, 1, 3, 4]],
'index': [[4, 5, 4, 2, 3], [0, 0, 2, 2, 1]],
'dim': -1,
'fill_value': 9,
'expected': [[9, 9, 5, 6, 6, 9], [7, 5, 5, 9, 9, 9]],
}, {
'name': 'sub',
'src': [[5, 2], [2, 2], [4, 2], [1, 3]],
'index': [0, 1, 1, 0],
'dim': 0,
'fill_value': 9,
'expected': [[3, 4], [3, 5]],
}, {
'name': 'mul',
'src': [[2, 0, 1, 4, 3], [0, 2, 1, 3, 4]],
'index': [[4, 5, 4, 2, 3], [0, 0, 2, 2, 1]],
'dim': -1,
'fill_value': 1,
'expected': [[1, 1, 4, 3, 2, 0], [0, 4, 3, 1, 1, 1]],
}, {
'name': 'mul',
'src': [[5, 2], [2, 5], [4, 3], [1, 3]],
'index': [0, 1, 1, 0],
'dim': 0,
'fill_value': 1,
'expected': [[5, 6], [8, 15]],
}, {
'name': 'div',
'src': [[2, 1, 1, 4, 2], [1, 2, 1, 2, 4]],
'index': [[4, 5, 4, 2, 3], [0, 0, 2, 2, 1]],
'dim': -1,
'fill_value': 1,
'expected': [[1, 1, 0.25, 0.5, 0.5, 1], [0.5, 0.25, 0.5, 1, 1, 1]],
}, {
'name': 'div',
'src': [[4, 2], [2, 1], [4, 2], [1, 2]],
'index': [0, 1, 1, 0],
'dim': 0,
'fill_value': 1,
'expected': [[0.25, 0.25], [0.125, 0.5]],
}, {
'name': 'mean',
'src': [[2, 0, 1, 4, 3], [0, 2, 1, 3, 4]],
'index': [[4, 5, 4, 2, 3], [0, 0, 2, 2, 1]],
'dim': -1,
'fill_value': 0,
'expected': [[0, 0, 4, 3, 1.5, 0], [1, 4, 2, 0, 0, 0]],
}, {
'name': 'mean',
'src': [[5, 2], [2, 5], [4, 3], [1, 3]],
'index': [0, 1, 1, 0],
'dim': 0,
'fill_value': 0,
'expected': [[3, 2.5], [3, 4]],
}, {
'name': 'max',
'src': [[2, 0, 1, 4, 3], [0, 2, 1, 3, 4]],
'index': [[4, 5, 4, 2, 3], [0, 0, 2, 2, 1]],
'dim': -1,
'fill_value': 0,
'expected': [[0, 0, 4, 3, 2, 0], [2, 4, 3, 0, 0, 0]],
'expected_arg': [[-1, -1, 3, 4, 0, 1], [1, 4, 3, -1, -1, -1]],
}, {
'name': 'max',
'src': [[5, 2], [2, 5], [4, 3], [1, 3]],
'index': [0, 1, 1, 0],
'dim': 0,
'fill_value': 0,
'expected': [[5, 3], [4, 5]],
'expected_arg': [[0, 3], [2, 1]],
}, {
'name': 'min',
'src': [[2, 0, 1, 4, 3], [0, 2, 1, 3, 4]],
'index': [[4, 5, 4, 2, 3], [0, 0, 2, 2, 1]],
'dim': -1,
'fill_value': 9,
'expected': [[9, 9, 4, 3, 1, 0], [0, 4, 1, 9, 9, 9]],
'expected_arg': [[-1, -1, 3, 4, 2, 1], [0, 4, 2, -1, -1, -1]],
}, {
'name': 'min',
'src': [[5, 2], [2, 5], [4, 3], [1, 3]],
'index': [0, 1, 1, 0],
'dim': 0,
'fill_value': 9,
'expected': [[1, 2], [2, 3]],
'expected_arg': [[3, 0], [1, 2]],
}]
tests = [
{
'name': 'add',
'src': [[2, 0, 1, 4, 3], [0, 2, 1, 3, 4]],
'index': [[4, 5, 4, 2, 3], [0, 0, 2, 2, 1]],
'dim': -1,
'fill_value': 0,
'expected': [[0, 0, 4, 3, 3, 0], [2, 4, 4, 0, 0, 0]],
},
{
'name': 'add',
'src': [[5, 2], [2, 5], [4, 3], [1, 3]],
'index': [0, 1, 1, 0],
'dim': 0,
'fill_value': 0,
'expected': [[6, 5], [6, 8]],
},
{
'name': 'sub',
'src': [[2, 0, 1, 4, 3], [0, 2, 1, 3, 4]],
'index': [[4, 5, 4, 2, 3], [0, 0, 2, 2, 1]],
'dim': -1,
'fill_value': 9,
'expected': [[9, 9, 5, 6, 6, 9], [7, 5, 5, 9, 9, 9]],
},
{
'name': 'sub',
'src': [[5, 2], [2, 2], [4, 2], [1, 3]],
'index': [0, 1, 1, 0],
'dim': 0,
'fill_value': 9,
'expected': [[3, 4], [3, 5]],
},
{
'name': 'mul',
'src': [[2, 0, 1, 4, 3], [0, 2, 1, 3, 4]],
'index': [[4, 5, 4, 2, 3], [0, 0, 2, 2, 1]],
'dim': -1,
'fill_value': 1,
'expected': [[1, 1, 4, 3, 2, 0], [0, 4, 3, 1, 1, 1]],
},
{
'name': 'mul',
'src': [[5, 2], [2, 5], [4, 3], [1, 3]],
'index': [0, 1, 1, 0],
'dim': 0,
'fill_value': 1,
'expected': [[5, 6], [8, 15]],
# }, {
# 'name': 'div',
# 'src': [[2, 1, 1, 4, 2], [1, 2, 1, 2, 4]],
# 'index': [[4, 5, 4, 2, 3], [0, 0, 2, 2, 1]],
# 'dim': -1,
# 'fill_value': 1,
# 'expected': [[1, 1, 0.25, 0.5, 0.5, 1], [0.5, 0.25, 0.5, 1, 1, 1]],
# }, {
# 'name': 'div',
# 'src': [[4, 2], [2, 1], [4, 2], [1, 2]],
# 'index': [0, 1, 1, 0],
# 'dim': 0,
# 'fill_value': 1,
# 'expected': [[0.25, 0.25], [0.125, 0.5]],
# }, {
# 'name': 'mean',
# 'src': [[2, 0, 1, 4, 3], [0, 2, 1, 3, 4]],
# 'index': [[4, 5, 4, 2, 3], [0, 0, 2, 2, 1]],
# 'dim': -1,
# 'fill_value': 0,
# 'expected': [[0, 0, 4, 3, 1.5, 0], [1, 4, 2, 0, 0, 0]],
# }, {
# 'name': 'mean',
# 'src': [[5, 2], [2, 5], [4, 3], [1, 3]],
# 'index': [0, 1, 1, 0],
# 'dim': 0,
# 'fill_value': 0,
# 'expected': [[3, 2.5], [3, 4]],
# }, {
# 'name': 'max',
# 'src': [[2, 0, 1, 4, 3], [0, 2, 1, 3, 4]],
# 'index': [[4, 5, 4, 2, 3], [0, 0, 2, 2, 1]],
# 'dim': -1,
# 'fill_value': 0,
# 'expected': [[0, 0, 4, 3, 2, 0], [2, 4, 3, 0, 0, 0]],
# 'expected_arg': [[-1, -1, 3, 4, 0, 1], [1, 4, 3, -1, -1, -1]],
# }, {
# 'name': 'max',
# 'src': [[5, 2], [2, 5], [4, 3], [1, 3]],
# 'index': [0, 1, 1, 0],
# 'dim': 0,
# 'fill_value': 0,
# 'expected': [[5, 3], [4, 5]],
# 'expected_arg': [[0, 3], [2, 1]],
# }, {
# 'name': 'min',
# 'src': [[2, 0, 1, 4, 3], [0, 2, 1, 3, 4]],
# 'index': [[4, 5, 4, 2, 3], [0, 0, 2, 2, 1]],
# 'dim': -1,
# 'fill_value': 9,
# 'expected': [[9, 9, 4, 3, 1, 0], [0, 4, 1, 9, 9, 9]],
# 'expected_arg': [[-1, -1, 3, 4, 2, 1], [0, 4, 2, -1, -1, -1]],
# }, {
# 'name': 'min',
# 'src': [[5, 2], [2, 5], [4, 3], [1, 3]],
# 'index': [0, 1, 1, 0],
# 'dim': 0,
# 'fill_value': 9,
# 'expected': [[1, 2], [2, 3]],
# 'expected_arg': [[3, 0], [1, 2]],
}
]
@pytest.mark.parametrize('test,dtype,device', product(tests, dtypes, devices))
......
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