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Add support for __floordiv__ and __rdiv__ for integral tensors #7245

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Merged
apaszke merged 3 commits into from
May 3, 2018
Merged

Add support for __floordiv__ and __rdiv__ for integral tensors #7245

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da65cb2
Add support for __floordiv__ and __rdiv__ for integral tensors
apaszke May 3, 2018
2b8998c
Add tests
apaszke May 3, 2018
77f9340
Python 2.7 fix
apaszke May 3, 2018
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22 changes: 22 additions & 0 deletions test/test_torch.py
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Original file line number Diff line number Diff line change
Expand Up @@ -1003,6 +1003,28 @@ def test_div(self):
res2[i, 3] = res2[i, 3] / 2
self.assertEqual(res1, res2)

def test_floordiv(self):
for dtype in torch.testing.get_all_dtypes():
if dtype is torch.float16:
continue
x = torch.randn(100).mul(10).to(dtype)
y = x // 3
self.assertEqual(y.dtype, x.dtype)
z = torch.tensor([math.trunc(v.item() / 3.) for v in x], dtype=y.dtype)
self.assertEqual(y, z)

def test_rdiv(self):
for dtype in torch.testing.get_all_dtypes():
if dtype is torch.float16:
continue
x = torch.rand(100).add(1).mul(4).to(dtype)
y = 30 / x
if dtype.is_floating_point:
z = torch.tensor([30 / v.item() for v in x], dtype=dtype)
else:
z = torch.tensor([math.trunc(30. / v.item()) for v in x], dtype=dtype)
self.assertEqual(y, z)

def test_fmod(self):
m1 = torch.Tensor(10, 10).uniform_(-10., 10.)
res1 = m1.clone()
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18 changes: 17 additions & 1 deletion torch/tensor.py
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Expand Up @@ -317,7 +317,11 @@ def __rsub__(self, other):
return -self + other

def __rdiv__(self, other):
return self.reciprocal() * other
if self.dtype.is_floating_point:
return self.reciprocal() * other
else:
return (self.double().reciprocal() * other).type_as(self)

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__rtruediv__ = __rdiv__
__itruediv__ = _C._TensorBase.__idiv__

Expand All @@ -334,6 +338,18 @@ def __ipow__(self, other):
def __rpow__(self, other):
return self.new([other]) ** self

def __floordiv__(self, other):
result = self / other
if result.dtype.is_floating_point:
result = result.trunc()
return result

def __rfloordiv__(self, other):
result = other / self
if result.dtype.is_floating_point:
result = result.trunc()
return result

__neg__ = _C._TensorBase.neg

__eq__ = _C._TensorBase.eq
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