Tensor.logaddexp (#11793)

docs/tensor/elementwise.md

@@ -78,6 +78,7 @@ Elementwise ops operate on a per element basis. They don't change the shape of t
 ::: tinygrad.Tensor.minimum
 ::: tinygrad.Tensor.where
 ::: tinygrad.Tensor.copysign
+::: tinygrad.Tensor.logaddexp
 
 ## Casting Ops
 

extra/torch_backend/backend.py

@@ -381,6 +381,7 @@ decomps = [
   aten.elu,  # elu has a scale + input_scale param
   aten.elu_backward,
   aten.softplus,
+  aten.logaddexp,
   aten.threshold,
   aten.nll_loss_forward,
   aten.nll_loss_backward,

test/test_ops.py

@@ -928,6 +928,12 @@ class TestOps(unittest.TestCase):
       for j in [-1., 0., 1.]:
         helper_test_op(None, torch.copysign, Tensor.copysign, vals=[[i], [j]])
 
+  def test_logaddexp(self):
+    helper_test_op([(45,65), (45,65)], torch.logaddexp, Tensor.logaddexp)
+    helper_test_op(None, torch.logaddexp, Tensor.logaddexp, vals=[[-1.], [-1.0, 2, 3]])
+    helper_test_op(None, torch.logaddexp, Tensor.logaddexp, vals=[[-100.0, -200, -300], [-1.0, 2, 3]])
+    helper_test_op(None, torch.logaddexp, Tensor.logaddexp, vals=[[1.0, 2000, 30000], [-1.0, 2, 3]])
+
   def test_softsign(self):
     helper_test_op([(45,65)], torch.nn.functional.softsign, Tensor.softsign)
     helper_test_op([()], torch.nn.functional.softsign, Tensor.softsign)

tinygrad/tensor.py

@@ -3759,6 +3759,13 @@ class Tensor(MathTrait):
     # TODO: remove other*0?
     return (other < 0).where(-self.abs(), self.abs()) + other*0
 
+  def logaddexp(self, other) -> Tensor:
+    """
+    Calculates (self.exp()+other.exp()).log(), elementwise.
+    """
+    m = self.maximum(other)
+    return ((self-m).exp() + (self._broadcasted(other)[1]-m).exp()).log() + m
+
   # ***** op wrappers *****
 
   def __invert__(self) -> Tensor: return self.bitwise_not()