fix pow(int, float) (#17126)

* fix pow(int, float)

* onnx

test/backend/test_ops.py

@@ -768,6 +768,11 @@ class TestOps(unittest.TestCase):
     helper_test_op([], lambda: torch.tensor([2], dtype=torch.int) ** torch.tensor(-2, dtype=torch.int),
                        lambda: Tensor([2]) ** Tensor(-2), forward_only=True)
 
+  def test_pow_int_base_float_exponent(self):
+    for exponent in (0.5, 1.5, 2.0, -1.0, 0.0):
+      helper_test_op([], lambda: torch.tensor([1, 2, 3, 4], dtype=torch.int) ** exponent,
+                         lambda: Tensor([1, 2, 3, 4], dtype=dtypes.int32) ** exponent, forward_only=True)
+
   def test_sqrt(self):
     helper_test_op([(45,65)], lambda x: x.sqrt())
     helper_test_op(None, lambda x: x.sqrt(), vals=[[0.0]])

tinygrad/mixin/elementwise.py

@@ -557,9 +557,7 @@ class ElementwiseMixin(CreationMixin):
     # TODO: int pow
     if not base.is_floating_point() and isinstance(x, ConstType) and not (isinstance(x, int) and x >= 0):
       raise RuntimeError("base needs to be float")
-    ret = base.alu(Ops.POW, exponent)
-    # NOTE: pow(int, float) -> int
-    return ret.round().cast(self.dtype) if not reverse and not dtypes.is_float(self.dtype) and dtypes.is_float(exponent.dtype) else ret
+    return base.alu(Ops.POW, exponent)
 
   def __pow__(self, x: Self | ConstType) -> Self:
     return self.pow(x)

tinygrad/nn/onnx.py

@@ -617,6 +617,8 @@ def get_onnx_ops() -> dict[str, types.FunctionType|dict[OpSetId, types.FunctionT
   def Add(x:Tensor,y:Tensor, broadcast=None, axis=None): return x + y
   def Sub(x:Tensor|int,y:Tensor): return x - y # some test has input as int
   def Div(x:Tensor,y:Tensor): return x.div(y, rounding_mode='trunc' if dtypes.is_int(x.dtype) else None)
+  # ONNX Pow is (T, T1) -> T, the output takes the base dtype while Tensor.pow promotes base and exponent
+  def Pow(x:Tensor,y:Tensor): return x.pow(y).round().cast(x.dtype) if dtypes.is_int(x.dtype) else x.pow(y)
   def Less(x:Tensor,y:Tensor): return x < y
   def LessOrEqual(x:Tensor,y:Tensor): return x <= y
   def Greater(x:Tensor,y:Tensor): return x > y
@@ -1297,7 +1299,7 @@ def get_onnx_ops() -> dict[str, types.FunctionType|dict[OpSetId, types.FunctionT
 
   return {
     # Tensor ops
-    **{op: getattr(Tensor, op.lower()) for op in ("Neg", "Reciprocal", "Pow", "Sqrt", "Sign", "Abs", "Exp", "Log", "Mish", "Sin", "Cos", "Tan",
+    **{op: getattr(Tensor, op.lower()) for op in ("Neg", "Reciprocal", "Sqrt", "Sign", "Abs", "Exp", "Log", "Mish", "Sin", "Cos", "Tan",
     "Asin", "Acos", "Atan", "Relu", "Sigmoid", "MatMul", "Floor", "Ceil", "IsNaN", "Softplus", "HardSwish", "Where", "Mul", "Sinh", "Cosh",
     "Tanh", "Softsign", "Asinh", "Acosh", "Atanh", "Elu", "Celu", "Selu", "Round", "Erf")},
     # Implemented ops