some dtype creation spec test cases (#2722)

test/test_dtype.py

@@ -218,5 +218,21 @@ class TestHelpers(unittest.TestCase):
   def test_scalar(self, dtype, amt):
     assert dtype.vec(amt).scalar() == dtype
 
+class TestTypeSpec(unittest.TestCase):
+  def test_creation(self):
+    assert Tensor([]).dtype == Tensor.default_type
+    # assert Tensor([1]).dtype == dtypes.int
+    assert Tensor([1.1]).dtype == Tensor.default_type
+
+  def test_const_full(self):
+    assert Tensor.ones([2,3]).dtype == Tensor.default_type
+    assert Tensor.zeros([2,3]).dtype == Tensor.default_type
+    assert Tensor.full([2,3], 3.3).dtype == Tensor.default_type
+    # assert Tensor.full([2,3], 3).dtype == dtypes.int
+
+  def test_reduce_0d_default(self):
+    assert Tensor.ones([2,3,0]).sum(2).dtype ==  Tensor.default_type
+    # assert Tensor.ones([2,3,0], dtype=dtypes.int).sum(2).dtype == dtypes.int
+
 if __name__ == '__main__':
   unittest.main()

tinygrad/tensor.py

@@ -473,7 +473,7 @@ class Tensor:
     axis_: List[int] = list(range(len(self.shape))) if axis is None else ([axis] if isinstance(axis, int) else list(axis))
     axis_ = [x if x >= 0 else x+len(self.shape) for x in axis_]
     shape = tuple(s for i,s in enumerate(self.shape) if i not in axis_)
-    if 0 in self.shape and 0 not in shape: return Tensor.full(tuple(1 if s == 0 else s for s in self.shape) if keepdim else shape, {mlops.Sum: 0, mlops.Max: -float("inf")}[fxn])
+    if 0 in self.shape and 0 not in shape: return Tensor.full(tuple(1 if s == 0 else s for s in self.shape) if keepdim else shape, {mlops.Sum: 0.0, mlops.Max: -float("inf")}[fxn])
     ret = fxn.apply(self, new_shape=tuple([1 if i in axis_ else s for i,s in enumerate(self.shape)]))
     return ret if keepdim else ret.reshape(shape=shape)