|---| | [ View source on GitHub](https://github.com/tensorflow/probability/blob/v0.25.0/tensorflow_probability/python/math/generic.py#L182-L218) | Reduces the input tensor along the given axis using Kahan summation. tfp.math.reduce_kahan_sum( input_tensor, axis=None, keepdims=False, name=None ) Returns both the total and the correction term, as a `namedtuple`, representing the sum in higher precision as `total - correction`. A practical use-case is computing the difference of two large (magnitude) sums we expect to be nearly equal. If instead we take their difference as `(s0.total - s1.total) - (s0.correction - s1.correction)`, we can retain more precision in computing their difference. Note that `total` holds all the high-order bits of the sum, so the correction can be safely neglected if further enhanced precision computations are not required. > [!NOTE] > **Note:** (TF + JAX) This function does not work properly on XLA:CPU without the environment variable: `XLA_FLAGS=--xla_cpu_enable_fast_math=false`, due to LLVM's reassociation optimizations, which simplify error terms to zero.


| ## Args || |---|---| | `input_tensor` | The tensor to sum. | | `axis` | One of `None`, a Python `int`, or a sequence of Python `int`. The axes to be reduced. `None` is taken as "reduce all axes". | | `keepdims` | Python `bool` indicating whether we return a tensor with singleton dimensions in the reduced axes (`True`), or squeeze the axes out (default, `False`). | | `name` | Optional name for ops in scope. |



| ## Returns || |---|---| | `reduced` | A `Kahan(total, correction)` namedtuple. |