tft.sum

Computes the sum of the values of a Tensor over the whole dataset.

tft.sum(
    x: common_types.TensorType,
    reduce_instance_dims: bool = True,
    name: Optional[str] = None
) -> tf.Tensor

Args
`x`	A `Tensor`, `SparseTensor`, or `RaggedTensor`. Its type must be floating point (float{16\|32\|64}),integral (int{8\|16\|32\|64}), or unsigned integral (uint{8\|16}).
`reduce_instance_dims`	By default collapses the batch and instance dimensions to arrive at a single scalar output. If False, only collapses the batch dimension and outputs a vector of the same shape as the input.
`name`	(Optional) A name for this operation.

Returns
A `Tensor` containing the sum. If `x` is float32 or float64, the sum will have the same type as `x`. If `x` is float16, the output is cast to float32. If `x` is integral, the output is cast to [u]int64. If `x` is sparse and reduce_inst_dims is False will return 0 in place where column has no values across batches.

Raises
`TypeError`	If the type of `x` is not supported.

Args