tft.var

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

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

Uses the biased variance (0 delta degrees of freedom), as given by (x - mean(x))**2 / length(x).

x: Tensor, SparseTensor, or RaggedTensor. Its type must be floating point (float{16|32|64}), or integral ([u]int{8|16|32|64}). 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. output_dtype: (Optional) If not None, casts the output tensor to this type.

A Tensor containing the variance. If x is floating point, the variance will have the same type as x. If x is integral, the output is cast to float32. NaNs and infinite input values are ignored.

TypeError: If the type of x is not supported.