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).

Args
`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.

Returns
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.

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

tft.var

Args

Returns

Raises