tf.math.reduce_std

Computes the standard deviation of elements across dimensions of a tensor.

Used in the notebooks

Used in the tutorials

Reduces input_tensor along the dimensions given in axis. Unless keepdims is true, the rank of the tensor is reduced by 1 for each of the entries in axis, which must be unique. If keepdims is true, the reduced dimensions are retained with length 1.

If axis is None, all dimensions are reduced, and a tensor with a single element is returned.

For example:

x = tf.constant([[1., 2.], [3., 4.]])
tf.math.reduce_std(x)
<tf.Tensor: shape=(), dtype=float32, numpy=1.118034>
tf.math.reduce_std(x, 0)
<tf.Tensor: shape=(2,), dtype=float32, numpy=array([1., 1.], dtype=float32)>
tf.math.reduce_std(x, 1)
<tf.Tensor: shape=(2,), dtype=float32, numpy=array([0.5, 0.5], dtype=float32)>

input_tensor The tensor to reduce. Should have real or complex type.
axis The dimensions to reduce. If None (the default), reduces all dimensions. Must be in the range [-rank(input_tensor), rank(input_tensor)).
keepdims If true, retains reduc