|TensorFlow 1 version||View source on GitHub|
Computes the standard deviation of elements across dimensions of a tensor.
Compat aliases for migration
See Migration guide for more details.
tf.math.reduce_std( input_tensor, axis=None, keepdims=False, name=None )
Used in the notebooks
|Used in the tutorials|
input_tensor along the dimensions given in
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.
axis is None, all dimensions are reduced, and a
tensor with a single element is returned.
x = tf.constant([[1., 2.], [3., 4.]])
<tf.Tensor: shape=(), dtype=float32, numpy=1.118034>
<tf.Tensor: shape=(2,), dtype=float32, numpy=array([1., 1.], dtype=float32)>
<tf.Tensor: shape=(2,), dtype=float32, numpy=array([0.5, 0.5], dtype=float32)>
||The tensor to reduce. Should have real or complex type.|
The dimensions to reduce. If
||If true, retains reduced dimensions with length 1.|
||A name scope for the associated operations (optional).|
The reduced tensor, of the same dtype as the input_tensor. Note, for