|TensorFlow 1 version||View source on GitHub|
Computes the mean of elements across dimensions of a tensor.
tf.math.reduce_mean( input_tensor, axis=None, keepdims=False, name=None )
Used in the notebooks
|Used in the guide||Used in the tutorials|
input_tensor along the dimensions given in
axis by computing the
mean of elements across the dimensions 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., 1.], [2., 2.]])
<tf.Tensor: shape=(), dtype=float32, numpy=1.5>
<tf.Tensor: shape=(2,), dtype=float32, numpy=array([1.5, 1.5], dtype=float32)>
<tf.Tensor: shape=(2,), dtype=float32, numpy=array([1., 2.], dtype=float32)>