|TensorFlow 2 version||View source on GitHub|
Computes the "logical and" of elements across dimensions of a tensor. (deprecated arguments)
See Migration guide for more details.
tf.math.reduce_all( input_tensor, axis=None, keepdims=None, name=None, reduction_indices=None, keep_dims=None )
input_tensor along the dimensions given in
keepdims is true, the rank of the tensor is reduced by 1 for each
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([[True, True], [False, False]]) tf.reduce_all(x) # False tf.reduce_all(x, 0) # [False, False] tf.reduce_all(x, 1) # [True, False]
||The boolean tensor to reduce.|
The dimensions to reduce. If
||If true, retains reduced dimensions with length 1.|
||A name for the operation (optional).|
||The old (deprecated) name for axis.|
Deprecated alias for
|The reduced tensor.|
Equivalent to np.all