tf.reduce_all( input_tensor, axis=None, keepdims=None, name=None, reduction_indices=None, keep_dims=None )
See the guide: Math > Reduction
Computes the "logical and" of elements across dimensions of a tensor. (deprecated arguments)
SOME ARGUMENTS ARE DEPRECATED. They will be removed in a future version. Instructions for updating: keep_dims is deprecated, use keepdims instead
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 has no entries, 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]
input_tensor: The boolean tensor to reduce.
axis: The dimensions to reduce. If
None(the default), reduces all dimensions. Must be in the range
keepdims: If true, retains reduced dimensions with length 1.
name: A name for the operation (optional).
reduction_indices: The old (deprecated) name for axis.
keep_dims: Deprecated alias for
The reduced tensor.
Equivalent to np.all