tf.compat.v1.reduce_any

View source on GitHub

Computes the "logical or" of elements across dimensions of a tensor. (deprecated arguments)

tf.compat.v1.reduce_any(
    input_tensor, axis=None, keepdims=None, name=None, reduction_indices=None,
    keep_dims=None
)

Warning: SOME ARGUMENTS ARE DEPRECATED: (keep_dims). They will be removed in a future version. Instructions for updating: keep_dims is deprecated, use keepdims instead

Reduces input_tensor along the dimensions given in axis. Unless keepdims is true, the rank of the tensor is reduced by 1 for each entry in axis. 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([[True,  True], [False, False]])
tf.reduce_any(x)  # True
tf.reduce_any(x, 0)  # [True, True]
tf.reduce_any(x, 1)  # [True, False]

Args:

Returns:

The reduced tensor.

Numpy Compatibility

Equivalent to np.any