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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.
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]
input_tensor: The boolean tensor to reduce.axis: The dimensions to reduce. If None (the default), reduces all
dimensions. Must be in the range [-rank(input_tensor),
rank(input_tensor)).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 keepdims.The reduced tensor.
Equivalent to np.any