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# tf.compat.v2.reduce_any

Computes the "logical or" of elements across dimensions of a tensor.

### Aliases:

• `tf.compat.v2.math.reduce_any`
``````tf.compat.v2.reduce_any(
input_tensor,
axis=None,
keepdims=False,
name=None
)
``````

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:

• `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).

#### Returns:

The reduced tensor.

#### Numpy Compatibility

Equivalent to np.any