# tf.reduce_all

tf.reduce_all(
input_tensor,
axis=None,
keepdims=None,
name=None,
reduction_indices=None,
keep_dims=None
)


Defined in tensorflow/python/ops/math_ops.py.

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

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 has no entries, all dimensions are reduced, and a tensor with a single element is returned.

For example:

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]


#### 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).
• reduction_indices: The old (deprecated) name for axis.
• keep_dims: Deprecated alias for keepdims.

#### Returns:

The reduced tensor.

#### Numpy Compatibility

Equivalent to np.all