tf.compat.v1.reduce_all

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

View aliases

Compat aliases for migration

See Migration guide for more details.

tf.compat.v1.math.reduce_all

tf.compat.v1.reduce_all(
    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_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