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Computes the "logical and" of elements across dimensions of a tensor. (deprecated arguments)
Compat aliases for migration
See Migration guide for more details.
tf.compat.v1.reduce_all( input_tensor, axis=None, keepdims=None, name=None, reduction_indices=None, keep_dims=None )
input_tensor along the dimensions given in
keepdims is true, the rank of the tensor is reduced by 1 for each
of the entries in
axis, which must be unique. If
keepdims is true, the
reduced dimensions are retained with length 1.
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_all(x) # False tf.reduce_all(x, 0) # [False, False] tf.reduce_all(x, 1) # [True, False]
||The boolean tensor to reduce.|
The dimensions to reduce. If
||If true, retains reduced dimensions with length 1.|
||A name for the operation (optional).|
||The old (deprecated) name for axis.|
Deprecated alias for
|The reduced tensor.|
Equivalent to np.all