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Computes the "logical and" of elements across dimensions of a tensor.
tf.reduce_all( input_tensor, axis=None, keepdims=False, name=None )
input_tensor along the dimensions given in
keepdims is true, the rank of the tensor is reduced by 1 for each
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 reduced tensor.|
Equivalent to np.all