tf.compat.v1.sparse_reduce_max  |  TensorFlow v2.16.1 (original) (raw)

'x' represents [[1, ?, 2]

[?, 3, ?]]

where ? is implicitly-zero.

x = tf.sparse.SparseTensor([[0, 0], [0, 2], [1, 1]], [1, 2, 3], [2, 3]) tf.sparse.reduce_max(x) <tf.Tensor: shape=(), dtype=int32, numpy=3> tf.sparse.reduce_max(x, 0) <tf.Tensor: shape=(3,), dtype=int32, numpy=array([1, 3, 2], dtype=int32)> tf.sparse.reduce_max(x, 1) <tf.Tensor: shape=(2,), dtype=int32, numpy=array([2, 3], dtype=int32)> tf.sparse.reduce_max(x, 1, keepdims=True) <tf.Tensor: shape=(2, 1), dtype=int32, numpy= array([[2], [3]], dtype=int32)> tf.sparse.reduce_max(x, [0, 1]) <tf.Tensor: shape=(), dtype=int32, numpy=3>

'y' represents [[-7, ?]

[ 4, 3]

[ ?, ?]

y = tf.sparse.SparseTensor([[0, 0,], [1, 0], [1, 1]], [-7, 4, 3], [3, 2]) tf.sparse.reduce_max(y, 1) <tf.Tensor: shape=(3,), dtype=int32, numpy=array([-7, 4, 0], dtype=int32)>