# tensor 't' shape is [1, 2, 3, 4]

# 'dims' is [3] or 'dims' is [-1]
reverse(t, dims) ==> [[[[ 3,  2,  1,  0],
                        [ 7,  6,  5,  4],
                        [ 11, 10, 9, 8]],
                       [[15, 14, 13, 12],
                        [19, 18, 17, 16],
                        [23, 22, 21, 20]]]]

# 'dims' is '[1]' (or 'dims' is '[-3]')
reverse(t, dims) ==> [[[[12, 13, 14, 15],

    node {
      name: "Const"
      op: "Const"
      attr {
        key: "_output_shapes"
        value {
          list {
            shape {
              dim {
                size: 150
              }
              dim {
                size: 150
              }
            }
          }
        }
      }
      attr {
        key: "dtype"
        value {

- Switch etcd image (with migration scripts) from debian to distroless ([#91171](https://github.com/kubernetes/kubernetes/pull/91171), [@dims](https://github.com/dims)) [SIG API Machinery and Cloud Provider]

		{"Atan", Func, 0},
		{"Atan2", Func, 0},
		{"Atanh", Func, 0},
		{"Cbrt", Func, 0},
		{"Ceil", Func, 0},
		{"Copysign", Func, 0},
		{"Cos", Func, 0},
		{"Cosh", Func, 0},
		{"Dim", Func, 0},
		{"E", Const, 0},
		{"Erf", Func, 0},
		{"Erfc", Func, 0},
		{"Erfcinv", Func, 10},
		{"Erfinv", Func, 10},
		{"Exp", Func, 0},
		{"Exp2", Func, 0},
		{"Expm1", Func, 0},

* `tf.argmax`: `dimension` becomes `axis` * `tf.argmin`: `dimension` becomes
`axis` * `tf.count_nonzero`: `reduction_indices` becomes `axis` *
`tf.expand_dims`: `dim` becomes `axis` * `tf.reduce_all`: `reduction_indices`
becomes `axis` * `tf.reduce_any`: `reduction_indices` becomes `axis` *
`tf.reduce_join`: `reduction_indices` becomes `axis` * `tf.reduce_logsumexp`: