1 !important;\n  flex-shrink: 1 !important;\n}\n\n.justify-content-start {\n  -ms-flex-pack: start !important;\n  justify-content: flex-start !important;\n}\n\n.justify-content-end {\n  -ms-flex-pack: end !important;\n  justify-content: flex-end !important;\n}\n\n.justify-content-center {\n  -ms-flex-pack: center !important;\n  justify-content: center !important;\n}\n\n.justify-content-between {\n  -ms-flex-pack: justify !important;\n  justify-content: space-between !important;\n}\n\n.justify-content-around...

  TF_DerivedOperandTypeListAttr dtypes = TF_DerivedOperandTypeListAttr<0>;
}

def TF_PackOp : TF_Op<"Pack", [Pure]> {
  let summary = [{
Packs a list of `N` rank-`R` tensors into one rank-`(R+1)` tensor.
  }];

  let description = [{
Packs the `N` tensors in `values` into a tensor with rank one higher than each
tensor in `values`, by packing them along the `axis` dimension.

          type: "bool"
          default_value {
            b: false
          }
        }
        is_stateful: true
      }
      op {
        name: "NoOp"
      }
      op {
        name: "Pack"
        input_arg {
          name: "values"
          type_attr: "T"
          number_attr: "N"
        }
        output_arg {
          name: "output"
          type_attr: "T"
        }
        attr {

                        Service with no endpoints), the underlying implementation MUST actively
                        reject connection attempts to this backend. Packet drops must
                        respect weight; if an invalid backend is requested to have 80% of
                        the packets, then 80% of packets must be dropped instead.

`tf.reverse_v2()` will remain until 1.0 final. * `tf.mul`, `tf.sub` and `tf.neg`
are deprecated in favor of `tf.multiply`, `tf.subtract` and `tf.negative`. *
`tf.pack` and `tf.unpack` are deprecated in favor of `tf.stack` and
`tf.unstack`. * `TensorArray.pack` and `TensorArray.unpack` are getting
deprecated in favor of `TensorArray.stack` and `TensorArray.unstack`. * The