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...

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...

		{"UserInfo10.FullName", Field, 0},
		{"UserInfo10.Name", Field, 0},
		{"UserInfo10.UsrComment", Field, 0},
		{"Ustat", Func, 0},
		{"Ustat_t", Type, 0},
		{"Ustat_t.Fname", Field, 0},
		{"Ustat_t.Fpack", Field, 0},
		{"Ustat_t.Pad_cgo_0", Field, 0},
		{"Ustat_t.Pad_cgo_1", Field, 0},
		{"Ustat_t.Tfree", Field, 0},
		{"Ustat_t.Tinode", Field, 0},
		{"Utimbuf", Type, 0},
		{"Utimbuf.Actime", Field, 0},

if `axis == 1` then the `output` tensor will have the shape `(A, N, B, C)`.
Etc.

For example:

```
# 'x' is [1, 4]
# 'y' is [2, 5]
# 'z' is [3, 6]
pack([x, y, z]) => [[1, 4], [2, 5], [3, 6]]  # Pack along first dim.
pack([x, y, z], axis=1) => [[1, 2, 3], [4, 5, 6]]
```

This is the opposite of `unpack`.
  }];

  let arguments = (ins

          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 {

`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