MHLO_SignOp should not be converted to TF_SignOp
A better solution might be to clamp to `[-1, 1]` (assuming `clamp(NaN, [-1, 1])` is still `NaN`), then round (away from zero). Looks like we do not have any MHLO->TF conversion pattern for `mhlo.round_nearest_afz` yet. For now converting `mhlo.sign` to `tf.sign` might actually be the best option.
### System information

This issue applies to all systems on all TF versions since 2020-03-28.

### Describe the problem
MHLO_SignOp is defined to [return -0.0](https://github.com/tensorflow/tensorflow/blob/007ef257793b6ea0464361d2fc6a5a5b57403ce5/tensorflow/compiler/xla/mlir_hlo/mhlo/IR/hlo_ops.td#L562) when input is -0.0, but TF_SignOp and [TFL_SignOp](https://github.com/tensorflow/tensorflow/blob/007ef257793b6ea0464361d2fc6a5a5b57403ce5/tensorflow/compiler/mlir/lite/ir/tfl_ops.td#L5036) both return +0.0 on -0.0. For example:

> \>\>\> tf.math.sign([-0.0, 0.0, 1, -1])
> <tf.Tensor: shape=(4,), dtype=float32, numpy=array([ 0.,  0.,  1., -1.], dtype=float32)>

### Source code / logs
https://github.com/tensorflow/tensorflow/blob/6b167daef1d6953fd908c1ced6f347e1a7758138/tensorflow/compiler/mlir/tensorflow/transforms/legalize_hlo_patterns.td#L132
