// Example- "tfl.transpose"(tensor<56x8x56x1x1x1x7xf32>, [4, 5, 1, 2, 0, 6, 3])
// Permutation before squeese is [4, 5, 1, 2, 0, 6, 3] becomes [1, 2, 0, 3]
// after squeeze is perfomed to retain the relative ordering of the non-1 dims.
DenseElementsAttr GetSqueezedPermutation(Value input_value,
                                         Value input_permutation) {

```
# 't' is a tensor of shape [1, 2, 1, 3, 1, 1]
shape(squeeze(t)) ==> [2, 3]
```

Or, to remove specific size 1 dimensions:

```
# 't' is a tensor of shape [1, 2, 1, 3, 1, 1]
shape(squeeze(t, [2, 4])) ==> [1, 2, 3, 1]
```
  }];

  let arguments = (ins
    Arg<TF_Tensor, [{The `input` to squeeze.}]>:$input,

    *   `parallel_for`: Add converters for `OneHot`, `LowerBound`, `UpperBound`.
    *   `parallel_for`: add converter for `BroadcastTo`.
    *   Add `pfor` converter for `Squeeze`.
    *   Add `RaggedTensor.placeholder()`.
    *   Add ragged tensor support to `tf.squeeze`.
    *   Update RaggedTensors to support int32 row_splits.
    *   Allow `LinearOperator.solve` to take a `LinearOperator`.

    "PAD",
    "UNIDIRECTIONAL_SEQUENCE_RNN",
    "GATHER",
    "BATCH_TO_SPACE_ND",
    "SPACE_TO_BATCH_ND",
    "TRANSPOSE",
    "MEAN",
    "SUB",
    "DIV",
    "SQUEEZE",
    "UNIDIRECTIONAL_SEQUENCE_LSTM",
    "STRIDED_SLICE",
    "BIDIRECTIONAL_SEQUENCE_RNN",
    "EXP",
    "TOPK_V2",
    "SPLIT",
    "LOG_SOFTMAX",
    "DELEGATE",