GREATER_EQUAL = 62,
  LESS_EQUAL = 63,
  SELECT = 64,
  SLICE = 65,
  SIN = 66,
  TRANSPOSE_CONV = 67,
  SPARSE_TO_DENSE = 68,
  TILE = 69,
  EXPAND_DIMS = 70,
  EQUAL = 71,
  NOT_EQUAL = 72,
  LOG = 73,
  SUM = 74,
  SQRT = 75,
  RSQRT = 76,
  SHAPE = 77,
  POW = 78,
  ARG_MIN = 79,
  FAKE_QUANT = 80,
  REDUCE_PROD = 81,
  REDUCE_MAX = 82,
  PACK = 83,

// CHECK:  tfl.floor_div %arg0, %arg1 : tensor<8x16xi16>
// CHECK:  return
}

func.func @not_equal(%arg0: tensor<8x16xf32>, %arg1: tensor<8x16xf32>) -> tensor<8x16xi1> {
  %0 = "tf.NotEqual"(%arg0, %arg1) : (tensor<8x16xf32>, tensor<8x16xf32>) -> tensor<8x16xi1>
  func.return %0 : tensor<8x16xi1>

// CHECK-LABEL: not_equal
// CHECK:  tfl.not_equal(%arg0, %arg1) : (tensor<8x16xf32>, tensor<8x16xf32>) -> tensor<8x16xi1>
// CHECK:  return
}

  GREATER_EQUAL = 62,
  LESS_EQUAL = 63,
  SELECT = 64,
  SLICE = 65,
  SIN = 66,
  TRANSPOSE_CONV = 67,
  SPARSE_TO_DENSE = 68,
  TILE = 69,
  EXPAND_DIMS = 70,
  EQUAL = 71,
  NOT_EQUAL = 72,
  LOG = 73,
  SUM = 74,
  SQRT = 75,
  RSQRT = 76,
  SHAPE = 77,
  POW = 78,
  ARG_MIN = 79,
  FAKE_QUANT = 80,
  REDUCE_PROD = 81,
  REDUCE_MAX = 82,
  PACK = 83,

  );
}

def TFL_NotEqualOp : TFL_Op<"not_equal", [
    TFL_OperandsHaveSameShapesOrBroadcastableShape<[0, 1], 4>,
    ComparisonOpSameElementTypeConstraint,
    ResultsBroadcastableShape,
    Commutative,
    Pure]> {
  let summary = "Not_equal operator";

  let description = [{
    Element-wise not_equal operation.
  }];

  let arguments = (

```python
    # Apply function (increments x_i) on elements for which a certain condition
    # apply (x_i != -1 in this example).
    x=tf.constant([0.1, -1., 5.2, 4.3, -1., 7.4])
    condition_mask=tf.not_equal(x,tf.constant(-1.))
    partitioned_data = tf.dynamic_partition(
        x, tf.cast(condition_mask, tf.int32) , 2)
    partitioned_data[1] = partitioned_data[1] + 1.0
    condition_indices = tf.dynamic_partition(

        `tf.floor`, `tf.greater`, `tf.greater_equal`, `tf.less`,
        `tf.less_equal`, `tf.log`, `tf.logp1`, `tf.logical_and`,
        `tf.logical_not`, `tf.logical_or`, `tf.maximum`, `tf.minimum`,
        `tf.not_equal`, `tf.sin`, `tf.sinh`, `tf.tan`
    *   Deprecate `tf.data.Dataset.shard`.
    *   Deprecate `saved_model.loader.load` which is replaced by
        `saved_model.load` and `saved_model.main_op`, which will be replaced by

    "GREATER_EQUAL",
    "LESS_EQUAL",
    "SELECT",
    "SLICE",
    "SIN",
    "TRANSPOSE_CONV",
    "SPARSE_TO_DENSE",
    "TILE",
    "EXPAND_DIMS",
    "EQUAL",
    "NOT_EQUAL",
    "LOG",
    "SUM",
    "SQRT",
    "RSQRT",
    "SHAPE",
    "POW",
    "ARG_MIN",
    "FAKE_QUANT",
    "REDUCE_PROD",
    "REDUCE_MAX",
    "PACK",
    "LOGICAL_OR",