return ArraysAreCastCompatible(inferred, actual);
    }
  }];
}

def TF_LogSoftmaxOp : TF_Op<"LogSoftmax", [Pure, TF_SameOperandsAndResultTypeResolveRef]> {
  let summary = "Computes log softmax activations.";

  let description = [{
For each batch `i` and class `j` we have

    logsoftmax[i, j] = logits[i, j] - log(sum(exp(logits[i])))
  }];

  let arguments = (ins

    stateless and do not touch any resources.
*   Refactors code in Quant8 LSTM support to reduce TFLite binary size.
*   Add support of local soft device placement for eager op.
*   Add HW acceleration support for `LogSoftMax`.
*   Added a function `nested_value_rowids` for ragged tensors.
*   Add guard to avoid acceleration of L2 Normalization with input rank != 4
*   Add `tf.math.cumulative_logsumexp operation`.
*   Add `tf.ragged.stack`.