allErrors = append(allErrors, field.Invalid(path, "<value omitted>", "at least one trust anchor must be provided"))
	}

	for _, indices := range blockDedupe {
		if len(indices) > 1 {
			allErrors = append(allErrors, field.Invalid(path, "<value omitted>", fmt.Sprintf("duplicate trust anchor (indices %v)", indices)))
		}
	}

	return allErrors

}

// Represents an op type and its operand indices that should be "compile time
// constant" from the XLA compiler's point of view.
template <typename OpT, int... OperandIdx>
struct CompileTimeConstantOperand {
  static_assert(
      sizeof...(OperandIdx) > 0,
      "CompileTimeConstantOperand should have at least one operand index.");

  using OpType = OpT;

  // Returns the indices of operands that should be compile time constants.

//===----------------------------------------------------------------------===//

// Here, $params and $indices needs to be ranked so that $axis and $batch_dims
// attributes can be converted from TensorFlow axis format supporting negative
// indexing to the HLO format.
def LegalizeGatherV2 :
  Pat<(TF_GatherV2Op AnyRankedTensor:$params, AnyRankedTensor:$indices,
        (ConstantLikeMatcher ElementsAttr:$axis), $batch_dims),

  //     to segment the indices array, each segment corresponds to one element
  //     in the previous dimension. array_indices represents the index of the
  //     non-zero elements within this dimension (as those in the CSR matrix
  //     format, where the first array is row pointers and the second array is
  //     column indices).
  dense_size:int;
  array_segments:SparseIndexVector;

  // Successful gather.
  {
    const float params[4] = {1, 2, 3, 4};
    std::copy(params + 0, params + 4, gather.arg0_data());
    const int32 indices[2] = {1, 3};
    std::copy(indices + 0, indices + 2, gather.arg1_data());
    EXPECT_TRUE(gather.Run());
    EXPECT_EQ(gather.error_msg(), "");
    const float results[2] = {2, 4};
    for (int i = 0; i < 2; ++i) {

defm : LiftCompositeOpsWithActivation<TF_Relu6Op, "relu6">;

def LiftGather : Pat<
  (TF_GatherV2Op:$res $params, $indices, $axis, $batch_dims),
  (LiftAsTFPartitionedCall<"composite_gather_fn">
    (ArgumentList $params, $indices, $axis),
    (ResultList $res),
    (NamedAttributeList
      (NamedAttr<"batch_dims"> $batch_dims))),

        List<String> unexpectedInputs = inputs.collect { formatInputForAssert(it) }.reverse()
        for (int i in expectedInputs.indices.reverse()) {
            def expectedInput = expectedInputs[i]
            for (int j in unexpectedInputs.indices) {
                if (expectedInput.matches(unexpectedInputs[j])) {
                    expectedInputs.removeAt(i)
                    unexpectedInputs.removeAt(j)

  // CHECK-NOT: tf_mlrt.executeop(
  // CHECK: [[device:%.*]] = tf_mlrt_tpu.get_tpu_host_device
  // CHECK: [[var:%.*]] = tf_mlrt.executeop.device([[device]]){{.*}}op: \22ResourceGather\22
  // CHECK: [[rendezvous_key_base:%.*]] = tf_mlrt_tpu.compile_and_execute([[var]])

	// Output:
	// [["ab" ""]]
	// [["axxb" "xx"]]
	// [["ab" ""] ["axb" "x"]]
	// [["axxb" "xx"] ["ab" ""]]
}

func ExampleRegexp_FindAllStringSubmatchIndex() {
	re := regexp.MustCompile(`a(x*)b`)
	// Indices:
	//    01234567   012345678
	//    -ab-axb-   -axxb-ab-
	fmt.Println(re.FindAllStringSubmatchIndex("-ab-", -1))
	fmt.Println(re.FindAllStringSubmatchIndex("-axxb-", -1))

          clEnumValN(OpSet::UNIFORM_QUANTIZED, "UNIFORM_QUANTIZED",
                     "Uses TF Uniform Quantized ops"))};
};

// Check if given indices in `val1` has same number of elements as given
// indices in `val2`.
bool HasEqualElementSize(Value val1, Value val2, ArrayRef<int> val1_indices,
                         ArrayRef<int> val2_indices) {