}

def TF_ConcatOp : TF_Op<"Concat", [Pure]> {
  let summary = "Concatenates tensors along one dimension.";

  let arguments = (ins
    Arg<TF_Int32Tensor, [{0-D.  The dimension along which to concatenate.  Must be in the
range [0, rank(values)).}]>:$concat_dim,
    Arg<Variadic<TF_Tensor>, [{The `N` Tensors to concatenate. Their ranks and types must match,

		1  .  X: 42
		2  }`},
	{struct{ X, Y int }{42, 991},
		`0  struct { X int; Y int } {
		1  .  X: 42
		2  .  Y: 991
		3  }`},
}

// Split s into lines, trim whitespace from all lines, and return
// the concatenated non-empty lines.
func trim(s string) string {
	lines := strings.Split(s, "\n")
	i := 0
	for _, line := range lines {
		line = strings.TrimSpace(line)
		if line != "" {
			lines[i] = line
			i++
		}
	}

    CharSource concatenated = CharSource.concat(cycle);

    String expected = "abcdabcd";

    // read the first 8 chars manually, since there's no equivalent to ByteSource.slice
    // TODO(cgdecker): Add CharSource.slice?
    StringBuilder builder = new StringBuilder();
    Reader reader = concatenated.openStream(); // no need to worry about closing

        then:
        DaemonExpirationResult result = agg.checkExpiration()
        result.status == DO_NOT_EXPIRE
        result.reason == null
    }

    def "doesn't concatenate a null reason"() {
        given:
        AllDaemonExpirationStrategy agg = new AllDaemonExpirationStrategy([c1, c2])

        when:
        1 * c1.checkExpiration() >> { new DaemonExpirationResult(GRACEFUL_EXPIRE, null) }

    /**
     * Adds an output entry to the group.
     */
    public void addOutput(String output) {
        outputs.add(output);
    }

    /**
     * Returns concatenated non-empty output entries.
     */
    public String getOutput() {
        List<String> nonEmptyOutputs = filter(outputs, string -> !string.equals(""));
        return join("\n", nonEmptyOutputs);
    }

    /**

  %2 = "stablehlo.concatenate"(%0, %1) {dimension = 0 : i64} : (tensor<?xf32>, tensor<?xf32>) -> tensor<?xf32>
  %3 = "quantfork.stats"(%2) {layerStats = dense<[-0.83811146, 2.4960899]> : tensor<2xf32>} : (tensor<?xf32>) -> tensor<?xf32>
  %4 = "quantfork.stats"(%arg2) {layerStats = dense<[-1.5726943, 1.07351148]> : tensor<2xf32>} : (tensor<?xf32>) -> tensor<?xf32>

    ): FirLiteralExpression? {
        val concatenated = buildString {
            for (arg in stringConcatenationCall.arguments) {
                val evaluated = evaluate(arg) ?: return null
                append(evaluated.value.toString())
            }
        }

        return ConstantValueKind.String.toLiteralExpression(stringConcatenationCall.source, concatenated)
    }

    private fun evaluateFunctionCall(

   * position + 8. The array must have at least 8 bytes from offset (inclusive).
   *
   * @param input the input bytes
   * @param offset the offset into the array at which to start
   * @return a long of a concatenated 8 bytes
   */
  static long load64(byte[] input, int offset) {
    // We don't want this in production code as this is the most critical part of the loop.
    assert input.length >= offset + 8;

// allowed.
func.func @parallel_execute_mismatched_output_types() {
  "tf_device.parallel_execute"() ({
// expected-error@-1 {{'tf_device.parallel_execute' op output types must be a concatenated list of output types for each regions.}}
    %0 = "tf.opA"() : () -> (tensor<*xi1>)
    %1 = "tf.opB"() : () -> (tensor<*xi32>)
    tf_device.return %0, %1 : tensor<*xi1>, tensor<*xi32>
  },
  {

	_, tag, digest, err := parsers.ParseImageName(image)
	if err != nil {
		return "", err
	}
	// we just concatenate the image name with the default tag here instead
	if len(digest) == 0 && len(tag) > 0 && !strings.HasSuffix(image, ":"+tag) {
		// we just concatenate the image name with the default tag here instead
		// of using dockerref.WithTag(named, ...) because that would cause the