std::vector<MaybeParallelTensorOwned> outputs;
    outputs.reserve(t->num_tensors());
    for (int i = 0; i < t->num_tensors(); ++i) {
      TensorHandlePtr this_output(
          TFE_TensorHandleCopySharingTensor(t->tensor(i), status));
      outputs.emplace_back(std::move(this_output));
      if (TF_GetCode(status) != TF_OK) return result;
    }
    result.emplace(std::move(outputs));
    return result;
  }

  //
  // This is a no-op if the tensor is already being watched either from an
  // earlier call to `GradientTape::Watch` or being an output of an op with
  // watched inputs.
  void Watch(const AbstractTensorHandle*);
  // Records an operation with given inputs and outputs
  // on the tape and marks all its outputs as watched if at
  // least one input of the op is watched and has a trainable dtype.

  outputs.dir("$buildDir/generated/sources/idnaMappingTable")
  mainClass.set("okhttp3.internal.idn.GenerateIdnaMappingTableCode")
  args("$buildDir/generated/sources/idnaMappingTable")
  classpath = generateIdnaMappingTableConfiguration
}

kotlin {
  sourceSets {
    getByName("main") {
      kotlin.srcDir(copyKotlinTemplates.get().outputs)
      kotlin.srcDir(generateIdnaMappingTable.outputs)

			if !match {
				continue
			}
			for _, child := range children {
				outputs = append(outputs, fmt.Sprintf("%v%v%v -> %v", n, equality, k, child))
			}
		}
	}
	return outputs, len(outputs) > 0
}

// PrintListenerSummary prints a summary of the relevant listeners in the config dump to the ConfigWriter stdout
func (c *ConfigWriter) PrintListenerSummary(filter ListenerFilter) error {

	if [[ $? -eq 0 ]]; then
		echo "Outputs are consistent."
		break
	fi

	remaining_attempts=$((max_wait_attempts - attempt))
	if ((attempt >= max_wait_attempts)); then
		echo "Outputs remain inconsistent after $max_wait_attempts attempts. Exiting with error."
		exit 1
	else
		echo "Outputs are inconsistent. Waiting for $wait_interval seconds (attempt $attempt/$max_wait_attempts)."

                    final List<String> outputStrings = split(sides.get(1), ",");
                    outputs = new String[outputStrings.size()];
                    for (int i = 0; i < outputs.length; i++) {
                        outputs[i] = unescape(outputStrings.get(i)).trim();
                    }

                    if (inputs.length > 0 && outputs.length > 0) {
                        id++;

  if (TF_GetCode(status) != TF_OK) {
    cancellation_manager_->StartCancel();
    return;
  }
  unwrapped_results.resize(real_num_outputs);
  outputs->reserve(real_num_outputs);
  for (TFE_TensorHandle* unwrapped_result : unwrapped_results) {
    outputs->emplace_back(unwrapped_result);
  }
}

ParallelDevice::ParallelDevice(const std::vector<std::string>& devices,

   *
   *   A =[[0, 1],[1, 0]]
   *   B =[[1, 0],[0, 1]]
   *
   *   output1, output2, output3 = two_adds_and_mm(A, B)
   *
   * We expect outputs:
   *
   *   output1 = [[1, 1],[1, 1]]
   *   output2 = [[2, 0],[0, 2]]
   *   output3 = [[2, 2],[2, 2]]
   *
   */

  // Build eager context.
  TFE_ContextOptions* opts = TFE_NewContextOptions();

    override fun transform(outputs: TransformOutputs) {
        for (entry in parameters.keepClassesByArtifact) {
            val fileName = artifact.get().asFile.name
            if (fileName.startsWith(entry.key)) {
                val nameWithoutExtension = Files.getNameWithoutExtension(fileName)
                minify(artifact.get().asFile, entry.value, outputs.file("$nameWithoutExtension-min.jar"))
                return

    abstract Provider<FileSystemLocation> getArtifact()

    @Override
    void transform(TransformOutputs outputs) {
        File baselineJarsDirectory = artifact.get().asFile
        if (baselineJarsDirectory.name == 'gradle-jars') {
            baselineJarsDirectory.listFiles().each {
                outputs.file(it)
            }
        }
    }