* Returns a defensive copy to prevent external modification.
     *
     * @return array of input sequences (defensive copy)
     */
    public String[] getInputs() {
        return inputs == null ? null : inputs.clone();
    }

    /**
     * Returns all input sequences joined with newline characters as a single string.

    /**
     * Gets the original input words.
     * Returns a defensive copy to prevent external modification.
     *
     * @return The original input words (defensive copy).
     */
    public String[] getInputs() {
        return inputs == null ? null : inputs.clone();
    }

    /**
     * Gets the input words as a newline-separated string.
     *
     * @return The input words as a string.
     */

    if (input_shape.num_dims == InferenceContext::kUnknownRank) {
      c.SetInput(i, c.UnknownShape());
      continue;
    }
    dims.reserve(input_shape.num_dims);
    for (int j = 0; j < input_shape.num_dims; ++j) {
      dims.push_back(c.MakeDim(input_shape.dims[j]));
    }
    c.SetInput(i, c.MakeShape(dims));
  }

  // TODO(bgogul): Handle input_tensors_as_shapes.

  for (mapping in mappings) {
    require(!mapping.spansSections)

    val section = mapping.section
    val rangeStart = mapping.rangeStart

    val sectionList = result.getOrPut(section) { mutableListOf() }

    sectionList +=
      when (mapping.type) {
        TYPE_MAPPED -> {
          run {
            val deltaMapping = inlineDeltaOrNull(mapping)

            File expectedOutputFile = useNativeExpanded
                ? new File(projectArtifact.expandedDistDir, "elasticsearch-" + bwcVersion.get() + "-SNAPSHOT")
                : projectArtifact.distFile;
            c.getInputs().file(new File(project.getBuildDir(), "refspec"));
            if (useNativeExpanded) {
                c.getOutputs().dir(expectedOutputFile);
            } else {
                c.getOutputs().files(expectedOutputFile);

        final Iterator<ImageReader> readers = ImageIO.getImageReaders(input);
        if (readers.hasNext()) {
            final ImageReader reader = readers.next();
            try {
                reader.setInput(input);
                final ImageReadParam param = reader.getDefaultReadParam();
                final int width = reader.getWidth(0);
                final int height = reader.getHeight(0);

    public Object convert(final TypeLiteral role, final String value) {
        if (value.trim().startsWith("<")) {
            try {
                final MXParser parser = new MXParser();
                parser.setInput(new StringReader(value));
                parser.nextTag();

                return parse(parser, role);
            } catch (final Exception e) {

}

extern int TFE_OpGetFlatInputCount(const TFE_Op* op, TF_Status* status) {
  return tensorflow::unwrap(op)->GetInputs().size();
}

extern TFE_TensorHandle* TFE_OpGetFlatInput(const TFE_Op* op, int index,
                                            TF_Status* status) {
  return tensorflow::wrap(tensorflow::unwrap(op)->GetInputs()[index]);
}

TF_AttrType TFE_OpGetAttrType(TFE_Op* op, const char* attr_name,

                options.setSeparateOutputDirs(false);
                options.setBackends(singletonList("html5"));
            });

            // TODO: Break the paths assumed here
            TaskInputs inputs = task.getInputs();
            inputs.files(extension.getCssFiles())
                .withPropertyName("manual")
                .withPathSensitivity(PathSensitivity.RELATIVE);
            inputs.dir("src/main/resources")

    enableTls()

    val testHandler =
      object : Handler() {
        val calls = mutableMapOf<String, AtomicInteger>()

        override fun publish(record: LogRecord) {
          calls
            .getOrPut(record.loggerName) { AtomicInteger(0) }
            .incrementAndGet()
        }

        override fun flush() {
        }

        override fun close() {
        }
      }.apply {