}\n\n    if (!button || button.hasAttribute('disabled') || button.classList.contains('disabled')) {\n      event.preventDefault() // work around Firefox bug #1540995\n    } else {\n      const inputBtn = button.querySelector(SELECTOR_INPUT)\n\n      if (inputBtn && (inputBtn.hasAttribute('disabled') || inputBtn.classList.contains('disabled'))) {\n        event.preventDefault() // work around Firefox bug #1540995\n        return\n      }\n\n      if (initialButton.tagName === 'INPUT' || button.tagName...

        readingList.add(toKatakana(text));
        return readingList;
    }

    protected String toKatakana(final String inputStr) throws IOException {
        final StringBuilder kanaBuf = new StringBuilder();

        final Reader rd = new StringReader(inputStr);
        try (TokenStream stream = createTokenStream(rd)) {
            if (stream == null) {
                throw new IOException("Invalid tokenizer.");

      @RetainedLocalRef
      ImmutableCollection<? extends ListenableFuture<? extends InputT>> localFutures = futures;
      ImmutableCollection<? extends Future<? extends InputT>> localFuturesOrNull =
          collectsValues ? localFutures : null;
      Runnable listener = () -> decrementCountAndMaybeComplete(localFuturesOrNull);
      for (ListenableFuture<? extends InputT> future : localFutures) {
        if (future.isDone()) {

  TFE_TensorHandle* input_eager = TestScalarTensorHandle(eager_ctx, 2.0f);
  TF_AbstractTensor* input_t =
      TF_CreateAbstractTensorFromEagerTensor(input_eager, status.get());
  ASSERT_EQ(TF_OK, TF_GetCode(status.get())) << TF_Message(status.get());

  TF_ExecuteOperation(fn_op, 1, &input_t, add_outputs, status.get());
  ASSERT_EQ(TF_OK, TF_GetCode(status.get())) << TF_Message(status.get());

	}
}

// TestSignV4TrimAll - tests the logic of TrimAll() function
func TestSignV4TrimAll(t *testing.T) {
	testCases := []struct {
		// Input.
		inputStr string
		// Expected result.
		result string
	}{
		{"本語", "本語"},
		{" abc ", "abc"},
		{" a b ", "a b"},
		{"a b ", "a b"},
		{"a  b", "a b"},
		{"a   b", "a b"},
		{"   a   b  c   ", "a b c"},

        float splits.
    *   `Conv2D`, `Conv2DBackpropInput`, `Conv2DBackpropFilter` now supports
        arbitrary dilations with GPU and cuDNNv6 support.
    *   `Estimator` now supports `Dataset`: `input_fn` can return a `Dataset`
        instead of `Tensor`s.
    *   Add `RevBlock`, a memory-efficient implementation of reversible residual
        layers.
    *   Reduce BFCAllocator internal fragmentation.