}

void TFE_ContextAddFunctionDef(TFE_Context* ctx,
                               const char* serialized_function_def, size_t size,
                               TF_Status* status) {
  tensorflow::FunctionDef function_def;
  if (!function_def.ParseFromString(
          absl::string_view(serialized_function_def, size))) {
    status->status =
        tensorflow::errors::InvalidArgument("Invalid FunctionDef proto");
    return;
  }

            assertEquals(24, ServerMessageBlock2.size8(17));
        }

        @Test
        @DisplayName("Should calculate size8 with alignment")
        void testSize8WithAlignment() {
            assertEquals(8, ServerMessageBlock2.size8(8, 0));
            // size8(10, 2): rem = 10%8 - 2 = 2 - 2 = 0, returns 10
            assertEquals(10, ServerMessageBlock2.size8(10, 2));

    assertEquals(expectedSize, multimap.size());

    int size = 0;
    for (Entry<K, V> entry : multimap.entries()) {
      assertTrue(multimap.containsEntry(entry.getKey(), entry.getValue()));
      size++;
    }
    assertEquals(expectedSize, size);

    int size2 = 0;
    for (Entry<K, Collection<V>> entry2 : multimap.asMap().entrySet()) {
      size2 += entry2.getValue().size();
    }
    assertEquals(expectedSize, size2);

Ian Lance Taylor <******@****.***> 1765577893 -0800

    std::vector<TF_Output> tf_outputs(inputs.size());
    for (int i = 0; i < inputs.size(); i++) {
      GraphTensor* t = dyn_cast<GraphTensor>(inputs[i]);
      if (!t) {
        return tensorflow::errors::InvalidArgument(
            "Unable to cast input to GraphTensor");
      }
      tf_outputs[i] = t->output_;
    }
    TF_AddInputList(op_.get(), tf_outputs.data(), tf_outputs.size());
    return absl::OkStatus();
  }

        assertEquals(expectedSize, request.size());
    }

    @Test
    @DisplayName("Test size calculation with empty path")
    void testSizeWithEmptyPath() {
        request = new Smb2CreateRequest(mockConfig, "");

        int expectedSize = Smb2Constants.SMB2_HEADER_LENGTH + 56;
        expectedSize += 8; // size8(1) - empty name gets 1 byte
        expectedSize = ((expectedSize + 7) / 8) * 8; // size8(size)

  std::vector<int64_t> input_ids(inputs.size());
  std::vector<tensorflow::DataType> input_dtypes(inputs.size());
  for (int i = 0; i < inputs.size(); i++) {
    input_ids[i] = ToId(inputs[i]);
    input_dtypes[i] = inputs[i]->DataType();
  }
  std::vector<TapeTensor> tape_tensors;
  tape_tensors.reserve(outputs.size());
  for (auto t : outputs) {
    tape_tensors.push_back(TapeTensor(t));
  }

Joe Tsai <******@****.***> 1503528984 -0700

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  private CollectSpliterators() {}

  static <T extends @Nullable Object> Spliterator<T> indexed(
      int size, int extraCharacteristics, IntFunction<T> function) {
    return indexed(size, extraCharacteristics, function, null);
  }

  static <T extends @Nullable Object> Spliterator<T> indexed(
      int size,
      int extraCharacteristics,
      IntFunction<T> function,
      @Nullable Comparator<? super T> comparator) {