.forEach(attrName -> OptionalUtil.ofNullable(attributes.get(attrName)).filter(StringUtil::isNotBlank).ifPresent(s -> {
                        try {
                            DfTypeUtil.toLong(s);
                        } catch (final NumberFormatException e) {
                            consumer.accept(attrName);
                        }
                    }));

  int64_t total_size;
} TF_AttrMetadata;

// Returns metadata about the value of the attribute `attr_name` of `oper`.
TF_CAPI_EXPORT extern TF_AttrMetadata TF_OperationGetAttrMetadata(
    TF_Operation* oper, const char* attr_name, TF_Status* status);

// Fills in `value` with the value of the attribute `attr_name`.  `value` must
// point to an array of length at least `max_length` (ideally set to

    func_ = TF_FunctionImportFunctionDef(buf.data(), buf.size(), s_);
    ASSERT_EQ(TF_OK, TF_GetCode(s_)) << TF_Message(s_);
  }

  void GetAttr(const char* attr_name, AttrValue* out_attr) {
    TF_Buffer* attr_buf = TF_NewBuffer();
    TF_FunctionGetAttrValueProto(func_, attr_name, attr_buf, s_);
    ASSERT_TRUE(out_attr->ParseFromArray(attr_buf->data, attr_buf->length));
    TF_DeleteBuffer(attr_buf);
  }

// That will require setting up the tensorflow build with gmock.
#define EXPECT_TF_META(attr_name, expected_list_size, expected_type, \
                       expected_total_size)                          \
  do {                                                               \
    auto m = TF_OperationGetAttrMetadata(oper, attr_name, s_);       \
    EXPECT_EQ(TF_OK, TF_GetCode(s_)) << TF_Message(s_);              \