CHECK_EQ(TF_OK, TF_GetCode(status_)) << TF_Message(status_);

  // Infer shape when everything is known.
  CheckOutputShapes(matmul_op,
                    /*input_shapes*/ {make_shape({3, 2}), make_shape({2, 4})},
                    /*input_tensors*/ {},
                    /*expected_shape*/ make_shape({3, 4}));

  // Infer shape when second operand has unknown shape.
  CheckOutputShapes(matmul_op,

    std::vector<PartialTensorShape> shapes;
    shapes.reserve(num_values);
    for (int i = 0; i < num_values; ++i) {
      if (num_dims[i] < 0) {
        shapes.emplace_back();
      } else {
        shapes.emplace_back(absl::Span<const int64_t>(
            reinterpret_cast<const int64_t*>(dims[i]), num_dims[i]));
      }
    }
    op_->node_builder.Attr(attr_name, shapes);
    return absl::OkStatus();
  }

    TF_ShapeAndTypeList** shape_list_array, int num_items);

// Infer shapes for the given `op`. The arguments mimic the arguments of the
// `shape_inference::InferenceContext` constructor. Note the following:
//   - The inputs of the `op` are not used for shape inference. So, it is
//     OK to not have the inputs properly set in `op`. See `input_tensors`
//     if you want shape inference to consider the input tensors of the
//     op for shape inference.

        GsaConfigParser parser = new GsaConfigParser();

        assertEquals("", parser.escape("# comment"));
        assertEquals("^\\Qtest\\E$", parser.escape("^test$"));
        assertEquals("^\\Qtest\\E", parser.escape("^test"));
        assertEquals("\\Qtest\\E$", parser.escape("test$"));
        assertEquals("\\Qtest\\E", parser.escape("test"));
    }

    @Test
    public void test_unescape() {

    ShapeHandle shape_handle = c.output(i);
    TF_ShapeAndType& shape = output_shapes_result->items[i];
    shape.num_dims = c.Rank(shape_handle);
    if (shape.num_dims == InferenceContext::kUnknownRank) {
      shape.dims = nullptr;
      continue;
    }
    shape.dims = new int64_t[shape.num_dims];
    for (size_t j = 0; j < shape.num_dims; ++j) {
      shape.dims[j] = c.Value(c.Dim(shape_handle, j));
    }
  }

  int version = TFE_CUSTOM_DEVICE_VERSION;

  // Computes the rank of the tensor handle.
  //
  // Shapes are specified via callbacks because retrieving the shape of a tensor
  // is a blocking operation for async eager; custom devices should avoid
  // retrieving shapes of tensors they wrap until the custom device tensor's
  // shape is explicitly requested where possible.
  int (*num_dims)(void* data, TF_Status* status);

            }

            @Override
            public boolean hasConditionQuery() {
                return conditions != null && !conditions.isEmpty();
            }

        }).escape(escape).build();
    }

    // Additional test methods for improved coverage

    @Test
    public void test_conditions_filetype() {
        final String k = "filetype";

		t.Errorf("Table with escape character, got %v", r.Statement.SQL.String())
	}

	r = dryDB.Table("user as u").Select("name").Find(&User{}).Statement
	if !regexp.MustCompile("SELECT .name. FROM user as u WHERE .u.\\..deleted_at. IS NULL").MatchString(r.Statement.SQL.String()) {
		t.Errorf("Table with escape character, got %v", r.Statement.SQL.String())
	}

    }

    /**
     * Sets whether to escape special characters in queries.
     * This method follows the builder pattern for method chaining.
     *
     * @param escape true to enable escaping, false to disable
     * @return this QueryStringBuilder instance for method chaining
     */
    public QueryStringBuilder escape(final boolean escape) {
        this.escape = escape;
        return this;
    }

// original framework of destruction, and this context will be deleted also.
struct TfDlManagedTensorCtx {
  TensorReference reference;
  std::vector<int64_t> shape;
  std::vector<int64_t> strides;
  DLManagedTensor tensor;

  explicit TfDlManagedTensorCtx(const TensorReference& ref) : reference(ref) {}
};

// Gets tensor from eager tensor handle.