# mypy: allow-untyped-defs
import torch

from torch._export.db.case import export_case
from torch.export import Dim

x = torch.randn(3, 2)
dim1_x = Dim("dim1_x")

@export_case(
    example_inputs=(x,),
    tags={"torch.dynamic-shape"},
    dynamic_shapes={"x": {1: dim1_x}},
)
class ScalarOutput(torch.nn.Module):
    """
    Returning scalar values from the graph is supported, in addition to Tensor
    outputs. Symbolic shapes are captured and rank is specialized.
    """
    def __init__(self):
        super().__init__()

    def forward(self, x):
        return x.shape[1] + 1