python.assert

dynamic_shape_assert

Примечание

Уровень поддержки: SUPPORTED

Исходный код:

# mypy: allow-untyped-defs
import torch

class DynamicShapeAssert(torch.nn.Module):
    """
    A basic usage of python assertion.
    """

    def forward(self, x):
        # assertion with error message
        assert x.shape[0] > 2, f"{x.shape[0]} is greater than 2"  # noqa: S101
        # assertion without error message
        assert x.shape[0] > 1  # noqa: S101
        return x

example_args = (torch.randn(3, 2),)
tags = {"python.assert"}
model = DynamicShapeAssert()


torch.export.export(model, example_args)

Результат:

ExportedProgram:
    class GraphModule(torch.nn.Module):
        def forward(self, x: "f32[3, 2]"):
            return (x,)

Graph signature:
    # inputs
    x: USER_INPUT

    # outputs
    x: USER_OUTPUT

Range constraints: {}

list_contains

Примечание

Теги: torch.dynamic-shape, python.assert, python.data-structure

Уровень поддержки: SUPPORTED

Исходный код:

# mypy: allow-untyped-defs
import torch

class ListContains(torch.nn.Module):
    """
    List containment relation can be checked on a dynamic shape or constants.
    """

    def forward(self, x):
        assert x.size(-1) in [6, 2]  # noqa: S101
        assert x.size(0) not in [4, 5, 6]  # noqa: S101
        assert "monkey" not in ["cow", "pig"]  # noqa: S101
        return x + x

example_args = (torch.randn(3, 2),)
tags = {"torch.dynamic-shape", "python.data-structure", "python.assert"}
model = ListContains()


torch.export.export(model, example_args)

Результат:

ExportedProgram:
    class GraphModule(torch.nn.Module):
        def forward(self, x: "f32[3, 2]"):
                add: "f32[3, 2]" = torch.ops.aten.add.Tensor(x, x);  x = None
            return (add,)

Graph signature:
    # inputs
    x: USER_INPUT

    # outputs
    add: USER_OUTPUT

Range constraints: {}

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https://docs.pytorch.org/docs/2.14/generated/exportdb/python.assert.html