python.assert

dynamic_shape_assert

Note

Tags: python.assert

Support Level: SUPPORTED

Original source code:

import torch



def dynamic_shape_assert(x):
    """
    A basic usage of python assertion.
    """
    # assertion with error message
    assert x.shape[0] > 2, f"{x.shape[0]} is greater than 2"
    # assertion without error message
    assert x.shape[0] > 1
    return x

Result:

ExportedProgram:
    class GraphModule(torch.nn.Module):
        def forward(self, arg0_1: f32[3, 2]):
            return (arg0_1,)

Graph Signature: ExportGraphSignature(parameters=[], buffers=[], user_inputs=['arg0_1'], user_outputs=['arg0_1'], inputs_to_parameters={}, inputs_to_buffers={}, buffers_to_mutate={}, backward_signature=None, assertion_dep_token=None)
Symbol to range: {}

list_contains

Note

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

Support Level: SUPPORTED

Original source code:

import torch



def list_contains(x):
    """
    List containment relation can be checked on a dynamic shape or constants.
    """
    assert x.size(-1) in [6, 2]
    assert x.size(0) not in [4, 5, 6]
    assert "monkey" not in ["cow", "pig"]
    return x + x

Result:

ExportedProgram:
    class GraphModule(torch.nn.Module):
        def forward(self, arg0_1: f32[3, 2]):
            #
            add: f32[3, 2] = torch.ops.aten.add.Tensor(arg0_1, arg0_1);  arg0_1 = None
            return (add,)

Graph Signature: ExportGraphSignature(parameters=[], buffers=[], user_inputs=['arg0_1'], user_outputs=['add'], inputs_to_parameters={}, inputs_to_buffers={}, buffers_to_mutate={}, backward_signature=None, assertion_dep_token=None)
Symbol to range: {}