python.object-model
=======================
model_attr_mutation
^^^^^^^^^^^^^^^^^^^

.. note::

    Tags: :doc:`python.object-model <python.object-model>`

    Support Level: SUPPORTED

Original source code:

.. code-block:: python

    # mypy: allow-untyped-defs
    import torch
    
    
    class ModelAttrMutation(torch.nn.Module):
        """
        Attribute mutation raises a warning. Covered in the test_export.py test_detect_leak_strict test.
        """
    
        def __init__(self) -> None:
            super().__init__()
            self.attr_list = [torch.randn(3, 2), torch.randn(3, 2)]
    
        def recreate_list(self):
            return [torch.zeros(3, 2), torch.zeros(3, 2)]
    
        def forward(self, x):
            self.attr_list = self.recreate_list()
            return x.sum() + self.attr_list[0].sum()
    
    
    example_args = (torch.randn(3, 2),)
    tags = {"python.object-model"}
    model = ModelAttrMutation()
    

    torch.export.export(model, example_args)

Result:

.. code-block::

    ExportedProgram:
        class GraphModule(torch.nn.Module):
            def forward(self, x: "f32[3, 2]"):
                    zeros: "f32[3, 2]" = torch.ops.aten.zeros.default([3, 2], device = device(type='cpu'), pin_memory = False)
                zeros_1: "f32[3, 2]" = torch.ops.aten.zeros.default([3, 2], device = device(type='cpu'), pin_memory = False);  zeros_1 = None
        
                    sum_1: "f32[]" = torch.ops.aten.sum.default(x);  x = None
                sum_2: "f32[]" = torch.ops.aten.sum.default(zeros);  zeros = None
                add: "f32[]" = torch.ops.aten.add.Tensor(sum_1, sum_2);  sum_1 = sum_2 = None
                return (add,)
        
    Graph signature: 
        # inputs
        x: USER_INPUT
        
        # outputs
        add: USER_OUTPUT
        
    Range constraints: {}
    


optional_input
^^^^^^^^^^^^^^

.. note::

    Tags: :doc:`python.object-model <python.object-model>`

    Support Level: SUPPORTED

Original source code:

.. code-block:: python

    # mypy: allow-untyped-defs
    import torch
    from torch._export.db.case import SupportLevel
    
    
    class OptionalInput(torch.nn.Module):
        """
        Tracing through optional input is not supported yet
        """
    
        def forward(self, x, y=torch.randn(2, 3)):
            if y is not None:
                return x + y
            return x
    
    
    example_args = (torch.randn(2, 3),)
    tags = {"python.object-model"}
    support_level = SupportLevel.SUPPORTED
    model = OptionalInput()
    

    torch.export.export(model, example_args)

Result:

.. code-block::

    ExportedProgram:
        class GraphModule(torch.nn.Module):
            def forward(self, c_dict_type_l__self______dict_____forward_____defaults___0: "f32[2, 3]", x: "f32[2, 3]"):
                    add: "f32[2, 3]" = torch.ops.aten.add.Tensor(x, c_dict_type_l__self______dict_____forward_____defaults___0);  x = c_dict_type_l__self______dict_____forward_____defaults___0 = None
                return (add,)
        
    Graph signature: 
        # inputs
        c_dict_type_l__self______dict_____forward_____defaults___0: CONSTANT_TENSOR target='dict_type_L__self______dict_____forward_____defaults___0' persistent=True
        x: USER_INPUT
        
        # outputs
        add: USER_OUTPUT
        
    Range constraints: {}