Tracing through __getitem__ -> __len__ for ModuleList fails.

[laithsakka]

python test/dynamo/test_dynamic_shapes.py -k DynamicShapesNNModuleTests.test_modulelist_dynamic_shapes

cc @ezyang @msaroufim @bdhirsh @anijain2305 @chauhang @voznesenskym @penguinwu @EikanWang @jgong5 @Guobing-Chen @XiaobingSuper @zhuhaozhe @blzheng @wenzhe-nrv @jiayisunx @chenyang78 @kadeng

[laithsakka]

related topic:
https://pytorch.org/docs/stable/generated/torch.nn.ModuleList.html

[laithsakka]

Ok I looked at this, and here is whats happening:
The module we are tracing is:

class ModuleList(torch.nn.Module):
    def __init__(self):
        super().__init__()
        self.layers = torch.nn.ModuleList(
            [
                torch.nn.Linear(10, 10),
            ]
        )

    def forward(self, x):
        for idx, layer in enumerate(self.layers[::-1]):
            # pass
            x = layer(x) * idx

        return x

1. when inlining disabled, when we trace through

 for idx, layer in enumerate(self.layers[::-1]):

we need to call getitem but this is special handled in

pytorch/torch/_dynamo/variables/nn_module.py

Line 600 in 796dff7

elif name == "__getitem__":

and we do not trace through getitem for ModuleList.

2. When we enable we trace through getItem which ends up calling
   def len(self) -> int:
   

   pytorch/torch/nn/modules/container.py

   Line 140 in 796dff7

   def __len__(self) -> int:

and we fail to trace through the length call.

[laithsakka]

basically we fail exactly here:

  File "/data/users/lsakka/pytorch/pytorch/torch/_dynamo/variables/functions.py", line 341, in call_function
    return super().call_function(tx, args, kwargs)
  File "/data/users/lsakka/pytorch/pytorch/torch/_dynamo/variables/functions.py", line 293, in call_function
    return super().call_function(tx, args, kwargs)
  File "/data/users/lsakka/pytorch/pytorch/torch/_dynamo/variables/functions.py", line 90, in call_function
    return tx.inline_user_function_return(self, [*self.self_args(), *args], kwargs)
  File "/data/users/lsakka/pytorch/pytorch/torch/_dynamo/symbolic_convert.py", line 743, in inline_user_function_return
    return InliningInstructionTranslator.inline_call(self, fn, args, kwargs)
  File "/data/users/lsakka/pytorch/pytorch/torch/_dynamo/symbolic_convert.py", line 2447, in inline_call
    return cls.inline_call_(parent, func, args, kwargs)
  File "/data/users/lsakka/pytorch/pytorch/torch/_dynamo/symbolic_convert.py", line 2563, in inline_call_
    tracer.run()
  File "/data/users/lsakka/pytorch/pytorch/torch/_dynamo/symbolic_convert.py", line 884, in run
    while self.step():
  File "/data/users/lsakka/pytorch/pytorch/torch/_dynamo/symbolic_convert.py", line 799, in step
    self.dispatch_table[inst.opcode](self, inst)
  File "/data/users/lsakka/pytorch/pytorch/torch/_dynamo/symbolic_convert.py", line 494, in wrapper
    return inner_fn(self, inst)
  File "/data/users/lsakka/pytorch/pytorch/torch/_dynamo/symbolic_convert.py", line 1253, in CALL_FUNCTION
    self.call_function(fn, args, {})
  File "/data/users/lsakka/pytorch/pytorch/torch/_dynamo/symbolic_convert.py", line 737, in call_function
    self.push(fn.call_function(self, args, kwargs))
  File "/data/users/lsakka/pytorch/pytorch/torch/_dynamo/variables/builtin.py", line 948, in call_function
    return handler(tx, args, kwargs)
  File "/data/users/lsakka/pytorch/pytorch/torch/_dynamo/variables/builtin.py", line 832, in builtin_dipatch
    rv = fn(tx, args, kwargs)
  File "/data/users/lsakka/pytorch/pytorch/torch/_dynamo/variables/builtin.py", line 750, in call_self_handler
    result = self_handler(tx, *args, **kwargs)
  File "/data/users/lsakka/pytorch/pytorch/torch/_dynamo/variables/builtin.py", line 1347, in call_len
    return args[0].call_method(tx, "__len__", args[1:], kwargs)
  File "/data/users/lsakka/pytorch/pytorch/torch/_dynamo/variables/misc.py", line 694, in call_method
    return super().call_method(tx, name, args, kwargs)
  File "/data/users/lsakka/pytorch/pytorch/torch/_dynamo/variables/base.py", line 320, in call_method
    unimplemented(f"call_method {self} {name} {args} {kwargs}")
  File "/data/users/lsakka/pytorch/pytorch/torch/_dynamo/exc.py", line 216, in unimplemented
    raise Unsupported(msg)
torch._dynamo.exc.Unsupported: call_method GetAttrVariable(UnspecializedNNModuleVariable(ModuleList), _modules) __len__ () {}

V0516 16:12:16.275000 140569933899584 torch/_dynamo/symbolic_convert.py:2535] [0/0] INLINING <code object __len__ at 0x7fd8f216a4a0, file "/data/users/lsakka/pytorch/pytorch/torch/nn/modules/container.py", line 311>, inlined according trace_rules.lookup MOD_INLINELIST
V0516 16:12:16.275000 140569933899584 torch/_dynamo/symbolic_convert.py:769] [0/0] [__trace_source] TRACE starts_line /data/users/lsakka/pytorch/pytorch/torch/nn/modules/container.py:313 in __len__ (ModuleList.__len__) (inline depth: 5)
V0516 16:12:16.275000 140569933899584 torch/_dynamo/symbolic_convert.py:769] [0/0] [__trace_source]             return len(self._modules)
V0516 16:12:16.276000 140569933899584 torch/_dynamo/symbolic_convert.py:792] [0/0] [__trace_bytecode] TRACE LOAD_GLOBAL len []
V0516 16:12:16.276000 140569933899584 torch/_dynamo/symbolic_convert.py:792] [0/0] [__trace_bytecode] TRACE LOAD_FAST self [BuiltinVariable()]
V0516 16:12:16.276000 140569933899584 torch/_dynamo/symbolic_convert.py:792] [0/0] [__trace_bytecode] TRACE LOAD_ATTR _modules [BuiltinVariable(), UnspecializedNNModuleVariable()]
V0516 16:12:16.277000 140569933899584 torch/_dynamo/symbolic_convert.py:792] [0/0] [__trace_bytecode] TRACE CALL_FUNCTION 1 [BuiltinVariable(), GetAttrVariable()]

    def call_method(
        self,
        tx,
        name,
        args: "List[VariableTracker]",
        kwargs: "Dict[str, VariableTracker]",
    ) -> "VariableTracker":
        if name == "__len__" and self.has_unpack_var_sequence(tx):
            assert not (args or kwargs)
            return variables.ConstantVariable.create(len(self.unpack_var_sequence(tx)))
        elif (
            name == "__getattr__"
            and len(args) == 1
            and args[0].is_python_constant()
            and not kwargs
        ):
            return self.var_getattr(tx, args[0].as_python_constant())
        unimplemented(f"call_method {self} {name} {args} {kwargs}")

[laithsakka]

I think the issue is that self._module is a dictionary but we represent that as GetAttrVariable instead of ConstDictVariable, but i do now know if we its constant and if we can use ConstDictVariable,

the type of _module is _modules: Dict[str, Module] # type: ignore[assignment]