Open
Description
Bug Description
error when compile an LSTM model using torch tensorrt
To Reproduce
import os
import torch
import torch.nn as nn
import torch.nn.functional as F
import torch_tensorrt
os.environ['CUDA_VISIBLE_DEVICES']= '3'
model = nn.LSTM(60, 128, num_layers=4, batch_first=True, dropout=0.5, bidirectional=True)
model = model.eval().cuda()
trt_model = torch_tensorrt.compile(model,
inputs= [torch_tensorrt.Input((1,2,60)) ],
enabled_precisions= {torch_tensorrt.dtype.f16}
)
errors
[WARNING | root ]: Given dtype that does not have direct mapping to torch (dtype.unknown), defaulting to torch.float
---------------------------------------------------------------------------
RuntimeError Traceback (most recent call last)
Cell In[9], line 12
9 model = nn.LSTM(60, 128, num_layers=4, batch_first=True, dropout=0.5, bidirectional=True)
10 model = model.eval().cuda()
---> 12 trt_model = torch_tensorrt.compile(model,
13 inputs= [torch_tensorrt.Input((1,2,60)) ])
File [/usr/local/lib/python3.12/dist-packages/torch_tensorrt/_compile.py:286](http://34.72.49.31:8889/usr/local/lib/python3.12/dist-packages/torch_tensorrt/_compile.py#line=285), in compile(module, ir, inputs, arg_inputs, kwarg_inputs, enabled_precisions, **kwargs)
283 torchtrt_arg_inputs = prepare_inputs(arg_inputs)
284 torchtrt_kwarg_inputs = prepare_inputs(kwarg_inputs)
--> 286 exp_program = dynamo_trace(
287 module, torchtrt_arg_inputs, kwarg_inputs=torchtrt_kwarg_inputs, **kwargs
288 )
289 trt_graph_module = dynamo_compile(
290 exp_program,
291 arg_inputs=torchtrt_arg_inputs,
292 enabled_precisions=enabled_precisions_set,
293 **kwargs,
294 )
295 return trt_graph_module
File [/usr/local/lib/python3.12/dist-packages/torch_tensorrt/dynamo/_tracer.py:83](http://34.72.49.31:8889/usr/local/lib/python3.12/dist-packages/torch_tensorrt/dynamo/_tracer.py#line=82), in trace(mod, inputs, arg_inputs, kwarg_inputs, **kwargs)
81 dynamic_shapes = get_dynamic_shapes_args(mod, arg_inputs)
82 dynamic_shapes.update(get_dynamic_shapes_kwargs(kwarg_inputs))
---> 83 exp_program = export(
84 mod,
85 tuple(torch_arg_inputs),
86 kwargs=torch_kwarg_inputs,
87 dynamic_shapes=dynamic_shapes,
88 )
90 return exp_program
File [/usr/local/lib/python3.12/dist-packages/torch/export/__init__.py:368](http://34.72.49.31:8889/usr/local/lib/python3.12/dist-packages/torch/export/__init__.py#line=367), in export(mod, args, kwargs, dynamic_shapes, strict, preserve_module_call_signature)
362 if isinstance(mod, torch.jit.ScriptModule):
363 raise ValueError(
364 "Exporting a ScriptModule is not supported. "
365 "Maybe try converting your ScriptModule to an ExportedProgram "
366 "using `TS2EPConverter(mod, args, kwargs).convert()` instead."
367 )
--> 368 return _export(
369 mod,
370 args,
371 kwargs,
372 dynamic_shapes,
373 strict=strict,
374 preserve_module_call_signature=preserve_module_call_signature,
375 pre_dispatch=True,
376 )
File [/usr/local/lib/python3.12/dist-packages/torch/export/_trace.py:1038](http://34.72.49.31:8889/usr/local/lib/python3.12/dist-packages/torch/export/_trace.py#line=1037), in _log_export_wrapper.<locals>.wrapper(*args, **kwargs)
1031 else:
1032 log_export_usage(
1033 event="export.error.unclassified",
1034 type=error_type,
1035 message=str(e),
1036 flags=_EXPORT_FLAGS,
1037 )
-> 1038 raise e
1039 finally:
1040 _EXPORT_FLAGS = None
File [/usr/local/lib/python3.12/dist-packages/torch/export/_trace.py:1011](http://34.72.49.31:8889/usr/local/lib/python3.12/dist-packages/torch/export/_trace.py#line=1010), in _log_export_wrapper.<locals>.wrapper(*args, **kwargs)
1009 try:
1010 start = time.time()
-> 1011 ep = fn(*args, **kwargs)
1012 end = time.time()
1013 log_export_usage(
1014 event="export.time",
1015 metrics=end - start,
1016 flags=_EXPORT_FLAGS,
1017 **get_ep_stats(ep),
1018 )
File [/usr/local/lib/python3.12/dist-packages/torch/export/exported_program.py:128](http://34.72.49.31:8889/usr/local/lib/python3.12/dist-packages/torch/export/exported_program.py#line=127), in _disable_prexisiting_fake_mode.<locals>.wrapper(*args, **kwargs)
125 @functools.wraps(fn)
126 def wrapper(*args, **kwargs):
127 with unset_fake_temporarily():
--> 128 return fn(*args, **kwargs)
File [/usr/local/lib/python3.12/dist-packages/torch/export/_trace.py:2057](http://34.72.49.31:8889/usr/local/lib/python3.12/dist-packages/torch/export/_trace.py#line=2056), in _export(mod, args, kwargs, dynamic_shapes, strict, preserve_module_call_signature, pre_dispatch, allow_complex_guards_as_runtime_asserts, _is_torch_jit_trace)
2049 # NOTE Export training IR rollout
2050 # Old export calls export._trace(pre_dispatch=True)
2051 # and there are still lot of internal[/OSS](http://34.72.49.31:8889/OSS) callsites that
(...)
2054 # export_training_ir_rollout_check returns True in OSS
2055 # while internally it returns False UNLESS otherwise specified.
2056 if pre_dispatch and export_training_ir_rollout_check():
-> 2057 return _export_for_training(
2058 mod,
2059 args,
2060 kwargs,
2061 dynamic_shapes,
2062 strict=strict,
2063 preserve_module_call_signature=preserve_module_call_signature,
2064 )
2066 (
2067 args,
2068 kwargs,
2069 original_in_spec,
2070 dynamic_shapes,
2071 ) = _process_export_inputs(mod, args, kwargs, dynamic_shapes)
2073 original_state_dict = _get_original_state_dict(mod)
File [/usr/local/lib/python3.12/dist-packages/torch/export/_trace.py:1038](http://34.72.49.31:8889/usr/local/lib/python3.12/dist-packages/torch/export/_trace.py#line=1037), in _log_export_wrapper.<locals>.wrapper(*args, **kwargs)
1031 else:
1032 log_export_usage(
1033 event="export.error.unclassified",
1034 type=error_type,
1035 message=str(e),
1036 flags=_EXPORT_FLAGS,
1037 )
-> 1038 raise e
1039 finally:
1040 _EXPORT_FLAGS = None
File [/usr/local/lib/python3.12/dist-packages/torch/export/_trace.py:1011](http://34.72.49.31:8889/usr/local/lib/python3.12/dist-packages/torch/export/_trace.py#line=1010), in _log_export_wrapper.<locals>.wrapper(*args, **kwargs)
1009 try:
1010 start = time.time()
-> 1011 ep = fn(*args, **kwargs)
1012 end = time.time()
1013 log_export_usage(
1014 event="export.time",
1015 metrics=end - start,
1016 flags=_EXPORT_FLAGS,
1017 **get_ep_stats(ep),
1018 )
File [/usr/local/lib/python3.12/dist-packages/torch/export/exported_program.py:128](http://34.72.49.31:8889/usr/local/lib/python3.12/dist-packages/torch/export/exported_program.py#line=127), in _disable_prexisiting_fake_mode.<locals>.wrapper(*args, **kwargs)
125 @functools.wraps(fn)
126 def wrapper(*args, **kwargs):
127 with unset_fake_temporarily():
--> 128 return fn(*args, **kwargs)
File [/usr/local/lib/python3.12/dist-packages/torch/export/_trace.py:1921](http://34.72.49.31:8889/usr/local/lib/python3.12/dist-packages/torch/export/_trace.py#line=1920), in _export_for_training(mod, args, kwargs, dynamic_shapes, strict, preserve_module_call_signature)
1908 original_state_dict = _get_original_state_dict(mod)
1910 export_func = (
1911 functools.partial(
1912 _strict_export_lower_to_aten_ir,
(...)
1919 )
1920 )
-> 1921 export_artifact = export_func( # type: ignore[operator]
1922 mod=mod,
1923 args=args,
1924 kwargs=kwargs,
1925 dynamic_shapes=dynamic_shapes,
1926 preserve_module_call_signature=preserve_module_call_signature,
1927 pre_dispatch=False,
1928 original_state_dict=original_state_dict,
1929 orig_in_spec=orig_in_spec,
1930 allow_complex_guards_as_runtime_asserts=False,
1931 _is_torch_jit_trace=False,
1932 )
1934 export_graph_signature = export_artifact.aten.sig
1936 forward_arg_names = _get_forward_arg_names(mod, args, kwargs)
File [/usr/local/lib/python3.12/dist-packages/torch/export/_trace.py:1290](http://34.72.49.31:8889/usr/local/lib/python3.12/dist-packages/torch/export/_trace.py#line=1289), in _strict_export_lower_to_aten_ir(mod, args, kwargs, dynamic_shapes, preserve_module_call_signature, pre_dispatch, original_state_dict, orig_in_spec, allow_complex_guards_as_runtime_asserts, _is_torch_jit_trace, lower_to_aten_callback)
1277 def _strict_export_lower_to_aten_ir(
1278 mod: torch.nn.Module,
1279 args: Tuple[Any, ...],
(...)
1288 lower_to_aten_callback: Callable,
1289 ) -> ExportArtifact:
-> 1290 gm_torch_level = _export_to_torch_ir(
1291 mod,
1292 args,
1293 kwargs,
1294 dynamic_shapes,
1295 preserve_module_call_signature=preserve_module_call_signature,
1296 restore_fqn=False, # don't need to restore because we will do it later
1297 allow_complex_guards_as_runtime_asserts=allow_complex_guards_as_runtime_asserts,
1298 _log_export_usage=False,
1299 )
1301 # We detect the fake_mode by looking at gm_torch_level's placeholders, this is the fake_mode created in dynamo.
1302 (
1303 fake_args,
1304 fake_kwargs,
1305 dynamo_fake_mode,
1306 ) = _extract_fake_inputs(gm_torch_level, args, kwargs)
File [/usr/local/lib/python3.12/dist-packages/torch/export/_trace.py:674](http://34.72.49.31:8889/usr/local/lib/python3.12/dist-packages/torch/export/_trace.py#line=673), in _export_to_torch_ir(f, args, kwargs, dynamic_shapes, preserve_module_call_signature, disable_constraint_solver, allow_complex_guards_as_runtime_asserts, restore_fqn, _log_export_usage, same_signature)
670 ctx = _wrap_submodules( # type: ignore[assignment]
671 f, preserve_module_call_signature, module_call_specs
672 )
673 with ctx, _ignore_backend_decomps():
--> 674 gm_torch_level, _ = torch._dynamo.export(
675 f,
676 dynamic_shapes=dynamic_shapes, # type: ignore[arg-type]
677 assume_static_by_default=True,
678 tracing_mode="symbolic",
679 disable_constraint_solver=disable_constraint_solver,
680 # currently the following 2 flags are tied together for export purposes,
681 # but untangle for sake of dynamo export api
682 prefer_deferred_runtime_asserts_over_guards=True,
683 allow_complex_guards_as_runtime_asserts=allow_complex_guards_as_runtime_asserts,
684 _log_export_usage=_log_export_usage,
685 same_signature=same_signature,
686 )(
687 *args,
688 **kwargs,
689 )
690 except (ConstraintViolationError, ValueRangeError) as e:
691 raise UserError(UserErrorType.CONSTRAINT_VIOLATION, str(e)) # noqa: B904
File [/usr/local/lib/python3.12/dist-packages/torch/_dynamo/eval_frame.py:1583](http://34.72.49.31:8889/usr/local/lib/python3.12/dist-packages/torch/_dynamo/eval_frame.py#line=1582), in export.<locals>.inner(*args, **kwargs)
1581 # TODO(voz): We may have instances of `f` that mutate inputs, we should track sideeffects and reject.
1582 try:
-> 1583 result_traced = opt_f(*args, **kwargs)
1584 except ConstraintViolationError as e:
1585 constraint_violation_error = e
File [/usr/local/lib/python3.12/dist-packages/torch/nn/modules/module.py:1739](http://34.72.49.31:8889/usr/local/lib/python3.12/dist-packages/torch/nn/modules/module.py#line=1738), in Module._wrapped_call_impl(self, *args, **kwargs)
1737 return self._compiled_call_impl(*args, **kwargs) # type: ignore[misc]
1738 else:
-> 1739 return self._call_impl(*args, **kwargs)
File [/usr/local/lib/python3.12/dist-packages/torch/nn/modules/module.py:1750](http://34.72.49.31:8889/usr/local/lib/python3.12/dist-packages/torch/nn/modules/module.py#line=1749), in Module._call_impl(self, *args, **kwargs)
1745 # If we don't have any hooks, we want to skip the rest of the logic in
1746 # this function, and just call forward.
1747 if not (self._backward_hooks or self._backward_pre_hooks or self._forward_hooks or self._forward_pre_hooks
1748 or _global_backward_pre_hooks or _global_backward_hooks
1749 or _global_forward_hooks or _global_forward_pre_hooks):
-> 1750 return forward_call(*args, **kwargs)
1752 result = None
1753 called_always_called_hooks = set()
File [/usr/local/lib/python3.12/dist-packages/torch/_dynamo/eval_frame.py:576](http://34.72.49.31:8889/usr/local/lib/python3.12/dist-packages/torch/_dynamo/eval_frame.py#line=575), in _TorchDynamoContext.__call__.<locals>._fn(*args, **kwargs)
573 _maybe_set_eval_frame(_callback_from_stance(callback))
575 try:
--> 576 return fn(*args, **kwargs)
577 except ShortenTraceback as e:
578 # Failures in the backend likely don't have useful
579 # data in the TorchDynamo frames, so we strip them out.
580 raise e.remove_dynamo_frames() from None # see TORCHDYNAMO_VERBOSE=1
File [/usr/local/lib/python3.12/dist-packages/torch/_dynamo/external_utils.py:46](http://34.72.49.31:8889/usr/local/lib/python3.12/dist-packages/torch/_dynamo/external_utils.py#line=45), in wrap_inline.<locals>.inner(*args, **kwargs)
41 def wrap_inline(fn: Callable[_P, _R]) -> Callable[_P, _R]:
42 """
43 Create an extra frame around fn that is not in skipfiles.
44 """
---> 46 @functools.wraps(fn)
47 def inner(*args: _P.args, **kwargs: _P.kwargs) -> _R:
48 return fn(*args, **kwargs)
50 return inner
File [/usr/local/lib/python3.12/dist-packages/torch/_dynamo/eval_frame.py:755](http://34.72.49.31:8889/usr/local/lib/python3.12/dist-packages/torch/_dynamo/eval_frame.py#line=754), in DisableContext.__call__.<locals>._fn(*args, **kwargs)
753 _maybe_set_eval_frame(_callback_from_stance(self.callback))
754 try:
--> 755 return fn(*args, **kwargs)
756 finally:
757 set_eval_frame(None)
File [/usr/local/lib/python3.12/dist-packages/torch/_dynamo/eval_frame.py:1546](http://34.72.49.31:8889/usr/local/lib/python3.12/dist-packages/torch/_dynamo/eval_frame.py#line=1545), in export.<locals>.inner.<locals>.dynamo_normalization_capturing_compiler.<locals>.result_capturing_wrapper(*graph_inputs)
1539 fake_params_buffers[name] = ambient_fake_mode.from_tensor(
1540 value, static_shapes=True
1541 )
1543 fake_graph_inputs = pytree.tree_map(
1544 ambient_fake_mode.from_tensor, graph_inputs
1545 )
-> 1546 graph_captured_result = torch.func.functional_call(
1547 graph, fake_params_buffers, fake_graph_inputs
1548 )
1550 return graph_captured_result
File [/usr/local/lib/python3.12/dist-packages/torch/_functorch/functional_call.py:147](http://34.72.49.31:8889/usr/local/lib/python3.12/dist-packages/torch/_functorch/functional_call.py#line=146), in functional_call(module, parameter_and_buffer_dicts, args, kwargs, tie_weights, strict)
141 else:
142 raise ValueError(
143 f"Expected parameter_and_buffer_dicts to be a dict, or a list[/tuple](http://34.72.49.31:8889/tuple) of dicts, "
144 f"but got {type(parameter_and_buffer_dicts)}"
145 )
--> 147 return nn.utils.stateless._functional_call(
148 module,
149 parameters_and_buffers,
150 args,
151 kwargs,
152 tie_weights=tie_weights,
153 strict=strict,
154 )
File [/usr/local/lib/python3.12/dist-packages/torch/nn/utils/stateless.py:282](http://34.72.49.31:8889/usr/local/lib/python3.12/dist-packages/torch/nn/utils/stateless.py#line=281), in _functional_call(module, parameters_and_buffers, args, kwargs, tie_weights, strict)
278 args = (args,)
279 with _reparametrize_module(
280 module, parameters_and_buffers, tie_weights=tie_weights, strict=strict
281 ):
--> 282 return module(*args, **kwargs)
File [/usr/local/lib/python3.12/dist-packages/torch/nn/modules/module.py:1739](http://34.72.49.31:8889/usr/local/lib/python3.12/dist-packages/torch/nn/modules/module.py#line=1738), in Module._wrapped_call_impl(self, *args, **kwargs)
1737 return self._compiled_call_impl(*args, **kwargs) # type: ignore[misc]
1738 else:
-> 1739 return self._call_impl(*args, **kwargs)
File [/usr/local/lib/python3.12/dist-packages/torch/nn/modules/module.py:1750](http://34.72.49.31:8889/usr/local/lib/python3.12/dist-packages/torch/nn/modules/module.py#line=1749), in Module._call_impl(self, *args, **kwargs)
1745 # If we don't have any hooks, we want to skip the rest of the logic in
1746 # this function, and just call forward.
1747 if not (self._backward_hooks or self._backward_pre_hooks or self._forward_hooks or self._forward_pre_hooks
1748 or _global_backward_pre_hooks or _global_backward_hooks
1749 or _global_forward_hooks or _global_forward_pre_hooks):
-> 1750 return forward_call(*args, **kwargs)
1752 result = None
1753 called_always_called_hooks = set()
File [/usr/local/lib/python3.12/dist-packages/torch/fx/_lazy_graph_module.py:126](http://34.72.49.31:8889/usr/local/lib/python3.12/dist-packages/torch/fx/_lazy_graph_module.py#line=125), in _LazyGraphModule._lazy_forward(self, *args, **kwargs)
121 assert not self._needs_recompile()
123 # call `__call__` rather than 'forward' since recompilation may
124 # install a wrapper for `__call__` to provide a customized error
125 # message.
--> 126 return self(*args, **kwargs)
File [/usr/local/lib/python3.12/dist-packages/torch/fx/graph_module.py:822](http://34.72.49.31:8889/usr/local/lib/python3.12/dist-packages/torch/fx/graph_module.py#line=821), in GraphModule.recompile.<locals>.call_wrapped(self, *args, **kwargs)
821 def call_wrapped(self, *args, **kwargs):
--> 822 return self._wrapped_call(self, *args, **kwargs)
File [/usr/local/lib/python3.12/dist-packages/torch/fx/graph_module.py:400](http://34.72.49.31:8889/usr/local/lib/python3.12/dist-packages/torch/fx/graph_module.py#line=399), in _WrappedCall.__call__(self, obj, *args, **kwargs)
398 raise e.with_traceback(None) # noqa: B904
399 else:
--> 400 raise e
File [/usr/local/lib/python3.12/dist-packages/torch/fx/graph_module.py:387](http://34.72.49.31:8889/usr/local/lib/python3.12/dist-packages/torch/fx/graph_module.py#line=386), in _WrappedCall.__call__(self, obj, *args, **kwargs)
385 return self.cls_call(obj, *args, **kwargs)
386 else:
--> 387 return super(self.cls, obj).__call__(*args, **kwargs) # type: ignore[misc]
388 except Exception as e:
389 assert e.__traceback__
File [/usr/local/lib/python3.12/dist-packages/torch/nn/modules/module.py:1739](http://34.72.49.31:8889/usr/local/lib/python3.12/dist-packages/torch/nn/modules/module.py#line=1738), in Module._wrapped_call_impl(self, *args, **kwargs)
1737 return self._compiled_call_impl(*args, **kwargs) # type: ignore[misc]
1738 else:
-> 1739 return self._call_impl(*args, **kwargs)
File [/usr/local/lib/python3.12/dist-packages/torch/nn/modules/module.py:1750](http://34.72.49.31:8889/usr/local/lib/python3.12/dist-packages/torch/nn/modules/module.py#line=1749), in Module._call_impl(self, *args, **kwargs)
1745 # If we don't have any hooks, we want to skip the rest of the logic in
1746 # this function, and just call forward.
1747 if not (self._backward_hooks or self._backward_pre_hooks or self._forward_hooks or self._forward_pre_hooks
1748 or _global_backward_pre_hooks or _global_backward_hooks
1749 or _global_forward_hooks or _global_forward_pre_hooks):
-> 1750 return forward_call(*args, **kwargs)
1752 result = None
1753 called_always_called_hooks = set()
File <eval_with_key>.5:6, in forward(self, L_args_0_)
4 def forward(self, L_args_0_ : torch.Tensor):
5 l_args_0_ = L_args_0_
----> 6 fn = self.fn(l_args_0_); l_args_0_ = None
7 getitem = fn[0]
8 getitem_1 = fn[1]; fn = None
File [/usr/local/lib/python3.12/dist-packages/torch/nn/modules/module.py:1739](http://34.72.49.31:8889/usr/local/lib/python3.12/dist-packages/torch/nn/modules/module.py#line=1738), in Module._wrapped_call_impl(self, *args, **kwargs)
1737 return self._compiled_call_impl(*args, **kwargs) # type: ignore[misc]
1738 else:
-> 1739 return self._call_impl(*args, **kwargs)
File [/usr/local/lib/python3.12/dist-packages/torch/nn/modules/module.py:1750](http://34.72.49.31:8889/usr/local/lib/python3.12/dist-packages/torch/nn/modules/module.py#line=1749), in Module._call_impl(self, *args, **kwargs)
1745 # If we don't have any hooks, we want to skip the rest of the logic in
1746 # this function, and just call forward.
1747 if not (self._backward_hooks or self._backward_pre_hooks or self._forward_hooks or self._forward_pre_hooks
1748 or _global_backward_pre_hooks or _global_backward_hooks
1749 or _global_forward_hooks or _global_forward_pre_hooks):
-> 1750 return forward_call(*args, **kwargs)
1752 result = None
1753 called_always_called_hooks = set()
File [/usr/local/lib/python3.12/dist-packages/torch/nn/modules/rnn.py:1043](http://34.72.49.31:8889/usr/local/lib/python3.12/dist-packages/torch/nn/modules/rnn.py#line=1042), in LSTM.forward(self, input, hx)
1042 def forward(self, input, hx=None): # noqa: F811
-> 1043 self._update_flat_weights()
1045 orig_input = input
1046 # xxx: isinstance check needs to be in conditional for TorchScript to compile
File [/usr/local/lib/python3.12/dist-packages/torch/nn/modules/rnn.py:392](http://34.72.49.31:8889/usr/local/lib/python3.12/dist-packages/torch/nn/modules/rnn.py#line=391), in RNNBase._update_flat_weights(self)
390 if not torch.jit.is_scripting():
391 if self._weights_have_changed():
--> 392 self._init_flat_weights()
File [/usr/local/lib/python3.12/dist-packages/torch/nn/modules/rnn.py:215](http://34.72.49.31:8889/usr/local/lib/python3.12/dist-packages/torch/nn/modules/rnn.py#line=214), in RNNBase._init_flat_weights(self)
208 self._flat_weights = [
209 getattr(self, wn) if hasattr(self, wn) else None
210 for wn in self._flat_weights_names
211 ]
212 self._flat_weight_refs = [
213 weakref.ref(w) if w is not None else None for w in self._flat_weights
214 ]
--> 215 self.flatten_parameters()
File [/usr/local/lib/python3.12/dist-packages/torch/nn/modules/rnn.py:256](http://34.72.49.31:8889/usr/local/lib/python3.12/dist-packages/torch/nn/modules/rnn.py#line=255), in RNNBase.flatten_parameters(self)
249 return
251 # If any parameters alias, we fall back to the slower, copying code path. This is
252 # a sufficient check, because overlapping parameter buffers that don't completely
253 # alias would break the assumptions of the uniqueness check in
254 # Module.named_parameters().
255 unique_data_ptrs = {
--> 256 p.data_ptr() for p in self._flat_weights # type: ignore[union-attr]
257 }
258 if len(unique_data_ptrs) != len(self._flat_weights):
259 return
RuntimeError: Cannot access data pointer of Tensor (e.g. FakeTensor, FunctionalTensor). If you're using torch.compile[/export/fx](http://34.72.49.31:8889/export/fx), it is likely that we are erroneously tracing into a custom kernel. To fix this, please wrap the custom kernel into an opaque custom op. Please see the following for details: https://pytorch.org/tutorials/advanced/custom_ops_landing_page.html
Expected behavior
expect no errors occure. Or maybe I did something wrong.
Also, tbh it's a bit confusing when I try to read the torch tensorrt documentation, there is the dynamo thing, torch scrip thing? the FX thing? FX graph? there is compile, then I have to trace it to save? some type of compile output I can trace it to save, others I can't ? I'm not trying babbling gibberish, but every page under https://pytorch.org/TensorRT there is little tweaks here and there. sometimes you input backend, other times you change ir, another page you start with torch.dynamo ....
Regardless, can't compile lstm
Environment
I'm using the NGC docker nvcr.io/nvidia/pytorch:25.02-py3
Google Clud VM is used with L4 GPU