Hi, I’m trying to save the model in torchscript module format. Unfortunately, I’m getting below error
---------------------------------------------------------------------------
NotSupportedError Traceback (most recent call last)
/tmp/ipykernel_127656/3223171615.py in <module>
----> 1 scripted_model = torch.jit.script(model)
~/miniconda3/envs/tensorrt/lib/python3.7/site-packages/torch/jit/_script.py in script(obj, optimize, _frames_up, _rcb, example_inputs)
1264 obj = call_prepare_scriptable_func(obj)
1265 return torch.jit._recursive.create_script_module(
-> 1266 obj, torch.jit._recursive.infer_methods_to_compile
1267 )
1268
~/miniconda3/envs/tensorrt/lib/python3.7/site-packages/torch/jit/_recursive.py in create_script_module(nn_module, stubs_fn, share_types, is_tracing)
452 if not is_tracing:
453 AttributeTypeIsSupportedChecker().check(nn_module)
--> 454 return create_script_module_impl(nn_module, concrete_type, stubs_fn)
455
456 def create_script_module_impl(nn_module, concrete_type, stubs_fn):
~/miniconda3/envs/tensorrt/lib/python3.7/site-packages/torch/jit/_recursive.py in create_script_module_impl(nn_module, concrete_type, stubs_fn)
464 """
465 cpp_module = torch._C._create_module_with_type(concrete_type.jit_type)
--> 466 method_stubs = stubs_fn(nn_module)
467 property_stubs = get_property_stubs(nn_module)
468 hook_stubs, pre_hook_stubs = get_hook_stubs(nn_module)
~/miniconda3/envs/tensorrt/lib/python3.7/site-packages/torch/jit/_recursive.py in infer_methods_to_compile(nn_module)
733 stubs = []
734 for method in uniqued_methods:
--> 735 stubs.append(make_stub_from_method(nn_module, method))
736 return overload_stubs + stubs
737
~/miniconda3/envs/tensorrt/lib/python3.7/site-packages/torch/jit/_recursive.py in make_stub_from_method(nn_module, method_name)
64 # In this case, the actual function object will have the name `_forward`,
65 # even though we requested a stub for `forward`.
---> 66 return make_stub(func, method_name)
67
68
~/miniconda3/envs/tensorrt/lib/python3.7/site-packages/torch/jit/_recursive.py in make_stub(func, name)
49 def make_stub(func, name):
50 rcb = _jit_internal.createResolutionCallbackFromClosure(func)
---> 51 ast = get_jit_def(func, name, self_name="RecursiveScriptModule")
52 return ScriptMethodStub(rcb, ast, func)
53
~/miniconda3/envs/tensorrt/lib/python3.7/site-packages/torch/jit/frontend.py in get_jit_def(fn, def_name, self_name, is_classmethod)
262 pdt_arg_types = type_trace_db.get_args_types(qualname)
263
--> 264 return build_def(parsed_def.ctx, fn_def, type_line, def_name, self_name=self_name, pdt_arg_types=pdt_arg_types)
265
266 # TODO: more robust handling of recognizing ignore context manager
~/miniconda3/envs/tensorrt/lib/python3.7/site-packages/torch/jit/frontend.py in build_def(ctx, py_def, type_line, def_name, self_name, pdt_arg_types)
300 py_def.col_offset + len("def"))
301
--> 302 param_list = build_param_list(ctx, py_def.args, self_name, pdt_arg_types)
303 return_type = None
304 if getattr(py_def, 'returns', None) is not None:
~/miniconda3/envs/tensorrt/lib/python3.7/site-packages/torch/jit/frontend.py in build_param_list(ctx, py_args, self_name, pdt_arg_types)
335 if arg is not None:
336 ctx_range = build_expr(ctx, arg).range()
--> 337 raise NotSupportedError(ctx_range, _vararg_kwarg_err)
338
339 # List of Tuple of args and type as inferred by profile directed typing
NotSupportedError: Compiled functions can't take variable number of arguments or use keyword-only arguments with defaults:
File "/home/iamalien/Desktop/my_files/semantic_segmentation_example/semantic-segmentation-pytorch/sage_example/code/mit_semseg/models/models.py", line 29
def forward(self, feed_dict, *, segSize=None):
~~~~ <--- HERE
# training
if segSize is None:
this is the github repository i’m using to build the model. could you please help me save the model in torchscript format?
@ptrblck