gistfile1.txt

---------------------------------------------------------------------------
ValueError                                Traceback (most recent call last)
<ipython-input-13-c9831efca396> in <module>
----> 1 torch.onnx.export(Model(), torch.zeros(1,1,1,1), MODEL_FILE, opset_version=11)
      2 
      3 loaded = onnx.load(MODEL_FILE)

~/work/pytorch/torch/onnx/__init__.py in export(model, args, f, export_params, verbose, training, input_names, output_names, aten, export_raw_ir, operator_export_type, opset_version, _retain_param_name, do_constant_folding, example_outputs, strip_doc_string, dynamic_axes, keep_initializers_as_inputs, custom_opsets, enable_onnx_checker, use_external_data_format)
    170                         do_constant_folding, example_outputs,
    171                         strip_doc_string, dynamic_axes, keep_initializers_as_inputs,
--> 172                         custom_opsets, enable_onnx_checker, use_external_data_format)
    173 
    174 

~/work/pytorch/torch/onnx/utils.py in export(model, args, f, export_params, verbose, training, input_names, output_names, aten, export_raw_ir, operator_export_type, opset_version, _retain_param_name, do_constant_folding, example_outputs, strip_doc_string, dynamic_axes, keep_initializers_as_inputs, custom_opsets, enable_onnx_checker, use_external_data_format)
     90             dynamic_axes=dynamic_axes, keep_initializers_as_inputs=keep_initializers_as_inputs,
     91             custom_opsets=custom_opsets, enable_onnx_checker=enable_onnx_checker,
---> 92             use_external_data_format=use_external_data_format)
     93 
     94 

~/work/pytorch/torch/onnx/utils.py in _export(model, args, f, export_params, verbose, training, input_names, output_names, operator_export_type, export_type, example_outputs, propagate, opset_version, _retain_param_name, do_constant_folding, strip_doc_string, dynamic_axes, keep_initializers_as_inputs, fixed_batch_size, custom_opsets, add_node_names, enable_onnx_checker, use_external_data_format)
    528                                                             example_outputs, propagate,
    529                                                             _retain_param_name, val_do_constant_folding,
--> 530                                                             fixed_batch_size=fixed_batch_size)
    531 
    532             # TODO: Don't allocate a in-memory string for the protobuf

~/work/pytorch/torch/onnx/utils.py in _model_to_graph(model, args, verbose, input_names, output_names, operator_export_type, example_outputs, propagate, _retain_param_name, do_constant_folding, _disable_torch_constant_prop, fixed_batch_size)
    382     graph = _optimize_graph(graph, operator_export_type,
    383                             _disable_torch_constant_prop=_disable_torch_constant_prop,
--> 384                             fixed_batch_size=fixed_batch_size, params_dict=params_dict)
    385 
    386     if isinstance(model, torch.jit.ScriptModule) or isinstance(model, torch.jit.ScriptFunction):

~/work/pytorch/torch/onnx/utils.py in _optimize_graph(graph, operator_export_type, _disable_torch_constant_prop, fixed_batch_size, params_dict)
    186         torch._C._jit_pass_erase_number_types(graph)
    187 
--> 188         graph = torch._C._jit_pass_onnx(graph, operator_export_type)
    189         torch._C._jit_pass_lint(graph)
    190 

~/work/pytorch/torch/onnx/__init__.py in _run_symbolic_function(*args, **kwargs)
    203 def _run_symbolic_function(*args, **kwargs):
    204     from torch.onnx import utils
--> 205     return utils._run_symbolic_function(*args, **kwargs)
    206 
    207 

~/work/pytorch/torch/onnx/utils.py in _run_symbolic_function(g, n, inputs, env, operator_export_type)
    780                                   .format(op_name, opset_version, op_name))
    781                 op_fn = sym_registry.get_registered_op(op_name, '', opset_version)
--> 782                 return op_fn(g, *inputs, **attrs)
    783 
    784         elif ns == "prim":

~/work/pytorch/torch/onnx/symbolic_opset11.py in symbolic_fn(g, input, output_size, *args)
    112 def _interpolate(name, dim, interpolate_mode):
    113     def symbolic_fn(g, input, output_size, *args):
--> 114         scales, align_corners = sym_help._get_interpolate_attributes(g, interpolate_mode, args)
    115         align_corners = sym_help._maybe_get_scalar(align_corners)
    116         coordinate_transformation_mode = "asymmetric" if interpolate_mode == "nearest" \

~/work/pytorch/torch/onnx/symbolic_helper.py in _get_interpolate_attributes(g, mode, args)
    295         align_corners = args[0]
    296         scales = args[1:]
--> 297     scales = _interpolate_get_scales_if_available(g, scales)
    298     return scales, align_corners
    299 

~/work/pytorch/torch/onnx/symbolic_helper.py in _interpolate_get_scales_if_available(g, scales)
    271 
    272 def _interpolate_get_scales_if_available(g, scales):
--> 273     available_scales = _maybe_get_const(scales[0], 'f') != -1 and not _is_none(scales[0])
    274 
    275     if not available_scales:

~/work/pytorch/torch/onnx/symbolic_helper.py in _maybe_get_const(value, desc)
     90 def _maybe_get_const(value, desc):
     91     if _is_value(value) and value.node().kind() == 'onnx::Constant':
---> 92         return _parse_arg(value, desc)
     93     return value
     94 

~/work/pytorch/torch/onnx/symbolic_helper.py in _parse_arg(value, desc)
     63             return int(tval)
     64         elif desc == 'f':
---> 65             return float(tval)
     66         elif desc == 'b':
     67             return bool(tval)

ValueError: only one element tensors can be converted to Python scalars