coremltools: AttributeError: 'torch._C.Node' object has no attribute 'ival'

🐞Describe the bug

I got this error when convert coremlmodel after torch.jit.freeze

Trace

Traceback (most recent call last):
  File "mini_code.py", line 15, in <module>
    model = ct.convert(
  File "/home/liyang/.local/lib/python3.8/site-packages/coremltools/converters/_converters_entry.py", line 175, in convert
    mlmodel = mil_convert(
  File "/home/liyang/.local/lib/python3.8/site-packages/coremltools/converters/mil/converter.py", line 128, in mil_convert
    proto = mil_convert_to_proto(model, convert_from, convert_to,
  File "/home/liyang/.local/lib/python3.8/site-packages/coremltools/converters/mil/converter.py", line 171, in mil_convert_to_proto
    prog = frontend_converter(model, **kwargs)
  File "/home/liyang/.local/lib/python3.8/site-packages/coremltools/converters/mil/converter.py", line 85, in __call__
    return load(*args, **kwargs)
  File "/home/liyang/.local/lib/python3.8/site-packages/coremltools/converters/mil/frontend/torch/load.py", line 70, in load
    converter = TorchConverter(torchscript, inputs, outputs, cut_at_symbols)
  File "/home/liyang/.local/lib/python3.8/site-packages/coremltools/converters/mil/frontend/torch/converter.py", line 146, in __init__
    self.graph = InternalTorchIRGraph(
  File "/home/liyang/.local/lib/python3.8/site-packages/coremltools/converters/mil/frontend/torch/internal_graph.py", line 241, in __init__
    new_node = InternalTorchIRNode(raw_node, parent=self)
  File "/home/liyang/.local/lib/python3.8/site-packages/coremltools/converters/mil/frontend/torch/internal_graph.py", line 140, in __init__
    self.attr = {
  File "/home/liyang/.local/lib/python3.8/site-packages/coremltools/converters/mil/frontend/torch/internal_graph.py", line 141, in <dictcomp>
    name: getattr(node, node.kindOf(name))(name)
AttributeError: 'torch._C.Node' object has no attribute 'ival'

To Reproduce

If a python script can reproduce the error, please paste the code snippet

import torch
import coremltools as ct

# init maxpool module
torch_model = torch.nn.Conv2d(3, 3, 1, 1)

# Trace with random data
example_input = torch.rand(1, 3, 224, 224) 
trace_model = torch.jit.trace(torch_model, example_input).eval()
freeze_model = torch.jit.freeze(trace_model)

# Convert to Core ML using the Unified Conversion API
model = ct.convert(
    freeze_model,
    inputs=[ct.ImageType(name="input", shape=example_input.shape)], 
)

System environment (please complete the following information):

coremltools version (e.g., 3.0b5): 4.1
OS (e.g., MacOS, Linux): Ubuntu20.04 LTS
How you install python (anaconda, virtualenv, system): miniconda
python version (e.g. 3.7): 3.8.5
any other relevant information:
- pytorch version: 1.9.0
- gpu: GeForce GTX 1650
- driver: Driver Version: 460.80
- CUDA: CUDA Version: 11.2

About this issue

Original URL
State: closed
Created 3 years ago
Comments: 16 (2 by maintainers)

Most upvoted comments

I think the problem is solved with Pytorch 1.12 because of this definition

Although, I’m getting other error conv1d not being define, so I cannot assure it.

alealv on Aug 5, 2022

I’m able to replicate the same error using the mobile optimizer as well:

trace = torch.jit.trace(net, dummy_input).eval()
# trace = torch.jit.freeze(trace)
trace = torch.utils.mobile_optimizer.optimize_for_mobile(
    trace,
    set(
        [
            MobileOptimizerType.CONV_BN_FUSION,
            MobileOptimizerType.INSERT_FOLD_PREPACK_OPS,
            MobileOptimizerType.REMOVE_DROPOUT,
        ]
    ),
)

Running it all on python 3.8.10, torch 1.9 and coremltools 5.1.

ludwigfriborg on Dec 14, 2021