apple
AttributeError: 'list' object has no attribute 'val'. When set flexible input shapes
🐞Describing the bug
Traceback (most recent call last):
File "/media/anlab/data-2tb/ANLAB_THUY/ImageSearcher/ConvertSolar2Coreml.py", line 119, in <module>
mlprogram = ct.convert(
File "/home/anlab/anaconda3/envs/convertmodel1/lib/python3.9/site-packages/coremltools/converters/_converters_entry.py", line 551, in convert
mlmodel = mil_convert(
File "/home/anlab/anaconda3/envs/convertmodel1/lib/python3.9/site-packages/coremltools/converters/mil/converter.py", line 188, in mil_convert
return _mil_convert(model, convert_from, convert_to, ConverterRegistry, MLModel, compute_units, **kwargs)
File "/home/anlab/anaconda3/envs/convertmodel1/lib/python3.9/site-packages/coremltools/converters/mil/converter.py", line 212, in _mil_convert
proto, mil_program = mil_convert_to_proto(
File "/home/anlab/anaconda3/envs/convertmodel1/lib/python3.9/site-packages/coremltools/converters/mil/converter.py", line 286, in mil_convert_to_proto
prog = frontend_converter(model, **kwargs)
File "/home/anlab/anaconda3/envs/convertmodel1/lib/python3.9/site-packages/coremltools/converters/mil/converter.py", line 108, in __call__
return load(*args, **kwargs)
File "/home/anlab/anaconda3/envs/convertmodel1/lib/python3.9/site-packages/coremltools/converters/mil/frontend/torch/load.py", line 75, in load
return _perform_torch_convert(converter, debug)
File "/home/anlab/anaconda3/envs/convertmodel1/lib/python3.9/site-packages/coremltools/converters/mil/frontend/torch/load.py", line 114, in _perform_torch_convert
prog = converter.convert()
File "/home/anlab/anaconda3/envs/convertmodel1/lib/python3.9/site-packages/coremltools/converters/mil/frontend/torch/converter.py", line 484, in convert
convert_nodes(self.context, self.graph)
File "/home/anlab/anaconda3/envs/convertmodel1/lib/python3.9/site-packages/coremltools/converters/mil/frontend/torch/ops.py", line 93, in convert_nodes
add_op(context, node)
File "/home/anlab/anaconda3/envs/convertmodel1/lib/python3.9/site-packages/coremltools/converters/mil/frontend/torch/ops.py", line 3923, in avg_pool2d
_avg_pool(context, node, inputs)
File "/home/anlab/anaconda3/envs/convertmodel1/lib/python3.9/site-packages/coremltools/converters/mil/frontend/torch/ops.py", line 3876, in _avg_pool
strides = mb.const(val=kernel_sizes.val, name=strides.name)
AttributeError: 'list' object has no attribute 'val'
To Reproduce
- I try convert model SOLAR- (https://github.com/tonyngjichun/SOLAR/tree/master)
Init model pytorch:
class Network(nn.Module):
def __init__(self, model):
super().__init__()
self.model = model.cpu()
self.mean = torch.tensor([0.485, 0.456, 0.406]).view(3, 1, 1)
self.std = torch.tensor([0.229, 0.224, 0.225]).view(3, 1, 1)
def forward(self,x):
out1 = self.model(x)
reshaped_tensor1 = out1.view(1, 2048)
return reshaped_tensor1
state = torch.load(os.path.join(get_data_root(), 'networks/model_best.pth.tar'),map_location=torch.device('cpu'))
net_params = {}
net_params['architecture'] = state['meta']['architecture']
net_params['pooling'] = state['meta']['pooling']
net_params['local_whitening'] = state['meta'].get('local_whitening', False)
net_params['regional'] = state['meta'].get('regional', False)
net_params['whitening'] = state['meta'].get('whitening', True)
net_params['mean'] = state['meta']['mean']
net_params['std'] = state['meta']['std']
net_params['pretrained'] = False
net = load_network('model_best.pth.tar')
net.load_state_dict(state['state_dict'])
net.eval()
test_model = Network(net)
Convert pytorch to coreml
scale = 1/(0.226*255.0)
bias = [- 0.485/(0.229) , - 0.456/(0.224), - 0.406/(0.225)]
input_shape = ct.Shape(shape=(1, 3, ct.RangeDim(lower_bound=100, upper_bound=800),
ct.RangeDim(lower_bound=100, upper_bound=800)))
dummy_input = torch.rand(1,3,300,300)
input_tensor = ct.ImageType(name="my_input", shape=input_shape,scale=scale, bias=bias)
traced_model = torch.jit.trace(test_model.eval(), dummy_input)
traced_model.eval()
mlprogram = ct.convert(
traced_model,
minimum_deployment_target=ct.target.iOS13,
inputs=[input_tensor],
outputs=[ct.TensorType(name="embeddings")],
convert_to="neuralnetwork",
compute_units=ct.ComputeUnit.CPU_ONLY,
)
saved_model = 'ModelConvert/TestModel/Solar300_image_CPU_FlexibleInput.mlmodel'
outputmodel.save(saved_model)
System environment
- coremltools version: 7.0
- OS (e.g. MacOS version or Linux type): Linux
- Any other relevant version information (e.g. PyTorch or TensorFlow version): Torch 1.9.1
Could you try https://github.com/apple/coremltools/pull/2050 to see if it fixes this problem ? Or could you provide a standalone minimum example for reproduce ?
Could you try #2050 to see if it fixes this problem ? Or could you provide a standalone minimum example for reproduce ?
I tried to change the code in file coremltools/converters/mil/frontend/torch/ops.py similar to #2050. But when I convert the model, it always pauses at a certain threshold. I tried waiting but it didn't seem to work. you can reproduce using my colab code here: https://colab.research.google.com/drive/1jqT_K3ValOyfc_o_2od44eiz4UiE8xAk?usp=sharing
Could you try #2050 to see if it fixes this problem ? Or could you provide a standalone minimum example for reproduce ?
I tried to change the code in file coremltools/converters/mil/frontend/torch/ops.py similar to #2050. But when I convert the model, it always pauses at a certain threshold. I tried waiting but it didn't seem to work. you can reproduce using my colab code here: https://colab.research.google.com/drive/1jqT_K3ValOyfc_o_2od44eiz4UiE8xAk?usp=sharing
OK. I also notice the pause and has a plan yet to be implemented. I'll try your code after the optimization.
My PR focused on "padding" and failed to fix this problem. I've encountered the same situation on another net structure with a similar root cause.
I'll try to generalize my fix for these.