RuntimeError: mat1 and mat2 shapes cannot be multiplied when calling get_potential_energy() #728
Comments
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Can you make sure you are using the same mace vesion to train and evaluate the models. |
Hi, thanks for your reply. I can confirm I am using the same mace version which is 0.3.7 and the pytorch version is 2.2.1 |
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Can you please try updating to the latest version of MACE? |
Thanks I will have a try with the latest version. |
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Or you using the model file without "compiled" in the file name ? |
I tried both, for the compiled one, the error is: 'RuntimeError: expand(torch.FloatTensor{[215, 215]}, size=[215]): the number of sizes provided (1) must be greater or equal to the number of dimensions in the tensor (2)' |
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Can you send me your model at ib467@cam.ac.uk? |
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I have mace 0.3.9 installed locally and the model works fine. Can you double check that you have the right mace version locally (please do pip uninstall mace-torch). |
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Hello, I also encountered this problem recently. I first evaluated (by mace 0.3.9) a model (trained by a previous mace version) with cueq, the error about matrix shape occured. Then I train a new model with 0.3.9 and evaluate again (both with cueq), the same error occurs as: |
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After several tests, the problem seems to only appear when running committee MACE using version 0.3.9, where a list of more than 2 models is passed to MACEcalculaters, no matter these models are trained on the old version or latest. (exactly 2 models will work well sometime) |
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mmm very weird, I don't think your two errors are the same though. Can you please send the scripts and models to reproduce your error on my email: ib467@cam.ac.uk |
Hi, Thanks for your testing. I just did a quick check and it seems the latest version is 0.3.8 and I am not able to install 0.3.9. |
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Can you try again, just do |
Description
I encountered a RuntimeError while attempting to calculate the potential energy of an atomic system using the get_potential_energy() function in ASE with a MACE-based calculator. The error appears to stem from a matrix multiplication shape mismatch in mace.modules.blocks.
This potential was specifically trained for a CPU system. Notably, I previously trained a similar MACE potential using the same configuration, and it worked without issues. The only difference in this case is the inclusion of a larger dataset during training.
Error Traceback
plaintext
RuntimeError Traceback (most recent call last)
~\AppData\Local\Temp\ipykernel_5224\1801253464.py in
----> 1 a.get_potential_energy()
D:\anaconda3\lib\site-packages\ase\atoms.py in get_potential_energy(self, force_consistent, apply_constraint)
753 self, force_consistent=force_consistent)
754 else:
--> 755 energy = self._calc.get_potential_energy(self)
756 if apply_constraint:
757 for constraint in self.constraints:
D:\anaconda3\lib\site-packages\ase\calculators\abc.py in get_potential_energy(self, atoms, force_consistent)
22 else:
23 name = 'energy'
---> 24 return self.get_property(name, atoms)
25
26 def get_potential_energies(self, atoms=None):
D:\anaconda3\lib\site-packages\ase\calculators\calculator.py in get_property(self, name, atoms, allow_calculation)
536 self.atoms = atoms.copy()
537
--> 538 self.calculate(atoms, [name], system_changes)
539
540 if name not in self.results:
D:\anaconda3\lib\site-packages\mace\calculators\mace.py in calculate(self, atoms, properties, system_changes)
232 if self.model_type in ["MACE", "EnergyDipoleMACE"]:
233 batch = self._clone_batch(batch_base)
--> 234 node_e0 = self.models[0].atomic_energies_fn(batch["node_attrs"])
235 compute_stress = not self.use_compile
236 else:
D:\anaconda3\lib\site-packages\torch\nn\modules\module.py in _wrapped_call_impl(self, *args, **kwargs)
1551 return self._compiled_call_impl(*args, **kwargs) # type: ignore[misc]
1552 else:
-> 1553 return self._call_impl(*args, **kwargs)
1554
1555 def _call_impl(self, *args, **kwargs):
D:\anaconda3\lib\site-packages\torch\nn\modules\module.py in _call_impl(self, *args, **kwargs)
1560 or _global_backward_pre_hooks or _global_backward_hooks
1561 or _global_forward_hooks or _global_forward_pre_hooks):
-> 1562 return forward_call(*args, **kwargs)
1563
1564 try:
D:\anaconda3\lib\site-packages\mace\modules\blocks.py in forward(self, x)
144 self, x: torch.Tensor # one-hot of elements [..., n_elements]
145 ) -> torch.Tensor: # [..., ]
--> 146 return torch.matmul(x, self.atomic_energies)
147
148 def repr(self):
RuntimeError: mat1 and mat2 shapes cannot be multiplied (215x2 and 1x2)
Steps to Reproduce
Use a MACE-based calculator in ASE.
Define an atomic structure (ase.Atoms).
Attempt to compute the potential energy using get_potential_energy().
Expected Behavior
The function should compute the potential energy of the system without error.
Actual Behavior
A RuntimeError occurs, indicating a shape mismatch during a matrix multiplication in mace.modules.blocks.
It appears that the issue arises in the forward method of mace.modules.blocks, where torch.matmul is called on tensors with incompatible shapes (215x2 and 1x2).
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