DANet dimensions issue with dataset openml__sulfur__360966

[duncanmcelfresh]

occurs with dataset openml__sulfur__360966

example traceback:

Traceback (most recent call last):
  File "/home/shared/tabzilla/TabSurvey/tabzilla_experiment.py", line 137, in __call__
    result = cross_validation(model, self.dataset, self.time_limit)
  File "/home/shared/tabzilla/TabSurvey/tabzilla_utils.py", line 236, in cross_validation
    loss_history, val_loss_history = curr_model.fit(
  File "/home/shared/tabzilla/TabSurvey/models/danet.py", line 79, in fit
    self.model.fit(
  File "/home/shared/tabzilla/TabSurvey/models/danet_lib/abstract_model.py", line 154, in fit
    self._train_epoch(train_dataloader)
  File "/home/shared/tabzilla/TabSurvey/models/danet_lib/abstract_model.py", line 247, in _train_epoch
    batch_logs = self._train_batch(X, y)
  File "/home/shared/tabzilla/TabSurvey/models/danet_lib/abstract_model.py", line 279, in _train_batch
    output = self.network(X)
  File "/opt/conda/envs/torch/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1110, in _call_impl
    return forward_call(*input, **kwargs)
  File "/home/shared/tabzilla/TabSurvey/models/danet_lib/model/DANet.py", line 104, in forward
    out = self.init_layer(x)
  File "/opt/conda/envs/torch/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1110, in _call_impl
    return forward_call(*input, **kwargs)
  File "/home/shared/tabzilla/TabSurvey/models/danet_lib/model/DANet.py", line 78, in forward
    out = self.conv1(pre_out)
  File "/opt/conda/envs/torch/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1110, in _call_impl
    return forward_call(*input, **kwargs)
  File "/home/shared/tabzilla/TabSurvey/models/danet_lib/model/DANet.py", line 58, in forward
    x = self.bn(x)
  File "/opt/conda/envs/torch/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1110, in _call_impl
    return forward_call(*input, **kwargs)
  File "/home/shared/tabzilla/TabSurvey/models/danet_lib/model/DANet.py", line 26, in forward
    res = [self.bn(x_) for x_ in chunks]
  File "/home/shared/tabzilla/TabSurvey/models/danet_lib/model/DANet.py", line 26, in <listcomp>
    res = [self.bn(x_) for x_ in chunks]
  File "/opt/conda/envs/torch/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1110, in _call_impl
    return forward_call(*input, **kwargs)
  File "/opt/conda/envs/torch/lib/python3.10/site-packages/torch/nn/modules/batchnorm.py", line 168, in forward
    return F.batch_norm(
  File "/opt/conda/envs/torch/lib/python3.10/site-packages/torch/nn/functional.py", line 2419, in batch_norm
    _verify_batch_size(input.size())
  File "/opt/conda/envs/torch/lib/python3.10/site-packages/torch/nn/functional.py", line 2387, in _verify_batch_size
    raise ValueError("Expected more than 1 value per channel when training, got input size {}".format(size))
ValueError: Expected more than 1 value per channel when training, got input size torch.Size([1, 320, 1])