bug ER - Class incremental

[optimass]

  File "/mnt/home/.conda/envs/sequoia/bin/sequoia_sweep", line 33, in <module>
    sys.exit(load_entry_point('sequoia', 'console_scripts', 'sequoia_sweep')())
  File "/mnt/home/dev/Sequoia/sequoia/experiments/hpo_sweep.py", line 129, in main
    return HPOSweep.main()
  File "/mnt/home/dev/Sequoia/sequoia/experiments/hpo_sweep.py", line 125, in main
    return experiment.launch(argv, strict_args=strict_args)
  File "/mnt/home/dev/Sequoia/sequoia/experiments/hpo_sweep.py", line 72, in launch
    best_params, best_objective = self.method.hparam_sweep(
  File "/mnt/home/dev/Sequoia/sequoia/settings/base/bases.py", line 732, in hparam_sweep
    result: Results = setting.apply(self)
  File "/mnt/home/dev/Sequoia/sequoia/settings/passive/cl/class_incremental_setting.py", line 362, in apply
    results: ClassIncrementalResults = super().main_loop(method)
  File "/mnt/home/dev/Sequoia/sequoia/settings/assumptions/incremental.py", line 222, in main_loop
    method.fit(
  File "/mnt/home/dev/Sequoia/sequoia/methods/experience_replay.py", line 112, in fit
    loss_replay = F.cross_entropy(b_logits, b_samples['y'])
  File "/mnt/home/.conda/envs/sequoia/lib/python3.8/site-packages/torch/nn/functional.py", line 2690, in cross_entropy
    return nll_loss(log_softmax(input, 1), target, weight, None, ignore_index, None, reduction)
  File "/mnt/home/.conda/envs/sequoia/lib/python3.8/site-packages/torch/nn/functional.py", line 1672, in log_softmax
    ret = input.log_softmax(dim)
 (function _print_stack)
Training Epoch 1:   1%|          | 1/127 [00:00<01:03,  2.00it/s, loss=5.3e+3, replay loss=3.07e+4]
2021-03-20:17:23:26,572 ERROR    [sequoia/settings/base/bases.py:735] Encountered an error, this trial will be dropped:
2021-03-20:17:23:26,573 ERROR    [sequoia/settings/base/bases.py:736] ------------------------------------------------------------
2021-03-20:17:23:26,579 ERROR    [sequoia/settings/base/bases.py:740] Traceback (most recent call last):
  File "/mnt/home/dev/Sequoia/sequoia/settings/base/bases.py", line 732, in hparam_sweep
    result: Results = setting.apply(self)
  File "/mnt/home/dev/Sequoia/sequoia/settings/passive/cl/class_incremental_setting.py", line 362, in apply
    results: ClassIncrementalResults = super().main_loop(method)
  File "/mnt/home/dev/Sequoia/sequoia/settings/assumptions/incremental.py", line 222, in main_loop
    method.fit(
  File "/mnt/home/dev/Sequoia/sequoia/methods/experience_replay.py", line 116, in fit
    loss.backward()
  File "/mnt/home/.conda/envs/sequoia/lib/python3.8/site-packages/torch/tensor.py", line 245, in backward
    torch.autograd.backward(self, gradient, retain_graph, create_graph, inputs=inputs)
  File "/mnt/home/.conda/envs/sequoia/lib/python3.8/site-packages/torch/autograd/__init__.py", line 145, in backward
    Variable._execution_engine.run_backward(
RuntimeError: Function 'LogSoftmaxBackward' returned nan values in its 0th output.