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Hey,
unfortunately, I am getting the following error when running your exemplary code for the 10kGNAD data set. It occurs when loading the model (learn_lm.load('ulmfit_for_german_jfilter')). I hope you can help me.
Best, Jacob
RuntimeError: Error(s) in loading state_dict for SequentialRNN:
size mismatch for 0.rnns.0.weight_hh_l0_raw: copying a param with shape torch.Size([4600, 1150]) from checkpoint, the shape in current model is torch.Size([4608, 1152]).
size mismatch for 0.rnns.0.module.weight_ih_l0: copying a param with shape torch.Size([4600, 400]) from checkpoint, the shape in current model is torch.Size([4608, 400]).
size mismatch for 0.rnns.0.module.weight_hh_l0: copying a param with shape torch.Size([4600, 1150]) from checkpoint, the shape in current model is torch.Size([4608, 1152]).
size mismatch for 0.rnns.0.module.bias_ih_l0: copying a param with shape torch.Size([4600]) from checkpoint, the shape in current model is torch.Size([4608]).
size mismatch for 0.rnns.0.module.bias_hh_l0: copying a param with shape torch.Size([4600]) from checkpoint, the shape in current model is torch.Size([4608]).
size mismatch for 0.rnns.1.weight_hh_l0_raw: copying a param with shape torch.Size([4600, 1150]) from checkpoint, the shape in current model is torch.Size([4608, 1152]).
size mismatch for 0.rnns.1.module.weight_ih_l0: copying a param with shape torch.Size([4600, 1150]) from checkpoint, the shape in current model is torch.Size([4608, 1152]).
size mismatch for 0.rnns.1.module.weight_hh_l0: copying a param with shape torch.Size([4600, 1150]) from checkpoint, the shape in current model is torch.Size([4608, 1152]).
size mismatch for 0.rnns.1.module.bias_ih_l0: copying a param with shape torch.Size([4600]) from checkpoint, the shape in current model is torch.Size([4608]).
size mismatch for 0.rnns.1.module.bias_hh_l0: copying a param with shape torch.Size([4600]) from checkpoint, the shape in current model is torch.Size([4608]).
size mismatch for 0.rnns.2.module.weight_ih_l0: copying a param with shape torch.Size([1600, 1150]) from checkpoint, the shape in current model is torch.Size([1600, 1152]).
The text was updated successfully, but these errors were encountered:
The workaround is not complete. However the following has worked for me: config = awd_lstm_lm_config.copy() config['n_hid'] = 1150 learn_lm = language_model_learner(data_lm, AWD_LSTM, drop_mult=0.5, pretrained=False, config=config) learn_lm.load('ulmfit_for_german_jfilter')
Hey,
unfortunately, I am getting the following error when running your exemplary code for the 10kGNAD data set. It occurs when loading the model (learn_lm.load('ulmfit_for_german_jfilter')). I hope you can help me.
Best, Jacob
RuntimeError: Error(s) in loading state_dict for SequentialRNN:
size mismatch for 0.rnns.0.weight_hh_l0_raw: copying a param with shape torch.Size([4600, 1150]) from checkpoint, the shape in current model is torch.Size([4608, 1152]).
size mismatch for 0.rnns.0.module.weight_ih_l0: copying a param with shape torch.Size([4600, 400]) from checkpoint, the shape in current model is torch.Size([4608, 400]).
size mismatch for 0.rnns.0.module.weight_hh_l0: copying a param with shape torch.Size([4600, 1150]) from checkpoint, the shape in current model is torch.Size([4608, 1152]).
size mismatch for 0.rnns.0.module.bias_ih_l0: copying a param with shape torch.Size([4600]) from checkpoint, the shape in current model is torch.Size([4608]).
size mismatch for 0.rnns.0.module.bias_hh_l0: copying a param with shape torch.Size([4600]) from checkpoint, the shape in current model is torch.Size([4608]).
size mismatch for 0.rnns.1.weight_hh_l0_raw: copying a param with shape torch.Size([4600, 1150]) from checkpoint, the shape in current model is torch.Size([4608, 1152]).
size mismatch for 0.rnns.1.module.weight_ih_l0: copying a param with shape torch.Size([4600, 1150]) from checkpoint, the shape in current model is torch.Size([4608, 1152]).
size mismatch for 0.rnns.1.module.weight_hh_l0: copying a param with shape torch.Size([4600, 1150]) from checkpoint, the shape in current model is torch.Size([4608, 1152]).
size mismatch for 0.rnns.1.module.bias_ih_l0: copying a param with shape torch.Size([4600]) from checkpoint, the shape in current model is torch.Size([4608]).
size mismatch for 0.rnns.1.module.bias_hh_l0: copying a param with shape torch.Size([4600]) from checkpoint, the shape in current model is torch.Size([4608]).
size mismatch for 0.rnns.2.module.weight_ih_l0: copying a param with shape torch.Size([1600, 1150]) from checkpoint, the shape in current model is torch.Size([1600, 1152]).
The text was updated successfully, but these errors were encountered: