Traceback (most recent call last):


 "train.py", line 138, in <module>

train()


 "train.py", line 120, in train

loss = criterion(out, data.y)


 "/home/wbl/software/anaconda3/envs/torch/lib/python3.8/site-packages/torch/nn/modules/module.py", line 722, in _call_impl

result = self.forward(*input, **kwargs)


 "/home/wbl/software/anaconda3/envs/torch/lib/python3.8/site-packages/torch/nn/modules/loss.py", line 211, in forward

return F.nll_loss(input, target, weight=self.weight, ignore_index=self.ignore_index, reduction=self.reduction)


 "/home/wbl/software/anaconda3/envs/torch/lib/python3.8/site-packages/torch/nn/functional.py", line 2215, in nll_loss

raise ValueError('Expected input batch_size ({}) to match target batch_size ({}).'
ValueError: Expected input batch_size (63) to match target batch_size (64).

Traceback (most recent call last):


 "/usr/local/lib/python3.6/threading.py", line 916, in _bootstrap_inner

self.run()


 "app.py", line 94, in run

self.behaviour.run(self.market_data, self.settings['output_mode'])


 "/app/behaviour.py", line 66, in run

new_result = self._test_strategies(market_data, output_mode)


 "/app/behaviour.py", line 152, in _test_strategies

market_pair


 "/app/behaviour.py", line 259, in _get_indicator_results

market_pair


 "/app/behaviour.py", line 421, in _get_analysis_result

results = dispatcher[indicator](**dispatcher_args)


 "/app/analyzers/indicators/ichimoku.py", line 83, in analyze

ichimoku_values.at[date, 'is_hot'] = span_hot and close_hot


 "/usr/local/lib/python3.6/site-packages/pandas/core/generic.py", line 1121, in __nonzero__

.format(self.__class__.__name__))
ValueError: The truth value of a Series is ambiguous. Use a.empty, a.bool(), a.item(), a.any() or a.all().
