Error when run char_lstm example

[ningyuwhut]

I run the char_lstm example on my mbp. As the computer has no NVIDIA card，so I change the notebook to use cpu(0), the change is at below:

model = mx.model.FeedForward(
ctx=mx.cpu(0),//chang ctx from mx.gpu(0)to mx.cpu(0)
symbol=symbol,
num_epoch=num_epoch,
learning_rate=learning_rate,
momentum=0,
wd=0.0001,
initializer=mx.init.Xavier(factor_type="in", magnitude=2.34))

and when I run the cell, the compiler report errors:

---

TypeError Traceback (most recent call last)
in ()
38 eval_metric=mx.metric.np(Perplexity),
39 batch_end_callback=mx.callback.Speedometer(batch_size, 20),
---> 40 epoch_end_callback=mx.callback.do_checkpoint("obama"))

/Library/Python/2.7/site-packages/mxnet-0.7.0-py2.7.egg/mxnet/model.pyc in fit(self, X, y, eval_data, eval_metric, epoch_end_callback, batch_end_callback, kvstore, logger, work_load_list, monitor, eval_batch_end_callback)
786 logger=logger, work_load_list=work_load_list, monitor=monitor,
787 eval_batch_end_callback=eval_batch_end_callback,
--> 788 sym_gen=self.sym_gen)
789
790

/Library/Python/2.7/site-packages/mxnet-0.7.0-py2.7.egg/mxnet/model.pyc in _train_multi_device(symbol, ctx, arg_names, param_names, aux_names, arg_params, aux_params, begin_epoch, end_epoch, epoch_size, optimizer, kvstore, update_on_kvstore, train_data, eval_data, eval_metric, epoch_end_callback, batch_end_callback, logger, work_load_list, monitor, eval_batch_end_callback, sym_gen)
243
244 # evaluate at end, so we can lazy copy
--> 245 executor_manager.update_metric(eval_metric, data_batch.label)
246
247 nbatch += 1

/Library/Python/2.7/site-packages/mxnet-0.7.0-py2.7.egg/mxnet/executor_manager.pyc in update_metric(self, metric, labels)
404 def update_metric(self, metric, labels):
405 """update metric with the current executor"""
--> 406 self.curr_execgrp.update_metric(metric, labels)

/Library/Python/2.7/site-packages/mxnet-0.7.0-py2.7.egg/mxnet/executor_manager.pyc in update_metric(self, metric, labels)
260 for texec, islice in zip(self.train_execs, self.slices):
261 labels_slice = [label[islice] for label in labels]
--> 262 metric.update(labels_slice, texec.outputs)
263
264 class DataParallelExecutorManager(object):

/Library/Python/2.7/site-packages/mxnet-0.7.0-py2.7.egg/mxnet/metric.pyc in update(self, labels, preds)
342 pred = pred[:, 1]
343
--> 344 reval = self._feval(label, pred)
345 if isinstance(reval, tuple):
346 (sum_metric, num_inst) = reval

/Library/Python/2.7/site-packages/mxnet-0.7.0-py2.7.egg/mxnet/metric.pyc in feval(label, pred)
368 def feval(label, pred):
369 """Internal eval function."""
--> 370 return numpy_feval(label, pred)
371 feval.name = numpy_feval.name
372 return CustomMetric(feval, name, allow_extra_outputs)

in Perplexity(label, pred)
23
24
---> 25 loss += -np.log(max(1e-10, pred[i][int(label[i])]))
26 return np.exp(loss / label.size)
27

TypeError: only length-1 arrays can be converted to Python scalars

the error arise from the code ：
loss += -np.log(max(1e-10, pred[i][int(label[i])]))

so is it caused by the ctx change? please help

[AntonEryomin]

Nope, this error is not about ctx changing. This error is about the size of array, please looking carefully about the size of array.