fungtion opened a new issue #4159: How to bind 3 inputs using mxnet.io.NDArrayIter? URL: https://github.com/apache/incubator-mxnet/issues/4159 For bugs or installation issues, please provide the following information. The more information you provide, the more likely people will be able to help you. ## Environment info Operating System: Ubuntu 14.04 Compiler:python 2.7 Package used (Python/R/Scala/Julia):python I want to feed the convolution net with triple input: image, annotation, label. According to #2929, I define the input using mxnet.io.NDArrayIter as: ``` import mxnet as mx import numpy as np train = mx.io.NDArrayIter(data=np.zeros((120000, 3, 224, 224), dtype='float32'), label={'label1': np.zeros((120000, 81), dtype='int8'), 'label2': np.zeros((120000, ), dtype='int8')}, batch_size=10) ``` However, I got an error: **include/mxnet/./tensor_blob.h:742:check failed: (this->shape_.Size())==(shape.size()) TBlob.get_with_shape: new and old shape do not match total elements** and **TypeError: Invalid type'<type 'numpy.ndarray'> for data, should be NDArray or numpy.ndarray'** Does it means data and label should match in shape? And how can I feed triple input (one data and two kinds of label) to network?
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