[GitHub] EsraaRagaa opened a new issue #7422: Data provided by data_shapes don't match names specified by data_names

[gi...@git.apache.org]

EsraaRagaa opened a new issue #7422: Data provided by data_shapes don't match names specified by data_names
URL: https://github.com/apache/incubator-mxnet/issues/7422
 
 
   I am trying to train my data with mxnet, the data are 20x20 images
   I put my data in a csv files in the form:
   label, pixel1, pixel2, ..., pixel400
   0,...
   1,...
   and my labels are 0 or 1,
   this is the code I used:
   batch_size = 2
   
   
   train_iterator = mx.io.NDArrayIter(X_train, Y_train, batch_size=batch_size)
   validate_iterator = mx.io.NDArrayIter(X_validate, Y_validate, batch_size=batch_size)
   
   ##first convelutional layer
   conv1 = mx.sym.Convolution(data=data, kernel=(3,3), num_filter=6)
   relu1 = mx.sym.Activation(data=conv1, act_type="relu")
   pool1 = mx.sym.Pooling(data=relu1, pool_type="max", kernel=(2,2), stride=(2,2))
   
   ##second convelutional layer
   conv2 = mx.sym.Convolution(data=pool1, kernel=(6,6), num_filter=12)
   relu2 = mx.sym.Activation(data=conv2, act_type="relu")
   pool2 = mx.sym.Pooling(data=relu2, pool_type="max", kernel=(2,2), stride=(2,2))
   
   ##first fully connected layer
   flatten = mx.sym.flatten(data=pool2)
   fc1 = mx.symbol.FullyConnected(data=flatten, num_hidden=12 )
   
   ##softmax loss
   lenet = mx.sym.SoftmaxOutput(data=fc1, name='softmax')
   
   ##create a trainable module on CPU 0
   lenet_model = mx.mod.Module(symbol=lenet, context=mx.cpu())
   device = mx.cpu()
   
   ##train using parameters
   
   '''
   model = mx.model.FeedForward.create(lenet_model,
   X = X_train,
   y = Y_train,
   ctx = device,
   num_epoch = 10)
   '''
   lenet_model.fit(train_iterator,
                            eval_data=validate_iterator,
                            optimizer='sgd',
                            optimizer_params={'learning_rate':0.1},
                            eval_metric='acc',
                            batch_end_callback = mx.callback.Speedometer(batch_size, 100),
                            num_epoch=10)
   # the error is:
    Traceback (most recent call last):
   
     File "<ipython-input-245-a2b29eed591d>", line 7, in <module>
       num_epoch=10)
   
     File "C:\Users\...\Anaconda2\lib\site-packages\mxnet-0.10.1-py2.7.egg\mxnet\module\base_module.py", line 459, in fit
       for_training=True, force_rebind=force_rebind)
   
     File "C:\Users\...\Anaconda2\lib\site-packages\mxnet-0.10.1-py2.7.egg\mxnet\module\module.py", line 372, in bind
       self.data_names, self.label_names, data_shapes, label_shapes)
   
     File "C:\Users\...\Anaconda2\lib\site-packages\mxnet-0.10.1-py2.7.egg\mxnet\module\base_module.py", line 70, in _parse_data_desc
       _check_names_match(data_names, data_shapes, 'data', True)
   
     File "C:\Users\...\Anaconda2\lib\site-packages\mxnet-0.10.1-py2.7.egg\mxnet\module\base_module.py", line 62, in _check_names_match
       raise ValueError(msg)
   
   ValueError: Data provided by data_shapes don't match names specified by data_names ([DataDesc[_0_data,(2,),<type 'numpy.float32'>,NCHW], DataDesc[_1_data,(2,),<type 'numpy.float32'>,NCHW], DataDesc[_2_data,(2,),<type 'numpy.float32'>,NCHW], DataDesc[_3_data,(2,),<type 'numpy.float32'>,NCHW], DataDesc[_4_data,(2,),<type 'numpy.float32'>,NCHW], DataDesc[_5_data,(2,),<type 'numpy.float32'>,NCHW], DataDesc[_6_data,(2,),<type 'numpy.float32'>,NCHW], DataDesc[_7_data,(2,),<type 'numpy.float32'>,NCHW], DataDesc[_8_data,(2,),<type 'numpy.float32'>,NCHW], DataDesc[_9_data,(2,),<type 'numpy.float32'>,NCHW], DataDesc[_10_data,(2,),<type 'numpy.float32'>,NCHW], DataDesc[_11_data,(2,),<type 'numpy.float32'>,NCHW], DataDesc[_12_data,(2,),<type 'numpy.float32'>,NCHW], DataDesc[_13_data,(2,),<type 'numpy.float32'>,NCHW], DataDesc[_14_data,(2,),<type 'numpy.float32'>,NCHW], DataDesc[_15_data,(2,),<type 'numpy.float32'>,NCHW], DataDesc[_16_data,(2,),<type 'numpy.float32'>,NCHW], DataDesc[_17_data,(
 2,),<type 'numpy.float32'>,NCHW],
   ...
   ...
   ...
   ...
   , DataDesc[_2773_data,(2,),<type 'numpy.float32'>,NCHW], DataDesc[_2774_data,(2,),<type 'numpy.float32'>,NCHW], DataDesc[_2775_data,(2,),<type 'numpy.float32'>,NCHW], DataDesc[_2776_data,(2,),<type 'numpy.float32'>,NCHW], DataDesc[_2777_data,(2,),<type 'numpy.float32'>,NCHW]] vs. ['data'])
   
   # What should the data look like, what is wrong in the code, please?
   I am using win10, python2, mxnet 0.10, anaconda2
   Thanks in advance
   
 
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