Runtime error when running svhn.py

[hanwentao]

When running svhn.py, a runtime error occurred, indicating a dimension mismatch. Both this program and the program under BinaryConnect project have the same problem. Is there something wrong with the data I downloaded?

hanwentao@hydrogen ~/repo/BinaryNet/Train-time {env2} (master*) % python svhn.py
batch_size = 50
alpha = 0.1
epsilon = 0.0001
activation = binary_net.binary_tanh_unit
binary = True
stochastic = False
H = 1.0
W_LR_scale = Glorot
num_epochs = 200
LR_start = 0.001
LR_fin = 1e-06
LR_decay = 0.96605087899
shuffle_parts = 1
Loading SVHN dataset
Building the CNN...
W_LR_scale = 20.0499
H = 1.0
W_LR_scale = 27.7128
H = 1.0
W_LR_scale = 33.9411
H = 1.0
W_LR_scale = 39.1918
H = 1.0
W_LR_scale = 48.0
H = 1.0
W_LR_scale = 55.4256
H = 1.0
W_LR_scale = 58.4237
H = 1.0
W_LR_scale = 36.9504
H = 1.0
W_LR_scale = 26.2552
H = 1.0
Training...
Traceback (most recent call last):
  File "svhn.py", line 322, in <module>
    test_set.X,test_set.y)
  File "/home/hanwentao/repo/BinaryConnect/binary_connect.py", line 252, in train
    train_loss = train_epoch(X_train,y_train,LR)
  File "/home/hanwentao/repo/BinaryConnect/binary_connect.py", line 218, in train_epoch
    loss += train_fn(X[i*batch_size:(i+1)*batch_size],y[i*batch_size:(i+1)*batch_size],LR)
  File "/home/hanwentao/sandbox/binarize/env2/lib/python2.7/site-packages/theano/compile/function_module.py", line
912, in __call__
    storage_map=getattr(self.fn, 'storage_map', None))
  File "/home/hanwentao/sandbox/binarize/env2/lib/python2.7/site-packages/theano/gof/link.py", line 314, in raise_with_op
    reraise(exc_type, exc_value, exc_trace)
  File "/home/hanwentao/sandbox/binarize/env2/lib/python2.7/site-packages/theano/compile/function_module.py", line
899, in __call__
    self.fn() if output_subset is None else\
ValueError: Input dimension mis-match. (input[1].shape[1] = 1, input[2].shape[1] = 10)
Apply node that caused the error: Elemwise{Composite{(i0 - (i1 * ((i2 * i3) + i4)))}}(TensorConstant{(1, 1) of 1.0}
, targets, Elemwise{sub,no_inplace}.0, Elemwise{true_div,no_inplace}.0, Rebroadcast{1}.0)
Toposort index: 448
Inputs types: [TensorType(float64, (True, True)), TensorType(float64, matrix), TensorType(float64, matrix), TensorT
ype(float64, row), TensorType(float64, row)]
Inputs shapes: [(1, 1), (50, 1), (50, 10), (1, 10), (1, 10)]
Inputs strides: [(8, 8), (8, 8), (80, 8), (80, 8), (80, 8)]
Inputs values: [array([[ 1.]]), 'not shown', 'not shown', 'not shown', 'not shown']
Outputs clients: [[Elemwise{maximum,no_inplace}(TensorConstant{(1, 1) of 0.0}, Elemwise{Composite{(i0 - (i1 * ((i2
* i3) + i4)))}}.0), Elemwise{EQ}(Elemwise{maximum,no_inplace}.0, Elemwise{Composite{(i0 - (i1 * ((i2 * i3) + i4)))}
}.0)]]

HINT: Re-running with most Theano optimization disabled could give you a back-trace of when this node was created.
This can be done with by setting the Theano flag 'optimizer=fast_compile'. If that does not work, Theano optimizations can be disabled with 'optimizer=None'.
HINT: Use the Theano flag 'exception_verbosity=high' for a debugprint and storage map footprint of this apply node.
Closing remaining open files:/home/hanwentao/data/tmp/svhn/h5/valid_32x32.h5...done/home/hanwentao/data/tmp/svhn/h5
/test_32x32.h5...done/home/hanwentao/data/tmp/svhn/h5/splitted_train_32x32.h5...done

[vtseng]

Hi @hanwentao , I aslo encountered the same issue. I wonder if you have figured out how to fix it? Thanks!

[MatthieuCourbariaux]

Your issue may be that the targets are not onehot encoded.

You may want to use this code to onehot the targets: https://github.com/MatthieuCourbariaux/BinaryNet/blob/master/Train-time/mnist.py#L109