Hi Arash,
Make sure all tensors are copied to the same cuda device to avoid memory
error.
Please reinstall singa using the latest wheel file
http://comp.nus.edu.sg/~dbsystem/singa/assets/file/pb2.6-cuda7.5-cudnn5/singa-1.0.0-cp27-none-linux_x86_64.whl
which resolved the problem of int32<->float3
The label tensor should be of shape (2947,) like this one
https://github.com/apache/incubator-singa/blob/master/python/singa/metric.py#L31
I will check the problem from int32 and float32.
On Sun, Oct 9, 2016 at 3:27 PM Arash Shafiei
wrote:
> I am facing a problem concerning creating tensor from
No. Loss != Inaccuracy.
If you want to compute the accuracy, you need to create an
evaluator=singa.Accuracy(), and call evaluator.Evaluate(o, t), where o is
the output from the dense layer and t is the ground truth tensor. You can
follow the example here
https://github.com/apache/incubator-singa/bl
Have you moved all tensor onto the same devices? Including the tensor for the
labels.
> On 9 Oct 2016, at 11:02 AM, Arash Shafiei wrote:
>
> outputs = rnn.forward(model_pb2.kTrain, inputs)[0:-2]
> grads = []
> batch_loss = 0
> g_dense_w.set_value(0.0)
> g_dense_b.set_value(0.0)
> print 'output
Actually, the char-rnn example is from type (4), where each rnn unit would
generate a prediction and has a ground truth label.
For your model (type 2), you only need to use the y128 (of shape 256, 28)
from the rnn::forward() as the input to the dense layer. All other yi
should be ignored.
Conseque
Currently, numpy array of dtype=np.float32 or np.int could be converted
into singa tensor.
Please convert the numpy array into np.float32 and then call
tensor.from_numpy(t) (without dtype=np.float32).
On Sat, Oct 8, 2016 at 6:36 PM Arash Shafiei
wrote:
> The values that I have are floating point
You may need use gcc4.8 or gcc4.9 to reinstall protobuf.
BTW, there is a compatibility problem between gcc5.x and cuda 7,
http://stackoverflow.com/questions/34996295/trying-to-get-cuda-7-5-to-work-with-gcc-5-x
On Thu, Sep 22, 2016 at 4:31 PM, Arash Shafiei
wrote:
> Yes, we are using the same
Are you using the singa wheel for protobuf 2.6 (i.e. the following link)?
http://comp.nus.edu.sg/~dbsystem/singa/assets/file/pb2.6-cuda7.5-cudnn5/singa-1.0.0-cp27-none-linux_x86_64.whl
May I know your gcc version for compiling protobuf?
On Thu, Sep 22, 2016 at 4:10 PM, Arash Shafiei
wrote:
> H
Hi Arash,
Have you installed google protobuf, which is a dependent library of SINGA?
Can you send me the output from running
ldd /usr/local/lib/python2.7/dist-packages/singa/_singa_wrap.so
It would display the version of the protobuf wheel is using.
Please make sure the version of the protobuf
Hi Arash,
Have you installed PySINGA via the following approaches (
http://singa.apache.org/en/docs/installation.html#install-pysinga)?
# in build/ folder
cmake -DUSE_CUDA=ON -DUSE_PYTHON=ON ..
make
cd python
pip install .
or using the python wheel
On Thu, Sep 22, 2016 at 2:02 PM, Arash Shafiei
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