flipkart-incubator / optimus Goto Github PK
View Code? Open in Web Editor NEWTrain, evaluate and deploy Deep Learning based text classifiers. Currently supports CNN
License: Apache License 2.0
Train, evaluate and deploy Deep Learning based text classifiers. Currently supports CNN
License: Apache License 2.0
python test.py sample/myFirstModel.p sample/datasets/sst_small_sample.csv sample/outputNonStatic true false
Performing this operation after training results in a segmentation fault
Reading line no. 0
['neg', 'pos']
lds 300
dss (64,)
Segmentation fault (core dumped)\
EDIT: problems arose from not using gpu_to_cpu.py, upon using this everything worked perfectly
We have modified yoon's original code to support multilabel classification. This was done by changing the last layer to a softmax. The task here is to integrate this code with the current refactored code.
Models trained on GPU are not deserializable on CPU. Many use cases would involve training of models on GPU, and deploying them on CPU.
The exact problem is that in the GPU models, cuda ndarrays are used instead of numpy arrays. When the model is unpickled, an error is thrown saying cuda is not found. This issue cannot be simply fixed by installing cuda on the CPU machine, but all the ndarrays have to be converted into numpy arrays.
There are two ways to solve this problem:
Appreciate the great work you guys have done and nice to see Flipkart supporting research work in Deep Learning for NLP. However, you mentioned in your Readme that "The wiki contains a summary of exciting results we obtained using optimus, on a variety of different text classification tasks" however I cannot figure out the wiki location. It will be interesting to see the results especially on sentences containing double negatives like "Overall it wasn't a bad movie".
Memory error is thrown on large test set. We can create mini batches of test set in the same way as we are doing it for train set.
For pip install -U scikit-learn
Error:
Command "/usr/bin/python -u -c "import setuptools, tokenize;file='/tmp/pip-build-vDJ91c/scikit-learn/setup.py';exec(compile(getattr(tokenize, 'open', open)(file).read().replace('\r\n', '\n'), file, 'exec'))" install --record /tmp/pip-P3laW8-record/install-record.txt --single-version-externally-managed --compile" failed with error code 1 in /tmp/pip-build-vDJ91c/scikit-learn
I am not able to comprehend this error.
Hi, Im trying to utilize the GPU to train on EC2 with a g2 instance, but on all sorts of configuration types I get this error. Im using theano 0.7 and have changed FloatX=float32 and device=gpu0
This doesn't work, and I noticed that this happens with yoon's original code too.
Has anyone found a way around this error?
If anybody has a configuration where GPU computation is working, please post your config!
Thanks!
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