Shanu Kumar

You can, just make sure the input format remains the same. On Wed, Oct 17, 2018 at 7:24 AM xinxu1018 wrote: > Can we use our own data set to...

I first extracted words and stored it in a list named as vocab, then extracted word embedding and stored it in a numpy array. If 2nd word in vocab is...

You can try this approach but its shortcoming is that you don't have word embedding for the multi-word term. Create a dependency tree, then choose entity from the two word...

My google drive is full, please share a folder with me, where I will upload the word_embed file. On Thu, Oct 18, 2018 at 9:03 PM xinxu1018 wrote: > @Sshanu...

Oh, please share it with [email protected] On Thu, Oct 18, 2018 at 9:43 PM xinxu1018 wrote: > @Sshanu Hi Sshanu, I just shared a google > drive folder to the...

I don't have the file, if you are having a problem in generating the exact file, then simply try storing the embeddings in numpy array and vocabulary in a list,...

first check whether [[childs_path1[k], childs_path2[k]] for k in range(s, end)] has the same dimension as [5, 2, 20, 20] and also the data type

please try using python 3. Just use printing the shapes of this tensors, then debug the code

Can you please post the error or for which tensors dimension problem is occurring?

are you using python3?