I am trying to adapt a pytorch Named Entity Recognition model to incorporate differential privacy with the Opacus library. My model uses torchtext to build the
I am trying to work with Bayesian Optimisation for my Numerical model run, Optimising its parameters. For this I am using BoTorch. Its example code is given as
I am trying to use PyTorch's '''nn.TransformerEncoder''' module for a classification task. I have data points of varying lengths i.e I have sequences of differe
There seems to be a problem mixing pytorch's autograd with joblib. I need to get gradient in parallel for a lot of samples. Joblib works fine with other aspects
The convolutional model presented below, has two branches and each branch (for example) has two stages (convolutional layers). My aim is to combine the weighte
I want to verify if 2D convolution in spatial domain is really a multiplication in frequency domain, so I used pytorch to implement convolution of an image with
I am trying to train a GPT2 language model for text generation tasks. I am trying to include an additional embedding layer (with POS-tagging) on top of token em
When I am using criterion = nn.BCELoss() for my binary classification task it creates problem and print "Using a target size (torch.Size([2])) that is different
I am using GOOGLE COLAB when I get this error. Here is my code, I didn't find anything wrong, these code were right few hour ago but suddenly went wrong, I don'
Im trying to run Pytorch and Torchvision on Mac M1. I follow these instructions successfully install pytorch and run it natively on apple - https://betterprogra
import torch.multiprocessing as mp import torch import time class test(): def __init__(self,X,Y): self.X=X #.share_memory_() self.Y=Y
I created an exe with the PyInstaller. As soon as I enable the --onefile flag. The exe needs several minutes to start. When I build the application with the --o
How can I change the attached model to fit my dataset for the Bayesian model? my data include 5 variables and 32 results model = nn.Sequential( bnn.BayesLin
I'm using Pyannote and when I run the following from pyannote.audio import Pipeline pipeline = Pipeline.from_pretrained("pyannote/speaker-diarization") diariza
I install Nvidia Windows Driver and CUDA according to this article. After the installation of Nvidia Windows Driver, I’ve checked CUDA version by running
Using bert.tokenizer I can get the subword ids and the word spans of words in a sentence, for example, given the sentence "This is an example", I get the encode
I try to implement a rather simple siamese network and a contrastive loss function. I use a pre-trained VGG16 as a backbone model and strip away the last ReLU a
Here I have a pytorch tensor object which I need to use for training a neural network. Can pytorch tensors be used for training a keras neural network and if so
I'm trying to define a flatten layer before initiating fully connected layer. As my input is a tensor with shape (512, 2, 2), so I want to flatten this tensor b
I am training a linear model using py-torch and I am saving it to a file with the "save" function call. I have another code that loads the model in C++ and perf