Unanswered Questions
283 questions with no upvoted or accepted answers
6
votes
0
answers
618
views
Adversarial Learning for Semantic Segmentation
I am incorporating Adversarial Training for Semantic Segmentation from Adversarial Learning for Semi-Supervised Semantic Segmentation.
The idea is like this:
The discriminator takes as input a ...
- 4,323
3
votes
0
answers
44
views
Loss while fine tuning a transformer based pose estimation model not reducing
I am trying to fine-tune a transformer/encoder based pose estimation model available here at: https://huggingface.co/docs/transformers/en/model_doc/vitpose
When passing "labels" attribute to ...
- 131
3
votes
1
answer
122
views
How to train next token prediction text generation model using Pytorch Transformer classes?
For learning purposes, I have tried to train a text generation model at a tiny scale in this notebook using RNN/LSTM model. But I am not able to take it further to use transformer model. Can anyone ...
CommunityBot
- 1
3
votes
1
answer
399
views
How is padding masking considered in the Attention Head of a Transformer?
For purely educational purposes, my goal is to implement basic Transformer architecture from scratch. So far I focused on the encoder for classification tasks and assumed that all samples in a batch ...
CommunityBot
- 1
3
votes
0
answers
263
views
Cluster tabular data with text in some columns
Let's say I have a following features in the my dataframe:
user_id
user_age
is_student
is_graduate
salary
resume
integer
integer
binary
binary
integer
text (up to 1000 symbols)
And also a few more ...
- 31
3
votes
0
answers
312
views
Struggling to understand/implement Transformer Decoder
I'm struggling to understand the decoder in a Transformer model, specifically with regards to some aspects of its architecture as well as how it actually handles the data during training.
What I have ...
- 131
3
votes
0
answers
893
views
What exactly negative/positive value of Captum's Integrated Gradient mean?
I use Captum's Integrated Gradient to interprete my PyTorch's neural network. I know that from github and original paper mentioned that ...
Positive attribution score means that the input in that ...
- 31
3
votes
0
answers
1k
views
PyTorch: Train without dataloader (loop trough dataframe instead)
I was wondering if it is bad practice to instead of using built in tools such as dataloader just loop trough each row in a pandas df. Lets say I am doing text classification and my training loop looks ...
- 193
3
votes
1
answer
167
views
How to specify version for dependencies so that each one is compatible and stays within a size limit?
I am trying to deploy a web app to Heroku. The free tier is limited to 500 MB.
I am using my resnet34 model as a .pkl file.
I create model with it using the fastai ...
CommunityBot
- 1
3
votes
0
answers
160
views
AlexNet Research Paper VS PytTorch and Tensorflow implementation
I'm making my way through Deep Learning research papers, starting with AlexNet, and I found differences in the implementation of PyTorch and Tensorflow that I can't explain.
In the research paper, ...
- 233
3
votes
0
answers
760
views
Explain FastText model using SHAP values
I have trained fastText model and some fully connected network build on its embeddings. I figured out how to use Lime on it: complete example can be found in Natural Language Processing Is Fun Part 3: ...
- 2,168
3
votes
1
answer
376
views
Policy Gradient not "learning"
I'm attempting to implement the policy gradient taken from the "Hands-On Machine Learning" book by Geron, which can be found here. The notebook uses Tensorflow and I'm attempting to do it with PyTorch....
CommunityBot
- 1
3
votes
1
answer
288
views
Is it possible to solve Rubik's cube using DQN?
I'm trying to solve Rubik's cube using deep learning and I came across with DQN, so I decided to give it a try. I developed all the code and started training but I got this results:
Loss goes up and ...
CommunityBot
- 1
3
votes
0
answers
871
views
Understanding depthwise convolution vs convolution with group parameters in pytorch
So in the mobilenet-v1 network, depthwise conv layers are used. And I understand that as follows.
For a input feature map of (C_in, F_in, F_in), we take only 1 ...
- 91
3
votes
0
answers
912
views
How can I get testing accuracy using tensorboard for Detectron2?
I'm learning to use Detecron2. I've followed this link to create a custom object detector.
My training code -
...
- 131