Comments (4)
Hi,
Thank you for your feedback! We will release a library and a model zoo for DEQs later (with systematically designed code and verified implementations). Hopefully, this can help solve the training issues.
Before that, you might refer to the DEQ-Flow's code to implement your model. Or you can use phantom grad's code to train your MDEQ.
Please wait for our release!
Thanks!
Zhengyang
from deq.
I find that this error happens at loss.backward()
right after finishing pretrainig (factor = 0.0 and deq_steps = 0). The backward_hook is called once and the returned result[''result]
is a tensor with the shape of [64, 30720,1]. The model is trained on a machine using 2 GeForce RTX 2080Ti GPUs. The configuration file I used is cls_mdeq_TINY.yaml.
from deq.
Hi @yj373 ,
What version of pytorch are you using?
It seems that the backwawrd hook is causing the problem. If the issue still persists, I suggest that you revert to the custom backward pass approach to use the implicit differentiation. An example here: https://github.com/locuslab/mdeq/blob/master/lib/models/mdeq_forward_backward.py#L32
from deq.
Thank you for the reply! I am using torch 1.8.1+cu101. Actually, I followed the suggestion from @Gsunshine and trained the MDEQ model using phantom grad's code. And it turns out to work fine. Thanks again!
from deq.
Related Issues (20)
- Two slightly different process for Deq HOT 2
- Segmentation Fault when Loss Backward CIFAR cls_mdeq_LARGE_reg HOT 10
- CIFAR-10 Reproduction HOT 6
- Test ImageNet Pre-trained Model HOT 10
- Segmentation fault after removing hook HOT 3
- RuntimeError: einsum(): the number of subscripts in the equation (3) does not match the number of dimensions (4) for operand 0 and no ellipsis was given HOT 1
- DEQ for Vision Transformer HOT 2
- Memory consumption on CIFAR-10 HOT 4
- I'd like to ask if anderson can't be used normally sometimes HOT 11
- Does MDEQ have different inference results for different batch sizes? HOT 6
- Expected a 'cuda' device type for generator (related to speed issues?) HOT 5
- RuntimeError: Only Tensors created explicitly by the user (graph leaves) support the deepcopy protocol at the moment HOT 2
- Question about Remove Hook HOT 6
- Higher order derivatives
- UnboundLocalError: local variable 'lowest_xest' referenced before assignment HOT 4
- Broyden defeats the purpose of DEQs? HOT 6
- Expected a 'cuda' device type for generator but found 'cpu' HOT 2
- Mismatch between a pretrained ImageNet model and a config file HOT 1
- Hyperparameters for MDEQ-XL on ImageNet
Recommend Projects
-
React
A declarative, efficient, and flexible JavaScript library for building user interfaces.
-
Vue.js
🖖 Vue.js is a progressive, incrementally-adoptable JavaScript framework for building UI on the web.
-
Typescript
TypeScript is a superset of JavaScript that compiles to clean JavaScript output.
-
TensorFlow
An Open Source Machine Learning Framework for Everyone
-
Django
The Web framework for perfectionists with deadlines.
-
Laravel
A PHP framework for web artisans
-
D3
Bring data to life with SVG, Canvas and HTML. 📊📈🎉
-
Recommend Topics
-
javascript
JavaScript (JS) is a lightweight interpreted programming language with first-class functions.
-
web
Some thing interesting about web. New door for the world.
-
server
A server is a program made to process requests and deliver data to clients.
-
Machine learning
Machine learning is a way of modeling and interpreting data that allows a piece of software to respond intelligently.
-
Visualization
Some thing interesting about visualization, use data art
-
Game
Some thing interesting about game, make everyone happy.
Recommend Org
-
Facebook
We are working to build community through open source technology. NB: members must have two-factor auth.
-
Microsoft
Open source projects and samples from Microsoft.
-
Google
Google ❤️ Open Source for everyone.
-
Alibaba
Alibaba Open Source for everyone
-
D3
Data-Driven Documents codes.
-
Tencent
China tencent open source team.
from deq.