Comments (3)
This implementation for pytorch does correspond to the actual paper.
from pytorch-cifar.
Actually noticed the same thing here facebookresearch/mixup-cifar10#3 . On top of that it seems to me that the final BN layer is missing.
from pytorch-cifar.
Hi,
In the ResNet publication they propose a different architecture where it comes to CIFAR-10 right?
The plain/residual architectures follow the form in Fig. 3 (middle/right). The network inputs are 32×32 images, with the per-pixel mean subtracted. The first layer is 3×3 convo- lutions. Then we use a stack of 6n layers with 3×3 convo- lutions on the feature maps of sizes {32, 16, 8} respectively, with 2n layers for each feature map size. The numbers of filters are {16, 32, 64} respectively. The subsampling is per- formed by convolutions with a stride of 2. The network ends with a global average pooling, a 10-way fully-connected layer, and softmax. There are totally 6n+2 stacked weighted layers. The following table summarizes the architecture:
There is only 3 layers and the feature map sizes are [16, 32, 64] not [64, 128, 256, 512] like for ImageNet.
The implementation of CIFAR in the original ResNet paper is reproduced in my repository, please see (https://github.com/Lornatang/ResNet/tree/master/examples/cifar)
Thank you, please give me some suggestions. @PabloRR100
from pytorch-cifar.
Related Issues (20)
- pytorch-cifar复现问题 HOT 4
- MobileNetV2 training does not converge HOT 1
- The test set is being used as validation set HOT 6
- 对于精度有疑问 HOT 2
- pre-train weights
- request: epochs numbers to converge in readme.md HOT 1
- ResNet18 performs much better than expected! HOT 5
- how to train my own dataset and classes? HOT 1
- [Question] efficientnet performance HOT 1
- Error when loading the weights on CPU but trained on GPU HOT 1
- Errors when testing on CPU HOT 11
- checkpoint
- ValueError: not enough values to unpack (expected 2, got 0) HOT 3
- load state_dict HOT 1
- Overfitting on ResNet18 HOT 2
- Performance degradation when loading a model after saving it HOT 2
- A problem in ShuffleNet
- How long will it take you to train the cifar10 model? HOT 1
- Overfitting
- Adding more flags to main.py
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 pytorch-cifar.