Comments (3)
You don't really have to use the HDF5 format (in fact, it's not being built by default anymore). If you want to see how the HDF5 files are being written, look in lstm-uw3-py.ipynb (an iPython Notebook).
It's probably easier for you just to use the C++ interface. If your CNN is already trained, you can just put the data into a Sequence
object; the indexes are sequence[timestep][feature,batch]
If you want to train the CNN and the CLSTM simultaneously, the CLSTM will backpropagate deltas for you that you can connect to your CNN library; after backward()
, the deltas are in net->d_inputs
.
from clstm.
"if you want to train the CNN and the CLSTM simultaneously, the CLSTM will backpropagate deltas for you that you can connect to your CNN library; after backward(), the deltas are in net->d_inputs",
where are the deltas in the new code?
from clstm.
I think they're in Batch::d
(see e.g. the usage in ocropus::share_deltas
)
from clstm.
Related Issues (20)
- core dumped, w != 0 failed
- Missing last char of the line. HOT 4
- Sort and Sed commands are causing the model not to train (ERROR 1/OUT is empty) HOT 2
- Arabic 800,000 model cant go below Error Rate 0.5 HOT 4
- Always missing one character in the output HOT 3
- Can I use this tool to do scene text detection + recognition ? HOT 2
- Is it possible to train multiple languages on a one model file ? HOT 6
- Error in training uw3-500
- clstmocr - error opening clstm file (trained model) HOT 8
- Segmentation fault when running clstmocr on pre-trained model HOT 1
- Error while using clstm models that I trained and test it !
- I want to use gpu to speed up training model! How do I do, I follow the previous issu to do but failed
- error: use of undeclared identifier 'environ' HOT 6
- How to optimally prepare the data
- Segmentation Fault when running tests HOT 1
- Inaccurate training
- question: clstmocrtrain on GPU
- How to make predictions using python code
- Is there a graphical depiction of the model being used/trained here? HOT 4
- question HOT 2
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 clstm.