jnn | Backpropagation neural-network API for Java | Machine Learning library
kandi X-RAY | jnn Summary
kandi X-RAY | jnn Summary
JNN is a Java library for neural network processing. The module also defines a neural network exchange format "NNA", a plain text format used to read and write neural networks. From 1.6 to 1.7. From 1.5 to 1.6.
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Top functions reviewed by kandi - BETA
- Reads theuralNet from a string
- Read a number of doubles
- Read one line
- Read a number of longs
- Clones this object
- Clone this unit
- Clones this layer
- Checks if all connections are valid
- Computes the Jacobobi of the input parameters
- Calculates the activation signal for the given signal
- Computes the dot product of two vectors
- Handle a network section entry
- Handles a network entry
- Process a single input vector
- Sets the input vector
- Call the NN function
- Reads neural network from input stream
- Sets the alpha tab
- Evaluate the input function
- Declares the arrays
- Handles a unit entry
- Handle a connection connection
- Evaluates the activation function
- Evaluates the output function on the given unit
- Handle a layer configuration entry
- Set the unit start
jnn Key Features
jnn Examples and Code Snippets
Community Discussions
Trending Discussions on jnn
QUESTION
I'd like to pack a string consisting of a 64 bits, 32 bits and 32 bits ints. I don't have much experience with the pack function (or bits altogether) so I'm trying to do something like this:
...ANSWER
Answered 2022-Mar-15 at 19:32pack creates a 16-character string.
QUESTION
I recently implemented a two-layer GRU network in Jax and was disappointed by its performance (it was unusable).
So, i tried a little speed comparison with Pytorch. Minimal working exampleThis is my minimal working example and the output was created on Google Colab with GPU-runtime. notebook in colab
...ANSWER
Answered 2021-Oct-29 at 13:49The reason the JAX code compiles slowly is that during JIT compilation JAX unrolls loops. So in terms of XLA compilation, your function is actually very large: you call rnn_jax.apply() 1000 times, and compilation times tend to be roughly quadratic in the number of statements.
By contrast, your pytorch function uses no Python loops, and so under the hood it is relying on vectorized operations that run much faster.
Any time you use a for loop over data in Python, a good bet is that your code will be slow: this is true whether you're using JAX, torch, numpy, pandas, etc. I'd suggest finding an approach to the problem in JAX that relies on vectorized operations rather than relying on slow Python looping.
QUESTION
I have this character vector of lines from a journal:
...ANSWER
Answered 2021-May-03 at 12:50If I understood correctly, you are sort of scanning the pdf downloaded from here. I think you should find a better way to scan your PDFs.
Till then, the best option could be this:
Community Discussions, Code Snippets contain sources that include Stack Exchange Network
Vulnerabilities
No vulnerabilities reported
Install jnn
You can use jnn like any standard Java library. Please include the the jar files in your classpath. You can also use any IDE and you can run and debug the jnn component as you would do with any other Java program. Best practice is to use a build tool that supports dependency management such as Maven or Gradle. For Maven installation, please refer maven.apache.org. For Gradle installation, please refer gradle.org .
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