Code Monkey home page Code Monkey logo

apxr_run's People

Stargazers

 avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar

Watchers

 avatar  avatar  avatar  avatar  avatar  avatar  avatar

Forkers

leonardb laymer

apxr_run's Issues

Slow to use huge databases to setup synapses, should have option to export synapses to disc (to reuse this)

As both projects use Apache 2 licenses, can use Erlang functions from C/C++ (see ClassCns.cxx),
but for lots of applications (such as https://github.com/SwuduSusuwu/SubStack/tree/trunk/cxx/ClassCns.cxx-based VirusAnalysis.cxx and ConversationCns.cxx) the clients do not have enough resources to load the databases (yet alone setup the synapses,)
but have enough resources to import synapses to use this.
Can you backup synapses to SQLite, csv, or some other storages for future uses?

src/agent_mgr/signal_aggregator.erl has "The are many other", should do "There are many other"

https://github.com/Rober-t/apxr_run/blob/master/src/agent_mgr/signal_aggregator.erl
0001-The-are-many-other-There-are-many-other.patch
Above Git patch, or below diff fix

diff --git a/src/agent_mgr/signal_aggregator.erl b/src/agent_mgr/signal_aggregator.erl
index c903663..2e73abc 100644
--- a/src/agent_mgr/signal_aggregator.erl
+++ b/src/agent_mgr/signal_aggregator.erl
@@ -34,9 +34,9 @@
 %%%      composes the scalar value by aggregating the input vectors, and then
 %%%      calculating the dot product of the input vectors and the synaptic
 %%%      weights. Another way to calculate a scalar value from the input and
-%%%      weight vectors is by multiplying the corresponding input signals by
+%o%%      weight vectors is by multiplying the corresponding input signals by
 %%%      their weights, but instead of adding the resulting multiplied values,
-%%%      we multiply them. The are many other types of aggregation functions
+%%%      we multiply them. There are many other types of aggregation functions
 %%%      that could be created. We can also add normalizer functions, which
 %%%      could normalize the input signals. The normalizers could be
 %%%      implemented as part of the aggregator functions, although it
@@ -145,4 +145,4 @@ mult_product([], [], Acc) ->
 mult([I | Input], [{W, _LPs} | WeightsP], Acc) ->
   mult(Input, WeightsP, I * W * Acc);
 mult([], [], Acc) ->
-  Acc.
\ No newline at end of file
+  Acc.

Recommend Projects

  • React photo React

    A declarative, efficient, and flexible JavaScript library for building user interfaces.

  • Vue.js photo Vue.js

    ๐Ÿ–– Vue.js is a progressive, incrementally-adoptable JavaScript framework for building UI on the web.

  • Typescript photo Typescript

    TypeScript is a superset of JavaScript that compiles to clean JavaScript output.

  • TensorFlow photo TensorFlow

    An Open Source Machine Learning Framework for Everyone

  • Django photo Django

    The Web framework for perfectionists with deadlines.

  • D3 photo D3

    Bring data to life with SVG, Canvas and HTML. ๐Ÿ“Š๐Ÿ“ˆ๐ŸŽ‰

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.

  • Game

    Some thing interesting about game, make everyone happy.

Recommend Org

  • Facebook photo Facebook

    We are working to build community through open source technology. NB: members must have two-factor auth.

  • Microsoft photo Microsoft

    Open source projects and samples from Microsoft.

  • Google photo Google

    Google โค๏ธ Open Source for everyone.

  • D3 photo D3

    Data-Driven Documents codes.