Rainy | umbrella Deep RL agents with PyTorch umbrella | Reinforcement Learning library

by kngwyu Python Version: 0.8.0 License: Apache-2.0

X-Ray Key Features Code Snippets(1)Community Discussions(10)Vulnerabilities Install Support

kandi X-RAY | Rainy Summary

Rainy is a Python library typically used in Artificial Intelligence, Reinforcement Learning, Pytorch applications. Rainy has no bugs, it has no vulnerabilities, it has build file available, it has a Permissive License and it has low support. You can install using 'pip install Rainy' or download it from GitHub, PyPI.

Reinforcement learning utilities and algrithm implementations using PyTorch.

Support

Quality

Security

License

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Support

Rainy has a low active ecosystem.

It has 24 star(s) with 2 fork(s). There are 2 watchers for this library.

It had no major release in the last 12 months.

There are 5 open issues and 10 have been closed. On average issues are closed in 59 days. There are no pull requests.

It has a neutral sentiment in the developer community.

The latest version of Rainy is 0.8.0

Quality

Rainy has no bugs reported.

Security

Rainy has no vulnerabilities reported, and its dependent libraries have no vulnerabilities reported.

License

Rainy is licensed under the Apache-2.0 License. This license is Permissive.

Permissive licenses have the least restrictions, and you can use them in most projects.

Reuse

Rainy releases are available to install and integrate.

Deployable package is available in PyPI.

Build file is available. You can build the component from source.

Installation instructions are not available. Examples and code snippets are available.

Top functions reviewed by kandi - BETA

kandi has reviewed Rainy and discovered the below as its top functions. This is intended to give you an instant insight into Rainy implemented functionality, and help decide if they suit your requirements.

Train the model
Compute the next OO operator
Calculate pmu from counts
Compute the PMU from x
Train the network
Return the network module corresponding to the given name
Compute the penalized policy loss
Compute next OO operator
Generate a config
Factory function for pybullet
Convert a function to click Option
Create a convolutional network
Loop forever
Create a NetFunctionOCNetworkOC network
Train the agent
Forward computation
Set the return value
Return a scala convolutional convolutional network
Save the state of the episode
Wrapper for pybullet_parant
Save the model to file
Train all episodes
Reset the agent
Convert a function to cls
Set GAE returns
Load data from file
Performs a single step
Train experiment

Get all kandi verified functions for this library.

Rainy Key Features

No Key Features are available at this moment for Rainy.

Rainy Examples and Code Snippets

Rainy,Example

Python

Lines of Code : 38

License : Permissive (Apache-2.0)

Copy

import os

from torch.optim import RMSprop

import rainy
from rainy import Config, net
from rainy.agents import DQNAgent
from rainy.envs import Atari
from rainy.lib.explore import EpsGreedy, LinearCooler


@rainy.main(DQNAgent, script_path=os.path.re

Community Discussions

Trending Discussions on Rainy

Using regex to remove sentence after occurrence of key phrase python

Flatten nested dictionary into a list of lists

How to keep track of number of occurrences between two dependent LinkedLists?

how to determine season dry or rainy in temporal analysis using R?

get a set of unique values from nested list

Plotting two boxplots using the same variable in one figure in base R

Vue 3 function that returns src

Conditional probability for Markov model

Copy paste a Naive Bayes example code on vscode but got errors

Delete files with certain name in all subdirectories

QUESTION

Using regex to remove sentence after occurrence of key phrase python

Asked 2021-May-27 at 20:39

I am looking for a regex solution to remove any words in the rest of the sentence after the occurrence of a key phrase.

Example

sentence = "The weather forecast for today is mostly sunny. The forecast for tomorrow will be rainy. The rest of the week..."

Key_phrase = "for tomorrow"

Desired output = "The weather forecast for today is mostly sunny. The forecast. The rest of the week..."

Attempt

...

ANSWER

Answered 2021-May-27 at 13:36

Using re.sub

Ex:

Source https://stackoverflow.com/questions/67723222

QUESTION

Flatten nested dictionary into a list of lists

Asked 2021-May-23 at 14:03

I have a code that as a result gets a nested dictionary like this:

...

ANSWER

Answered 2021-May-23 at 14:03

You can use a recursive generator function:

Source https://stackoverflow.com/questions/67660551

QUESTION

How to keep track of number of occurrences between two dependent LinkedLists?

Asked 2021-May-17 at 21:15

I'm having some trouble figuring out how to keep track of occurrences between two dependent LinkedLists.

Let me elaborate with an example:

These are the linked lists in question.

They are dependent because each value in first list corresponds to the value in the second list with the same index i. Both lists are always the same length.

...

ANSWER

Answered 2021-May-17 at 21:15

You may do that with a Map.

The key of the outer map is the weather (sunny, rainy etc.)
The value is another map which contains each possible value (yes, no, maybe...) and the number of times that value occurs.

Something like this to merge the two lists:

Source https://stackoverflow.com/questions/67576863

QUESTION

how to determine season dry or rainy in temporal analysis using R?

Asked 2021-May-01 at 21:45

I have the data temporal of temperature, i would like determinate if date be to season dry or rainy.

In my coutry the season dry start in May up to October, and season rainy start in November up to April.

Would be possible create a column with this information in package dplyr ou other?

my data-frame in:

...

ANSWER

Answered 2021-May-01 at 20:43

One option is to extract the month after converting to Date class, create a condition in case_when to return 'dry', 'rainy' based on the values of 'Month' column

Source https://stackoverflow.com/questions/67350662

QUESTION

get a set of unique values from nested list

Asked 2021-Apr-25 at 21:56

I have this nested list X_train

...

ANSWER

Answered 2021-Apr-25 at 21:17

You can zip() the list to get the columns. Unpacking the columns with * is the trick here. Then just take sets of the columns:

Source https://stackoverflow.com/questions/67258334

QUESTION

Plotting two boxplots using the same variable in one figure in base R

Asked 2021-Apr-24 at 13:05

I'm trying to plot two boxplots in the same figure in base R, one boxplot for the values of PM2.5 of which RAIN is 0 and hour is 12, the other for values of PM2.5 when RAIN is greater than 0 and hour is 12. This is a small part of my data set, called 'dat':

...

ANSWER

Answered 2021-Apr-24 at 12:16

ggplot is usually the answer:

Source https://stackoverflow.com/questions/67242395

QUESTION

Vue 3 function that returns src

Asked 2021-Apr-21 at 06:18

I have this vue function. That should return the img srs, dynamically. For some reasons, it is not reading the string as a local file. Image is not showing.

...

ANSWER

Answered 2021-Apr-21 at 06:18

You need to use require method to get the local image render in Vue.app.

Source https://stackoverflow.com/questions/67190217

QUESTION

Conditional probability for Markov model

Asked 2021-Apr-19 at 12:24

My data set consists of daily rainfall records for 31 days (zero represents no rain and non-zero entry represents rain). I required to compute the conditional probability in 4 different cases as explained below:

rainy day .... rainy day
rainy day ... non-rainy day
non-rainy day ... rainy-day
non-rainy day ... non-rainy-day

May someone suggest to me how to compute the conditional probabilities for the above-mentioned cases.

The data set and sample script are as below:

...

ANSWER

Answered 2021-Apr-19 at 12:21

This loops through the list and checks.

Source https://stackoverflow.com/questions/67161755

QUESTION

Copy paste a Naive Bayes example code on vscode but got errors

Asked 2021-Apr-14 at 19:59

I copied the code from datacamp to try the Naive Bayes classification on my own on python 3.8 . but when run the code the compiler gives this error

...

ANSWER

Answered 2021-Apr-14 at 19:59

What happens is that features should be a list to be passed to model.fit, currently they are type zip

Source https://stackoverflow.com/questions/67096686

QUESTION

Delete files with certain name in all subdirectories

Asked 2021-Mar-27 at 12:14

I would like to remove files with a certain name from all subdirectories. For example, my working directory is as follows: "main directory/weather_data --> weather data contains the subdirectories D0 and D1. In these subdirectories there are files with the names "rainy weather_D0.txt" and sunny weather_D0.txt". from both subdirectories (D0 and D1) I would like to remove the file with the name "rainy weather.txt"

I have tried to do it like this in R

...

ANSWER

Answered 2021-Mar-27 at 12:07

Since your text files are in subdirectories of weather_data you need to add the recursive = TRUE argument to list.files() - otherwise it will only find "D0" and "D1". The pattern also will not find the files because $ means end of line, so it will only find files that end with "rainy weather" (and your files begin with it). I suggest changing pattern to just "rainy weather".

Source https://stackoverflow.com/questions/66830392

Community Discussions, Code Snippets contain sources that include Stack Exchange Network

Vulnerabilities

No vulnerabilities reported

Install Rainy

You can install using 'pip install Rainy' or download it from GitHub, PyPI.
You can use Rainy like any standard Python library. You will need to make sure that you have a development environment consisting of a Python distribution including header files, a compiler, pip, and git installed. Make sure that your pip, setuptools, and wheel are up to date. When using pip it is generally recommended to install packages in a virtual environment to avoid changes to the system.

Support

For any new features, suggestions and bugs create an issue on GitHub. If you have any questions check and ask questions on community page Stack Overflow .

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