semvec/pypi-packages huggingface dataset:
pytorchrl 3.2.15
Disributed RL implementations with ray and pytorch.

## PyTorchRL: A PyTorch library for reinforcement learning

Deep Reinforcement learning (DRL) has been very successful in recent years but current methods still require vast amounts of data to solve non-trivial environments. Scaling to solve more complex tasks requires frameworks that are flexible enough to allow prototyping and testing of new ideas, yet avoiding the impractically slow experimental turnaround times associated to single-threaded implementations. PyTorchRL is a pytorch-based library for DRL that allows to easily assemble RL agents using a set of core reusable and easily extendable sub-modules as building blocks. To reduce training times, PyTorchRL allows scaling agents with a parameterizable component called Scheme, that permits to define distributed architectures with great flexibility by specifying which operations should be decoupled, which should be parallelized, and how parallel tasks should be synchronized.

### Installation

```
    conda create -y -n pytorchrl
    conda activate pytorchrl

    conda install pytorch torchvision cudatoolkit -c pytorch

    pip install pytorchrl gym[atari,accept-rom-license]==0.22.0 wandb opencv-python hydra-core
```

### Documentation

PyTorchRL documentation can be found [here](https://pytorchrl.readthedocs.io/en/latest/).

### Citing PyTorchRL

Here is the [paper](https://arxiv.org/abs/2007.02622)

```
@misc{bou2021pytorchrl,
      title={PyTorchRL: Modular and Distributed Reinforcement Learning in PyTorch},
      author={Albert Bou and Gianni De Fabritiis},
      year={2021},
      eprint={2007.02622},
      archivePrefix={arXiv},
      primaryClass={cs.CV}
}
```
Mouritech-LoggingPerformance1 0.0.2
A Mouritech package
Requires Python: >=3.7

## Package Name 
Mouritech_LoggingPerformance

''' Performance in python.
This is the project ,Whenever you need to check the performance of the code like time taken by the code to perform some task we will use this package in our module'''
a

## Requirements 
'''For running this, you need to have python3 installed on your system'''


## Debugging tools 

'''supported tools pycharm ,Anakonda ,Visual Studio etc...


## Installation 

Install my-project with Python
Install Mouritech_LoggingPerformance


  pip install  Mouritech_LoggingPerformance
  cd  Mouritech_LoggingPerformance

  (globally )

pip install -i https://test.pypi.org/simple/ Mouritech-LoggingPerformance


## Steps 

pip install -i https://test.pypi.org/simple/ Mouritech-LoggingPerformance

pip install Mouritech_LoggingPerformance


from Mouritech_LoggingPerformance.Performance import PerformanceLogger
from LogPerformance import PerformanceLogger

PerformanceLogger(

)



### Receiver Example  

# import time module 
import time

'''Importing our custom package from module Logperformance'''
from Mouritech_LoggingPerformance.LogPerformance import PerformanceLogger

# Create an instance of PerformanceLogger with a log file
logger = PerformanceLogger(__name__, log_file='performance.log')

# Use the logger to measure function performance
@logger.log_performance
def Disarum():
    '''Code which checks the Provided Number is Disarum number or Not'''
    num=int(input('Enter Num value:'))
    result=0
    power=1
    for x in str(num):
        y=int(x)

        '''Logic to check the disarum Number '''
        result= result + y**power
        power=power+1

        '''If the provided number is same as resultant number then it will be disarum number '''
    if num==result:
        print(f'The provide {num} is Disarum')
    else:
        print(f'The Provided {num} is Not a Disarum Number')
    

    '''Time taken by the funtion to excute the output '''
    time.sleep(1)

# Call the function
Disarum()



## Output :
'''The Provided Number is Disarum Number or Not Disarum number '''


2023-06-01 11:48:05,439 - __main__ - INFO - Function 'Disarum' executed in = started at 1685600283.4058442   ended at 1685600285.4397306 = 2.0339 seconds