garage | A toolkit for reproducible reinforcement learning research | Machine Learning library
kandi X-RAY | garage Summary
kandi X-RAY | garage Summary
garage is a toolkit for developing and evaluating reinforcement learning algorithms, and an accompanying library of state-of-the-art implementations built using that toolkit.
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Top functions reviewed by kandi - BETA
- Builds a Half Checheetah model .
- Creates a ML1 environment for the given context .
- Creates a Metawatch .
- Creates a simple meta - world model .
- Create point envs .
- Evaluate metaw .
- Evaluate TP10 .
- Top - level T1 T1 .
- Evaluate the model .
- Initialize target policy .
garage Key Features
garage Examples and Code Snippets
Lines of Code : 27
License : No License
Copy@fast
Feature: Long-Term Garage Parking feature
The parking lot calculator can calculate costs for Long-Term Garage parking.
Scenario Outline: Calculate LongTermGarage Parking Cost
Given parking lot is LongTermGarage
And parking duration is
Wh mqtt:
broker: {{Broker IP}}
discovery: True
username: "your mqtt username"
password: "your mqtt password"
topic_prefix: "garage"
on_message:
topic: "garageDoor/trigger"
then:
- switch.turn_on: garageDoorTemplate
client.publ cover:
- platform: mqtt
name: Garage Door
friendly_name: Garage
state_topic: "garage/door"
command_topic: "garage/button"
payload_open: "OPEN"
payload_close: "OPEN"
payload_stop: "OPEN"
state_open: "OPENED"
state def instructions():
print('***************************************************************')
print('Welcome to: Friday the 13th Text Based Game')
print('Move Between Rooms, Collect all 6 items')
print('Once you have all 6 iout = df.explode(df.columns.tolist()).reindex(['Reviewer_name','Review_date','Review_overall_rating','Review_title','Review_content'], axis=1)
Reviewer_name Review_date Rdata = ...
for device in data[0]["devices"]:
indoor_temp = device["thermostat"]["indoorTemperature"]
heat_set_point = device["changeableValues"]["heatSetpoint"]["value"]
print("Device ID: {}".format(device["deviceID"]))
prdf.drop_duplicates()
def main()
...
return df
if __name__ == '__main__':
df = main()
df.to_csv(f'{today}HPD.csv', index=False)
@dataclass(eq=True, order=True)
class House:
Address: str
Bedrooms: int
Bathrooms: int
Garage: bool
Price: float
# your code...
@dataclass(order=True)
class House:
Address: str
Bedrooms: intimport glob
import json
file_dir = 'wkdir1/' #file location
files = glob.glob(file_dir+'*.json')
key = 'Bedroom'
files_with_key = []
for fl in files:
f = open(fl)
json_data = json.load(f)
if key == json_data['room']['label']:
Community Discussions
Trending Discussions on garage
QUESTION
Currently I'm using Woocommerce Short_Description in Details Order answer code to show the product excerpt on WooCommerce checkout page:
...ANSWER
Answered 2022-Mar-13 at 11:45To display the short product description you can use:
QUESTION
In Jetpack Compose, when using Text, we can center text using TextAlign:
ANSWER
Answered 2022-Jan-26 at 10:17You can define the textAlign in the style parameter:
QUESTION
Please see the following minimal reproducible example.
...ANSWER
Answered 2022-Jan-15 at 18:38You could try this:
QUESTION
I have a Node.js Google cloud function which I now try to modularize into two js modules. It works fine locally on my machine but when trying to deploy to Google I get the following error:
ERROR: (gcloud.functions.deploy) OperationError: code=3, message=Build failed: npm ERR! @babel/cli not accessible from data-model
My main-function is using my data-model module via the following entry in package.json:
ANSWER
Answered 2022-Jan-11 at 15:37I finally managed to solve this, got a bit side-tracked by the babel/cli error message that CloudFunction threw.
The issue was that my data-model module was in another directory:
"data-model": "file:../../data-model",
I put it inside the main-function instead:
"data-model": "file:data-model",
and it works just fine to deploy to cloud functions.
Why it is so I have no clue but it is kind of documented in the Google Cloud Docs too:
The code for this local module should be stored somewhere other than the node_modules folder within your function's root directory.
QUESTION
$sql = DB::table('laravel_products')
->insert(array(
'name' => $name,
'price' => $price,
'qty' => $qty,
'description' => $description,
'uruu' => $uruu,
'garage' => $garage,
'duureg' => $duureg,
'tagt' => $tagt,
'talbai' => $talbai,
'haalga' => $haalga,
'tsonh' => $tsonh,
'shal' => $shal,
'tsonhtoo' => $ttsonh,
'hdawhar' => $bdawhar,
'lizing' => $lizing,
'utas' => $utas,
'email' => $email,
'hereg' => $hereg,
'bairshil' => $bairshil,
'bairlal' => $bairlal,
'ashig' => $ashigon,
'zahi' => $zahi,
'image' => $data
));
$lastInsertedID = $sql->lastInsertId();
ANSWER
Answered 2021-Dec-12 at 04:30If you want to get the last inserted ID like that you can call that method on the PDO instance directly:
QUESTION
I don't know a lot of mysql and have an error in my sql script. Currently running mysql 8.0.24. Does anyone know what might be the problem?
Error: https://prnt.sc/226xk5x
Sql:
...ANSWER
Answered 2021-Dec-07 at 18:43Your CHECK constraint does not reference the column. Or any column, actually. By using single-quotes, you're using a string literal, not a column name.
QUESTION
#include
using namespace std;
class car{
string owner;
string car_num;
string issue_date;
car(string o, string cn, string id)
{
owner = o;
car_num = cn;
issue_date = id;
}
void getInfo()
{
cout << "Car's Owner's Name : " << owner << endl;
cout << "Cars' Number : " << car_num << endl;
cout << "Car's Issue Date : " << issue_date << endl;
}
};
int main()
{
int n;
cout << "Enter total number of cars stored in your garage : \n";
cin >> n;
car c1[n]; //incomplete code due to the issue
return 0;
}
ANSWER
Answered 2021-Dec-02 at 15:21Use pointer array instead.e.g.
QUESTION
I have a DataFrame that contains some (text-) cleaned ads in one column and some very basic description of the same ads in one other column. I also have term frequencies stored in a dictionary in 'keyword':frequency format.
Task would be to purge all terms from the list in the df that falls below a certain cutpoint level of frequency.
ANSWER
Answered 2021-Nov-12 at 20:53IIUC, try:
- use
explodeto split the list to individual rows groupbyandtransformto get the count of the keyword in the dataframe and keep only rows where the "count" is greater than the cutoffgroupbyandaggto get the original DataFrame structure.
QUESTION
I have an example project and need to search for strings using the stringr package. In the example, to eliminate other case spellings I started with str_to_lower(example$remarks), which made the remarks all lower case. The remarks column describes residential properties.
I need to search for the word "shop". However, the word "shopping" is also in the remarks column and I don't want that word.
Some observations: a) Have only the word "shop"; b) Have only the word "shopping"; c) Have neither the words "shop" or "shopping"; d) Have BOTH the words "shop" & "shopping".
When using str_detect(), I want it to give me a TRUE for detecting the word "shop", but I DO NOT want it to give me a TRUE for detecting the string "shop" within the word "shopping". Currently, if I run str_detect(example$remarks, "shop") I get a TRUE for both the words "shop" and "shopping". Effectively, I ONLY want a TRUE for the 4-character string "shop" and if the characters "shop" appear but have any other characters after it like shop(ping), I want the code to exclude detecting it and not identifying it as TRUE.
Also, if the remarks contain BOTH the words "shop" and "shopping", I would like the result to be TRUE only for detecting "shop" but not "shopping".
Ultimately, I'm hoping one line of code using str_detect() can give me the result of:
- If the remarks observation has only the word "shop" =
TRUE - If the remarks observation has only the word "shopping" =
FALSE - If the remarks observation has neither the words "shop" or "shopping" =
FALSE - If the remarks observation has both the words "shop" AND "shopping" =
TRUEfor detecting ONLY the 4-character string "shop" and it DOES not output aTRUEbecause of the word "shopping".
I need all of the observations to remain in the dataset and cannot exclude them because I need to create a new column, which I have labeled shop_YN, that give a "Yes" for observations with only the 4-character string "shop". Once I have the correct str_detect() code, I plan to wrap the results in a mutate() and if_else() function as follows (except I don't know what to code to use inside str_detect() to get the results I need):
shop_YN <- example %>% mutate(shop_YN = if_else(str_detect(example$remarks, ), "Yes", "No"))
Here is a sample of the data using the dput():
ANSWER
Answered 2021-Oct-29 at 21:29You are probably looking for a word boundary here (\\b). Wrap the desired pattern between two word boundaries to match just the word, but not parts of longer words.
QUESTION
I am trying to scrape multiple pages from multiple URLS efficiently. I have been able to scrape multiple pages from one URL successfully, but unable to implement this for multiple URLs. Any and help would be greatly appreciated. Thank you.
Current Loop Code:
...ANSWER
Answered 2021-Oct-26 at 06:22You can combine for loops with Python's range() function.
The range() function provides a sequence of integers based upon the function's arguments.
Community Discussions, Code Snippets contain sources that include Stack Exchange Network
Vulnerabilities
No vulnerabilities reported
Install garage
You can use garage 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.
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