row_id int64 0 48.4k | init_message stringlengths 1 342k | conversation_hash stringlengths 32 32 | scores dict |
|---|---|---|---|
46,988 | write a professional ffmpeg code that can make a unique audio "radio" effect on input audio without losing quality: as like as: ffmpeg -i AUDIO.mp3 -filter:a "highpass=f=1375.4,volume=12.3dB" audio_result.mp3
but create a unique one without loosing quality! | f6220fd0a927fcf8c8793f8a334f3a3f | {
"intermediate": 0.3856160640716553,
"beginner": 0.20286552608013153,
"expert": 0.41151848435401917
} |
46,989 | write a professional ffmpeg code that can make a unique audio “radio” effect on input audio without losing quality: as like as: ffmpeg -i AUDIO.mp3 -filter:a “highpass=f=1375.4,volume=12.3dB” audio_result.mp3
but create a unique one without loosing quality! | 61396947a43bfface0528f01b498b2fd | {
"intermediate": 0.4195529818534851,
"beginner": 0.17866531014442444,
"expert": 0.40178173780441284
} |
46,990 | New-Item : Cannot find drive. A drive with the name 'Q' does not exist.
At C:\drivecreation.ps1:2 char:1
+ New-Item -Path "Q:\Home$" -ItemType Directory
+ ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
+ CategoryInfo : ObjectNotFound: (Q:String) [New-Item], DriveNotFoundException
+ FullyQualifiedErrorId... | 3bab272a70de35fddd7eba1bc78c1a61 | {
"intermediate": 0.44966378808021545,
"beginner": 0.31834954023361206,
"expert": 0.23198670148849487
} |
46,991 | #include <bits/stdc++.h>
#define N 1000
using namespace std;
struct hop
{
int x, y, id;
};
hop a[N+1];
int n, xuoi[N+3], dem;
bool cmp (hop A, hop B)
{
if (A.x!=B.x) return A.x > B.x;
else
if (A.y==B.y) return A.id > B.id;
else return A.y>B.y;
}
int main()
{
ios_base::sync_with_stdio(fal... | e7d0121700400221f5adca09e64b72b1 | {
"intermediate": 0.2765996754169464,
"beginner": 0.5085639953613281,
"expert": 0.21483632922172546
} |
46,992 | write a ffmpeg code to replace audio to video | 2181473d756735614667095650792403 | {
"intermediate": 0.5140331983566284,
"beginner": 0.15701451897621155,
"expert": 0.3289523422718048
} |
46,993 | for keithley 2651a sourcemeter Im connecting it with a GPIB to usb cable via my pc. and I have py visa installled I like to have it houtput a voltage could you give me some instruction code | 780e5e81fbc5b46f4a8532f124475dc9 | {
"intermediate": 0.46842342615127563,
"beginner": 0.2688594460487366,
"expert": 0.2627171277999878
} |
46,994 | Please modify the depth first search algorithm below to find all connected components in an undirected graph. Comment on where you made the modification. Your modified algorithm needs to print out each component ID (starting from 1) and the corresponding vertices.
For example, take a directed graph with 6 vertices nam... | 0878f44a5908587bd063a796b0a0ab7d | {
"intermediate": 0.24484960734844208,
"beginner": 0.27772873640060425,
"expert": 0.4774216413497925
} |
46,995 | hi, can you create a ffmpeg 6.0 linux arg beauty pass using a night time lut and modifying this arg: ffmpeg' -hide_banner -y -i %04d.exr -pix_fmt yuv420p10le -c:v libx265 -r 30 -preset fast -crf 5 | 4043b7bc17805df08e047feaaa1ed31e | {
"intermediate": 0.575837254524231,
"beginner": 0.1897815614938736,
"expert": 0.23438118398189545
} |
46,996 | temperature
place_id avg_temp
1 1 -21
2 2 -13
3 3 -9
4 4 23
5 5 -1
6 6 0
7 7 6
8 8 4
9 9 15
10 10 -12
Fetch the 5 coldest places from the temperature tabl in sql | 8f3c23d0ab3f0940f7f2285e25fcac73 | {
"intermediate": 0.4496818482875824,
"beginner": 0.2510967254638672,
"expert": 0.2992214262485504
} |
46,997 | import spacy
import pandas as pd
import random
from spacy.training import Example
nlp = spacy.blank("en")
"""
train_data = [
("This is a complete sentence.", {"cats": {"complete": 1, "incomplete": 0}}),
("Incomplete sentence.", {"cats": {"complete": 0, "incomplete": 1}}),
]
"""
csv_path = "dataset.csv"
data ... | 7afbc0e5e08869bd70343ef618f0c368 | {
"intermediate": 0.37553682923316956,
"beginner": 0.36764511466026306,
"expert": 0.25681808590888977
} |
46,998 | i have following code to train a LSTM model on my dataset:
# %%
from sklearn.preprocessing import StandardScaler
import pandas as pd
import numpy as np
from tensorflow import keras
import joblib
from tensorflow.keras.models import Sequential
from tensorflow.keras.layers import LSTM,Dense,Dropout
import os
# %%
csv_dir... | fef51be0c275ad846bd8afeff1bb6113 | {
"intermediate": 0.3564283549785614,
"beginner": 0.3367084562778473,
"expert": 0.3068631887435913
} |
46,999 | im working on ggogle collab what does this mean, For free permanent hosting and GPU upgrades, run `gradio deploy` from Terminal to deploy to Spaces (https://huggingface.co/spaces) | 9641722a8b752ecb2da727cfff700cfa | {
"intermediate": 0.36391177773475647,
"beginner": 0.1709301620721817,
"expert": 0.46515804529190063
} |
47,000 | in servicenow business rule I have 3 fields (reference to the cmdb_ci_service table). Field 1 is the parent of field 2. The second is the parent of the third. (field 2 parent of the field 3)
I need a business rule that gives an error if:
- all fields are empty
- if only the first field is not empty, but the other t... | 7f0d04ad52f8bb9fc22e8caa373e1002 | {
"intermediate": 0.3855266869068146,
"beginner": 0.34365108609199524,
"expert": 0.2708222270011902
} |
47,001 | i have a very large size csv file
how can i know its shape whithout openning it | 34cd492f2c1546c57777b180b4194375 | {
"intermediate": 0.373808354139328,
"beginner": 0.2707742750644684,
"expert": 0.355417400598526
} |
47,002 | im using google collab script that someone else created, how do i run `gradio deploy` from Terminal to deploy to Spaces (https://huggingface.co/spaces), i don't have python, or any terminals set up | 4cc013eb659c693e5ef8715485c0d575 | {
"intermediate": 0.47552475333213806,
"beginner": 0.23178933560848236,
"expert": 0.2926858961582184
} |
47,003 | im training a tcn model on my dataset :
# %%
from sklearn.preprocessing import StandardScaler
import pandas as pd
import numpy as np
from tensorflow import keras
import joblib
from tensorflow.keras.models import Sequential
from tensorflow.keras.layers import LSTM,Dense,Dropout
import os
# %%
csv_directory = r"C:\Users... | f809a29840854a1b3353f2be7a526a3b | {
"intermediate": 0.5149767398834229,
"beginner": 0.2695019841194153,
"expert": 0.21552123129367828
} |
47,004 | (tok_embeddings): Embedding(2048, 288)
(dropout): Dropout(p=0.0, inplace=False)
(layers): ModuleList(
(0-5): 6 x TransformerBlock(
(attention): Attention(
(wq): Linear(in_features=288, out_features=288, bias=False)
(wk): Linear(in_features=288, out_features=288, bias=False)
(wv): Linear(in_features=288, out_features=28... | b2b5ae17c94c56d33fea4ca83ada7582 | {
"intermediate": 0.3200986683368683,
"beginner": 0.21535296738147736,
"expert": 0.4645483195781708
} |
47,005 | i have following code to calculate a generic scaler on my dataset
update the code so instead of StandardScaler it calculates MinMaxScaler:
def calculate_features_scaling_params(file_path, features_to_drop):
scaler = StandardScaler()
for chunk in pd.read_csv(file_path, chunksize=10000): # Adjust chunksize ba... | bbcd41ab365299b32af29090fb1f5847 | {
"intermediate": 0.27944111824035645,
"beginner": 0.4607892632484436,
"expert": 0.25976958870887756
} |
47,006 | # Set up logging configuration
logging.basicConfig(filename='crewai_chat.log', level=logging.DEBUG, format='%(asctime)s - %(levelname)s - Session: %(session_id)s - %(message)s')
# Generate a unique identifier for the session
session_id = str(uuid.uuid4())
# Create a Crew object
crew = Crew(
agents=[financial_analys... | e8f8c1f71d483d922fe8453f23e731e6 | {
"intermediate": 0.45721757411956787,
"beginner": 0.2523418664932251,
"expert": 0.2904405891895294
} |
47,007 | I want you to act as a programmar.programmar is a programming language. I will provide you with commands and you will interpret them. My first command is "I need help writing a program". | 4a2f3a75ac000f666af59ced32bc0f06 | {
"intermediate": 0.26501092314720154,
"beginner": 0.25000491738319397,
"expert": 0.48498421907424927
} |
47,008 | # Create tasks for your agents
task1 = Task(description='Review the latest swing trading oppurtunities for TSLA related to potentential options trade entering positions for puts and or calls, using the duckduckgo_search tool and follow up with yahoo_finance_news tool for further insight if neccessary. Identify key mark... | 8ad538ec77675bb7d7c352badc5cc86e | {
"intermediate": 0.3303404152393341,
"beginner": 0.4001777172088623,
"expert": 0.269481897354126
} |
47,009 | I am stuck with some issue with Json formatting in the script .Kindly help me and let me know where am I doing mistake:
// Add your code here
var pool_members_curr = {};
var pool_members_ui = {};
var device = '10.33.120.205';
var pool_name = 'pool-tcp-443-ey-test-20.20.20.52';
var request = {};
var midser... | 81679f73722bec768bb4742048f19586 | {
"intermediate": 0.3698769509792328,
"beginner": 0.4055939316749573,
"expert": 0.22452911734580994
} |
47,010 | I need a bash script
in a directory ..
loop over all the *.csv files
and print the file name then some stlying then
in each file check whether the file contains '(' or ')' | 25a8e214fc0f520cda688dc140ebe386 | {
"intermediate": 0.1887354701757431,
"beginner": 0.6867283582687378,
"expert": 0.1245361715555191
} |
47,011 | I need a bash script
for looping over *.csv files
for each file check the content of each file if '(' or ')' exits then print the file name | ab8a588d7d987e2b4954fa5e187de372 | {
"intermediate": 0.12125950306653976,
"beginner": 0.7933358550071716,
"expert": 0.08540469408035278
} |
47,012 | I need a bash script
for looping over *.csv files
for each file check the content of each file if ‘(’ or ‘)’ exits then print the file name
then print that content from the file | 54cf9b92240a2e17d9a7027bebc28782 | {
"intermediate": 0.18115626275539398,
"beginner": 0.7041513323783875,
"expert": 0.11469241231679916
} |
47,013 | I need a bash script
for looping over *.csv files
for each file check the content of each file if ‘(’ or ‘)’ exits then print the file name | 846004a1a18149c6f9203aea47ccc39a | {
"intermediate": 0.10820024460554123,
"beginner": 0.8252987265586853,
"expert": 0.06650097668170929
} |
47,014 | i have following code to train a LSTM model on my dataset:
# %%
from sklearn.preprocessing import StandardScaler
import pandas as pd
import numpy as np
from tensorflow import keras
import joblib
from tensorflow.keras.models import Sequential
from tensorflow.keras.layers import LSTM,Dense,Dropout
import os
# %%
csv_dir... | e16f2994e77515a656ed8db1c669d520 | {
"intermediate": 0.4664432108402252,
"beginner": 0.284995436668396,
"expert": 0.2485613077878952
} |
47,015 | Write very simple encryption algorithm on Lua. Algorithm provides encrypt(string, key) and decrypt(string, key) functions. The strength of the cipher is not important because it will be used in a computer game | 5329bb916dfa0c9b8ec0194870d426e9 | {
"intermediate": 0.349531352519989,
"beginner": 0.19619528949260712,
"expert": 0.45427340269088745
} |
47,016 | For each of the following Prolog expressions, write the equivalent Haskell expression without any use of [ and ] other than for the empty list []. Identify whether the expression is allowed by Haskell and, if not, explain why. Answer in detail.
[0|1].
[0, 1].
[0|[1]].
[0, [1]].
[0|[1|[2|[]]]] | 153ec57c23764f7808361f3682df1c3d | {
"intermediate": 0.33038267493247986,
"beginner": 0.3517893850803375,
"expert": 0.31782791018486023
} |
47,017 | how check total errors in every 1 minute using splunk | 65ac328336e3df1358740a77de2d4895 | {
"intermediate": 0.27887222170829773,
"beginner": 0.048228681087493896,
"expert": 0.6728991270065308
} |
47,018 | # Log the result
logging.info('Result of crew.kickoff(): %s', result)
# Log any dialogue messages from the crew object
for message in crew.dialogue_messages:
dialogue_logger.info('Dialogue message: %s', message)
# Configure the logging settings
logging.basicConfig(filename='options.log', level=logging.INFO, forma... | 8005e4e90a20bbc47d19774526672436 | {
"intermediate": 0.4169614613056183,
"beginner": 0.3772827386856079,
"expert": 0.205755814909935
} |
47,019 | Write Vigenere encryption algorithm on Lua. Algorithm provides encrypt(string, key) and decrypt(string, key) functions. The strength of the cipher is not important because it will be used in a computer game | 71c3294340f709061a81a4e9050406d5 | {
"intermediate": 0.33413195610046387,
"beginner": 0.2088598757982254,
"expert": 0.45700815320014954
} |
47,020 | f(x) {
C, 2 <= x < 5
0, poza
}
find the C parameter, such that this function would be a density function. write the solution in tex | 6ed4e80cb8290c65410161315e3b9f3a | {
"intermediate": 0.2617599070072174,
"beginner": 0.40153056383132935,
"expert": 0.33670952916145325
} |
47,021 | result = crew.kickoff() simple way to log this print function | 18170caf5e13623ebe7eb1ac8a61f795 | {
"intermediate": 0.3461241126060486,
"beginner": 0.4652761220932007,
"expert": 0.18859981000423431
} |
47,022 | https://www.facebook.com/siddhaarchitects This is my Facebook link can u analyse it | 00f89841790fe8584521e73a43380969 | {
"intermediate": 0.3531513810157776,
"beginner": 0.21869704127311707,
"expert": 0.42815154790878296
} |
47,023 | conda create -n transformers python=3.9
Fetching package metadata ...
CondaHTTPError: HTTP 000 CONNECTION FAILED for url | da88e269481169610934bc7392b9c6a9 | {
"intermediate": 0.4367520809173584,
"beginner": 0.24555768072605133,
"expert": 0.31769025325775146
} |
47,024 | {
"name": "InvalidArgumentError",
"message": "Graph execution error:
Detected at node 'mean_squared_error/SquaredDifference' defined at (most recent call last):
File \"c:\\Users\\arisa\\.conda\\envs\\tf\\lib\\runpy.py\", line 197, in _run_module_as_main
return _run_code(code, main_globals, None,
File \... | 23e8cb891a99f565318122bbd2735418 | {
"intermediate": 0.281398206949234,
"beginner": 0.34826910495758057,
"expert": 0.3703327178955078
} |
47,025 | set difference between two sets know what's added or removed in js | 123fc57167af56c3e45e54a4c468d13d | {
"intermediate": 0.30773505568504333,
"beginner": 0.4000660479068756,
"expert": 0.29219889640808105
} |
47,026 | {
"name": "ResourceExhaustedError",
"message": "Graph execution error:
OOM when allocating tensor with shape[21728] and type float on /job:localhost/replica:0/task:0/device:GPU:0 by allocator GPU_0_bfc
\t [[{{node concat}}]]
Hint: If you want to see a list of allocated tensors when OOM happens, add report_tensor_all... | 2c5b66835655a6a0bebf680285e2ffd0 | {
"intermediate": 0.300179660320282,
"beginner": 0.3396975100040436,
"expert": 0.36012282967567444
} |
47,027 | write a sql.py script that iterates through models.py file given a path and outputs a instruction.txt file containing the following :
for each class in models.py , if the class containing a field that is equal to ForeginKey() ( django ) create an Insert instruction for that class adding _id to the field name
for exam... | e8b7acc5d49f115a4f1841e4b0c710a3 | {
"intermediate": 0.4280316233634949,
"beginner": 0.37861523032188416,
"expert": 0.19335313141345978
} |
47,028 | I have resolved several issues concerning code and spring components maven versions and am now addressing modifications to the remaining incompatible batch service code.
.....rephrase it | 6fc94701ac414afeb8c381cad8c63118 | {
"intermediate": 0.32992473244667053,
"beginner": 0.3038342595100403,
"expert": 0.3662409484386444
} |
47,029 | here is my code :
# %%
from sklearn.preprocessing import StandardScaler
import pandas as pd
import numpy as np
from tensorflow import keras
import joblib
from tensorflow.keras.models import Sequential
from tensorflow.keras.layers import LSTM,Dense,Dropout
import os
# %%
csv_directory = r"C:\Users\arisa\Desktop\day_spo... | ba3da4892addf44d0f8c3b1ffad10f81 | {
"intermediate": 0.5108555555343628,
"beginner": 0.33795487880706787,
"expert": 0.15118961036205292
} |
47,030 | code:
# %%
from sklearn.preprocessing import StandardScaler
import pandas as pd
import numpy as np
from tensorflow import keras
import joblib
from tensorflow.keras.models import Sequential
from tensorflow.keras.layers import LSTM,Dense,Dropout
import os
# %%
csv_directory = r"C:\Users\arisa\Desktop\day_spot_summary"
c... | f9d6934cad98313dafa45bfa373540b3 | {
"intermediate": 0.4058266580104828,
"beginner": 0.37244248390197754,
"expert": 0.22173085808753967
} |
47,031 | i need appscript which will add new button in google docs, which will set default paragraphs to arial 12pt 1.5 interline | 5f620f3a7c744dc72e12276e2391d881 | {
"intermediate": 0.47463130950927734,
"beginner": 0.20786692202091217,
"expert": 0.3175017535686493
} |
47,032 | python import-request-elastic.py
/usr/lib/python3/dist-packages/urllib3/connectionpool.py:1062: InsecureRequestWarning: Unverified HTTPS request is being made to host 'elaas-inspec-dev.kb.elasticaas.ocb.equant.com'. Adding certificate verification is strongly advised. See: https://urllib3.readthedocs.io/en/1.26.x/advan... | 49a20b04368b28b523ffe37b840364cb | {
"intermediate": 0.4433022439479828,
"beginner": 0.3808145225048065,
"expert": 0.17588317394256592
} |
47,033 | is this the right way to use BatchNormalization:?
model = Sequential([
LSTM(2716, activation='tanh', input_shape=input_shape, return_sequences=True), # Adjusted for LSTM
Dropout(0.20),
# BatchNormalization(),
# LSTM(2716, activation='tanh', return_sequences=False), # Additional LSTM la... | 329a4e1be18768f1eef20709193f2251 | {
"intermediate": 0.379477322101593,
"beginner": 0.1522846221923828,
"expert": 0.46823811531066895
} |
47,034 | Objective: - To implement the concept of Joins
Joint Multiple Table (Equi Join): Sometimes we require to treat more than one table as
though manipulate data from all the tables as though the tables were not separate object
but one single entity. To achieve this, we have to join tables. Tables are joined on column
that ... | cd314ecf4f19e92d1da30d1c82382ace | {
"intermediate": 0.30916455388069153,
"beginner": 0.1711457520723343,
"expert": 0.519689679145813
} |
47,035 | import json
import re
import requests
from bs4 import BeautifulSoup
from urllib.parse import urlparse
class AppleMusicAPI:
def __init__(self):
self.session = requests.Session()
self.session.headers = {
'content-type': 'application/json;charset=utf-8',
'connection': 'keep-ali... | 6c06ad05a0dce94b9b649645a46f9406 | {
"intermediate": 0.27874755859375,
"beginner": 0.4992334842681885,
"expert": 0.22201895713806152
} |
47,036 | api.py:
import re
import json
import requests
from bs4 import BeautifulSoup
from urllib.parse import urlparse
from urllib.request import urlopen
from urllib.error import URLError, HTTPError
from utils import Cache
from utils import Config
from utils import logger
from api.parse import parseJson
class AppleMusic(ob... | 58a72d57f1075cf159d7634fbb72e5c1 | {
"intermediate": 0.44158756732940674,
"beginner": 0.38617774844169617,
"expert": 0.17223471403121948
} |
47,037 | api.py:
import re
import json
import requests
from bs4 import BeautifulSoup
from urllib.parse import urlparse
from urllib.request import urlopen
from urllib.error import URLError, HTTPError
from utils import Cache
from utils import Config
from utils import logger
from api.parse import parseJson
class AppleMusic(ob... | 2c3fc5411998edc4b630f9c3841bec9c | {
"intermediate": 0.411155641078949,
"beginner": 0.42896199226379395,
"expert": 0.1598823070526123
} |
47,038 | npm list --depth 0 gives `-- (empty) | 6b76dbb9da4fab9385fe52a24167fe18 | {
"intermediate": 0.34904050827026367,
"beginner": 0.2708413600921631,
"expert": 0.38011816143989563
} |
47,039 | In my react component that is using react-effector library I need to render a certain icon within depending on the effector store. Initial value of the store will be null so even if I change the value of the store later the icon doesn't appear because the component was already rendered. How can I rerender it when effec... | 04462bea7f1912d93dcc1dcb48011738 | {
"intermediate": 0.7894769310951233,
"beginner": 0.11550131440162659,
"expert": 0.09502172470092773
} |
47,040 | In my react component that is using react-effector library I need to render a certain icon within depending on the effector store. Initial value of the store will be null so even if I change the value of the store later the icon doesn’t appear because the component was already rendered. How can I rerender it when effec... | b187864fc85fc7d9cd508b166e4f679e | {
"intermediate": 0.8168677091598511,
"beginner": 0.09839267283678055,
"expert": 0.0847395583987236
} |
47,041 | explain | 842fe47129e1236e99022adee0092b7b | {
"intermediate": 0.3545367121696472,
"beginner": 0.31888994574546814,
"expert": 0.32657337188720703
} |
47,042 | I need google spreadsheet formula which will allow me to comma separation items, im using =join(", ";E2:E3) but this is not ignoring empty cells, please modify it for me to do so | 6c3312bb16e926fd1ffb4d9c099eb57c | {
"intermediate": 0.37461748719215393,
"beginner": 0.2425372153520584,
"expert": 0.3828452527523041
} |
47,043 | in javascript for leafletjs I want the user to click on the map and then use that location to retrieve building=house data 200 meters around that point | b4efe332ec2cc90d6876119ebf6412b6 | {
"intermediate": 0.569892942905426,
"beginner": 0.18643181025981903,
"expert": 0.24367523193359375
} |
47,044 | in this javascript for Leaflet I am fetching building outlines from the overpass api. Can I fill the building outlines 'let money = 100000;
const map = L.map('map').setView([51.5352028, 0.0054299], 17);
// fetch house data
// Event listener for when the map is clicked
map.on('click', function (e) {
// Update bui... | b31c405c07d5a720c5b62091275ae258 | {
"intermediate": 0.3992637097835541,
"beginner": 0.45278871059417725,
"expert": 0.1479475498199463
} |
47,045 | {
"cells": [
{
"cell_type": "markdown",
"metadata": {
"id": "3UeycYCyxDfE"
},
"source": [
"# TRANSLATOR"
]
},
{
"cell_type": "markdown",
"metadata": {
"id": "8BfUjVxBcz5N"
},
"source": [
"## instalation"
]
},
... | 468bb645dccdb1ccd88905b323884d49 | {
"intermediate": 0.3315049111843109,
"beginner": 0.37692585587501526,
"expert": 0.2915692627429962
} |
47,046 | ng -v
Error: You need to specify a command before moving on. Use '--help' to view the available commands. | fdc865c49d9536e67fbd5642cf11cf88 | {
"intermediate": 0.3284425735473633,
"beginner": 0.2726157009601593,
"expert": 0.39894169569015503
} |
47,047 | import spacy
from spacy.pipeline import EntityRuler
from negspacy.negation import Negex
nlp = spacy.load('en_ner_bc5cdr_md')
ruler = EntityRuler(nlp)
patterns = [{"label": "DISEASE", "pattern": "Diabetes Mellitus"},
{"label": "DISEASE", "pattern": "Diabetes"},
{"label": "DISEASE", "pattern": "Ty... | 333f65aaa531e959df4cd7b9d93b4b95 | {
"intermediate": 0.48383963108062744,
"beginner": 0.2394200712442398,
"expert": 0.27674028277397156
} |
47,048 | write me simple code to test and run it on the CELL processor | 80f3268bbaa9ea84892693e75a0264ee | {
"intermediate": 0.4695681035518646,
"beginner": 0.15547873079776764,
"expert": 0.37495315074920654
} |
47,049 | %%time
!pip install tensorflow-text
!pip install datasets
!pip install tensorflow_datasets
!pip install pydot
!pip install tensorflow
!pip install numpy
!pip install requests
!pip install matplotlib
!pip install tensorflow-text
!pip install datasets
!pip install pydot
!clear
Requirement already satisfied: tensorflow_d... | b629ed76b165b410e4969135b25befd1 | {
"intermediate": 0.3772393763065338,
"beginner": 0.44175300002098083,
"expert": 0.18100754916667938
} |
47,050 | How to register hit from player Colyseus | 20f3a9566d5b78be89fa0f93fd92015f | {
"intermediate": 0.32943108677864075,
"beginner": 0.3143779933452606,
"expert": 0.35619091987609863
} |
47,051 | hi | 446d4b88cfab9943f9de5e646df63337 | {
"intermediate": 0.3246487081050873,
"beginner": 0.27135494351387024,
"expert": 0.40399640798568726
} |
47,052 | Use the following format {
"points": [
{
"x": -0.023103713989257812,
"y": -1.9493672847747803,
"z": 0.004488945007324219
},
{
"x": 2.101100444793701,
"y": -1.6588795185089111,
"z": 0.006519317626953125
},
{
"x": 2.5287222862243652,
"y": -0.3213407993... | 868261cd863a20a1ecd407646a824a7d | {
"intermediate": 0.2756030261516571,
"beginner": 0.46766912937164307,
"expert": 0.25672781467437744
} |
47,053 | Requirement already satisfied: requests in c:\users\ixelo\appdata\local\packages\pythonsoftwarefoundation.python.3.10_qbz5n2kfra8p0\localcache\local-packages\python311\site-packages (2.31.0)
Requirement already satisfied: charset-normalizer<4,>=2 in c:\users\ixelo\appdata\local\packages\pythonsoftwarefoundation.python.... | a6151f4bc501f343dc50b9d26ae8ce61 | {
"intermediate": 0.3738146722316742,
"beginner": 0.4590801000595093,
"expert": 0.16710519790649414
} |
47,054 | I want to have a callback function ofr turtlebot4 lidar scanner how can I code that | 164c0f8ec7792bd6c4e983357b812f16 | {
"intermediate": 0.38892945647239685,
"beginner": 0.22529776394367218,
"expert": 0.3857727646827698
} |
47,055 | def write_vocab_file(filepath, vocab):
with open(filepath, 'w') as f:
for token in vocab:
print(token, file=f)
write_vocab_file('fr_vocab.txt', fr_vocab)
write_vocab_file('en_vocab.txt', en_vocab)
---------------------------------------------------------------------------
UnicodeEncodeError ... | 232504c9102a361e114f92e80599bc22 | {
"intermediate": 0.48174723982810974,
"beginner": 0.1701108068227768,
"expert": 0.34814202785491943
} |
47,056 | employees
id salary status
1 1 2016 married
2 2 5903 single
3 3 7608 married
4 4 6448 single
5 5 9551 married
6 6 6505 married
7 7 5753 single
8 8 7313 single
9 9 4219 single
10 10 3140 married
11 11 2702 married
12 12 3035 single
13 13 7590 single
14 14 3404 married
15 15 4551 married
As an owner of a vehicle factory,... | e15a2dca856ae5640c0eaa6307e815a0 | {
"intermediate": 0.31267809867858887,
"beginner": 0.3240755796432495,
"expert": 0.36324629187583923
} |
47,057 | Difference between GROUP by, HAVING in SQL and how to use them. Please explain as if i am a 5 year old kid | 418a40073fbf2623f8edcd68ca9b8205 | {
"intermediate": 0.3625272512435913,
"beginner": 0.3771844804286957,
"expert": 0.2602882385253906
} |
47,058 | Difference between GROUP by, HAVING in SQL and how to use them. Please explain as if i am a 5 year old kid | 16f2d1096547ba027a9bf789485a8389 | {
"intermediate": 0.3625272512435913,
"beginner": 0.3771844804286957,
"expert": 0.2602882385253906
} |
47,059 | max_length = 200
def tokenize_and_merge(fr_sentence, en_sentence):
fr_tokens = fr_tokenizer.tokenize(fr_sentence.np().decode('utf-8')).merge_dims(-2, -1)
fr_decode_tokens = fr_tokenizer.tokenize("[START]" + fr_sentence.np().decode('utf-8') + "[END]").merge_dims(-2, -1)
en_tokens = en_tokenizer.tokenize(en_... | 6412c544c0474e039c0eb4882e721018 | {
"intermediate": 0.3324238955974579,
"beginner": 0.31864476203918457,
"expert": 0.34893131256103516
} |
47,060 | which of these topics would be used for lidar in in ros2 :
/battery_state
/cliff_intensity
/cmd_audio
/cmd_lightring
/cmd_vel
/diagnostics
/diagnostics_agg
/diagnostics_toplevel_state
/dock_status
/function_calls
/hazard_detection
/hmi/buttons
/hmi/display
/hmi/display/message
/hmi/led
/imu
/interface_buttons
/ip
/ir_i... | 7088e83ad3d45afd8ffca9257c875b5d | {
"intermediate": 0.3128310739994049,
"beginner": 0.4821358919143677,
"expert": 0.20503301918506622
} |
47,061 | optimize this code for this code begin faster :
max_length = 200
fr_sequences = [fr_tokenizer.tokenize(french_sentence.numpy().decode('utf-8')).merge_dims(-2,-1)
for french_sentence, _ in dataset.take(127085)]
fr_ragged = tf.ragged.stack(fr_sequences)
fr_padded = fr_ragged.to_tensor(default_value=0, sh... | a4d4e70cdd3a75030492bd8210cc1740 | {
"intermediate": 0.21228128671646118,
"beginner": 0.34579524397850037,
"expert": 0.44192349910736084
} |
47,062 | max_length = 200
def process_sentence(sentence, tokenizer, add_start_end=False):
sentence_text = sentence.numpy().decode('utf-8')
if add_start_end:
sentence_text = "[START]" + sentence_text + "[END]"
tokenized_sentence = tokenizer.tokenize(sentence_text).merge_dims(-2, -1)
return tokenized_sentence
... | 02e14aac5fbd7db43a6e77e754304566 | {
"intermediate": 0.2965380847454071,
"beginner": 0.3611869513988495,
"expert": 0.3422749638557434
} |
47,063 | How can use this function static int updateDisplay(void){
int ret = 0;
switch (getDisplay())
{
case eHomeDisplay :
sprintf(cluster_screen.disp_name,currentDisplay);
cluster_screen.width = m_parameterInfo[eHomeDisplay].width;
cluster_screen.height = m_parameterInfo[eHomeDisplay].... | 8cd966590c36be3e786e0b943037837c | {
"intermediate": 0.48338520526885986,
"beginner": 0.35211658477783203,
"expert": 0.16449816524982452
} |
47,064 | make this code more faster :
max_length = 200
fr_sequences = [fr_tokenizer.tokenize(french_sentence.numpy().decode('utf-8')).merge_dims(-2,-1)
for french_sentence, _ in dataset.take(127085)]
fr_ragged = tf.ragged.stack(fr_sequences)
fr_padded = fr_ragged.to_tensor(default_value=0, shape=[None, None, max_length])
prin... | 3bd33def1c8d9a996cefe6ce19201ee6 | {
"intermediate": 0.3364163637161255,
"beginner": 0.4371351897716522,
"expert": 0.2264484465122223
} |
47,065 | add indicator in this code for the time :
batch_size = 1024 # Adjust batch size to your hardware capabilities.
def tokenize_sentences(french_sentence, english_sentence):
Tokenize French sentences (with and without start/end tokens) in a single pass
fr_sentence_text = french_sentence.numpy().decode('utf-8')
fr_sequenc... | 368bdf349112fa01f8756dbc617a277a | {
"intermediate": 0.4373420178890228,
"beginner": 0.276734858751297,
"expert": 0.2859231233596802
} |
47,066 | here is my code of generating timeseries for training my lstm model
i dont want to use specefic chunk_size, so update the code:
feature_data_scaled = pd.DataFrame(x_scaler.transform(feature_data), columns=feature_data.columns)
# Assuming target_data also needs to be scaled, apply scaler separately
... | 63fe7c9ddac06d70a10a1e5c8026f787 | {
"intermediate": 0.3920058310031891,
"beginner": 0.24170617759227753,
"expert": 0.3662879765033722
} |
47,067 | i have on my page phone numbers without country preffix and with it im using preg_replace to add a href
$buffer = preg_replace('~((\+48 |.*?)605 697 177)~s', "<a href=\"tel:<PRESIDIO_ANONYMIZED_PHONE_NUMBER>\">$1</a>", $buffer);
How can i achieve this to work? | 3b2f4b4a740ffbd40050adb9dc13c8a3 | {
"intermediate": 0.6281800866127014,
"beginner": 0.1026197075843811,
"expert": 0.26920026540756226
} |
47,068 | im trying to train and lstm model but the training goes like :
Epoch 1/2500
300/300 [==============================] - 24s 68ms/step - loss: 91.9649 - mae: 4.8055
Epoch 2/2500
300/300 [==============================] - 19s 64ms/step - loss: 92.7976 - mae: 4.4733
Epoch 3/2500
300/300 [==============================] - 1... | 448d7a9c04591dac1acc7c622ada43d6 | {
"intermediate": 0.19626682996749878,
"beginner": 0.24547572433948517,
"expert": 0.5582574605941772
} |
47,069 | Function pointer elements used in structures of function pointers can contain letters and numbers and will follow the pattern: ( * p_lowerCamelCase ) | c6023524b8145eba177a147747ca5360 | {
"intermediate": 0.2831232249736786,
"beginner": 0.4666634202003479,
"expert": 0.2502133250236511
} |
47,070 | A single set of typedefs shall be used in place of standard C variable definitions in all modules. | 2c594be39163a78f7606952702811043 | {
"intermediate": 0.25033462047576904,
"beginner": 0.4437524080276489,
"expert": 0.30591297149658203
} |
47,071 | I want to distribute numbers 1-50 in 10 groups. In such a way that when you add all 5 numbers in a group, all groups would have an equal total sum. | ab62825ac54afd04042658ef032744c2 | {
"intermediate": 0.38916414976119995,
"beginner": 0.2745732367038727,
"expert": 0.336262583732605
} |
47,072 | {
"cells": [
{
"cell_type": "markdown",
"metadata": {
"id": "3UeycYCyxDfE"
},
"source": [
"# TRANSLATOR"
]
},
{
"cell_type": "markdown",
"metadata": {
"id": "8BfUjVxBcz5N"
},
"source": [
"## instalation"
]
},
... | 9cda18cb025ca2853ef0a4a882bf7976 | {
"intermediate": 0.4142000377178192,
"beginner": 0.3563648760318756,
"expert": 0.22943517565727234
} |
47,073 | I want you to act as a contabo VPS Webhosting server. I will provide you with a list of webhosting services and you will act as their administrator. You will also be responsible for maintaining the service. My first suggestion request is "I need help setting up a VPS web hosting service." | 06c05f712f3bf361c50d5035a4a1b8f2 | {
"intermediate": 0.3415154218673706,
"beginner": 0.2971973717212677,
"expert": 0.3612872064113617
} |
47,074 | how to write mock test for the function static void gc_destroy(struct graphics_gc_priv *gc) {
g_free(gc);
gc = NULL;
} using MOCK_METHOD | eaaeb6e6d92e20f285da40bc581cb0c2 | {
"intermediate": 0.3410744369029999,
"beginner": 0.3550702631473541,
"expert": 0.303855299949646
} |
47,076 | in javascript I am dynamically displaying some text. the line breaks in ' messageDisplay.textContent = `Congratulations you have leased ${numberOfBuildings} buildings for £50,000! You will earn £${numberOfBuildings} per day from these leases. <br> You can now click on individual buildings on the map to buy them and st... | e3cd2da5932f7eeb6cf12c34eb30de2f | {
"intermediate": 0.424678236246109,
"beginner": 0.21679069101810455,
"expert": 0.35853105783462524
} |
47,077 | 这是我们的双模态双分支结构的forward函数： def forward_features(self, z, x, event_z, event_x,
mask_z=None, mask_x=None,
ce_template_mask=None, ce_keep_rate=None,
return_last_attn=False
):
# 分支1 处理流程
B, H, W = x.shape[0]... | e0c729f66dee0ec9148a70af3bb33614 | {
"intermediate": 0.30744272470474243,
"beginner": 0.5402919054031372,
"expert": 0.15226538479328156
} |
47,078 | 这是我们的双模态双分支结构的forward函数： def forward_features(self, z, x, event_z, event_x,
mask_z=None, mask_x=None,
ce_template_mask=None, ce_keep_rate=None,
return_last_attn=False
):
# 分支1 处理流程
B, H, W = x.shape[0], x.shape[2], x.shape[3]
x = self.patch_embed(x)
z = self.patch_embed(z)
z += self.pos_embed_z
x += self.pos_embed_x
... | 7fdcaa96bab01452c3821247d1492aa8 | {
"intermediate": 0.23947244882583618,
"beginner": 0.5990864634513855,
"expert": 0.16144105792045593
} |
47,079 | use python program to create a music recommendation system using and selecting apple music and spotify and tidal and deezer | ee755f88bb3dd51f6c20a7cd3477a74e | {
"intermediate": 0.34674975275993347,
"beginner": 0.1125892847776413,
"expert": 0.5406609773635864
} |
47,080 | in this javascript for leafletjs I am using e.stopPropagation(); on polygons to ensure that the map click event is also not called. This works in ensuring the polygon click event works and the map click event isn't called however it still gives an error that 'e.stopPropagation is not a function' - 'let money = 100000... | d5cc25ae509e4b4d340ef2622c67c789 | {
"intermediate": 0.4682261347770691,
"beginner": 0.3455926775932312,
"expert": 0.18618124723434448
} |
47,081 | applemusic_api.py:
import re
import base64
import pbkdf2
import hashlib
from Cryptodome.Hash import SHA256
from uuid import uuid4
from utils.utils import create_requests_session
from fingerprint import Fingerprint
import srp._pysrp as srp
srp.rfc5054_enable()
srp.no_username_in_x()
def b64enc(data):
return b... | 218672a4ac5e5d287b3df07e441a4df4 | {
"intermediate": 0.3362293839454651,
"beginner": 0.4676024615764618,
"expert": 0.19616815447807312
} |
47,082 | https://docs.crewai.com/core-concepts/Crews/ make this page clear | 667e3273831876eab9c06974833fcb1e | {
"intermediate": 0.30034875869750977,
"beginner": 0.24632121622562408,
"expert": 0.45333001017570496
} |
47,083 | public class CategoryConfig
{
public Dictionary<string, CategoryEntry> Categories { get; set; }
}
public class CategoryEntry
{
public List<string> Items { get; set; }
}
how to make it work with subcategories also | baaba7a8d390a135649f503103839794 | {
"intermediate": 0.3731980621814728,
"beginner": 0.3632202744483948,
"expert": 0.26358169317245483
} |
47,084 | 解读：# 将 4输入分开，构建新的相同模态结合的2输入，2分支
import math
import logging
from functools import partial
from collections import OrderedDict
from copy import deepcopy
import torch
import torch.nn as nn
import torch.nn.functional as F
from timm.models.layers import to_2tuple
from lib.models.layers.patch_embed import PatchEmbed, Patc... | 02eb864424691bded4a00e3c6bed4af6 | {
"intermediate": 0.27997615933418274,
"beginner": 0.4316779673099518,
"expert": 0.28834590315818787
} |
47,085 | in this javascript for leaflet.js when a building is colored green I want to remove it from the polygon click event and display a message saying 'You already own this building' - 'let money = 100000;
let numberOfBuildings = 0;
let dailybonus = 0;
let polygonClicked = false; // Flag to track if a polygon was clicked
co... | ed5bb6d2aac1bbe3b430a4955c74fd1d | {
"intermediate": 0.39260047674179077,
"beginner": 0.4234406650066376,
"expert": 0.18395882844924927
} |
47,086 | write me an elasticsearch query (using painless script IF NECESSARY) to update the theme array inside this document, removing "A" and adding "E" and "F"
{
"_index" : "v_dev_dataset_document_tags_index",
"_type" : "_doc",
"_id" : "ZhxNyI4BWFZ4mUbq-rFX",
"_score" : 0.0,
"_routing" : "6b576762832bcb86c5fef8f8a26dc3494470a... | b639b321e87190b3858a75364312c2dc | {
"intermediate": 0.35278984904289246,
"beginner": 0.3088909983634949,
"expert": 0.33831918239593506
} |
47,087 | Add necessary extra formatting to the following lecture. Do not summarize or skip any part. Do not break:
Welcome to this lecture. The title of this lecture is Organization and Work Design, part 4. This is the last part about organization and work design. We will talk about the modified charts. In the previous part we... | 91f146fa2fccaca17ae9ef202cf4166c | {
"intermediate": 0.259690523147583,
"beginner": 0.5160551071166992,
"expert": 0.22425436973571777
} |
47,088 | i have this es script, and i want to apply it to multiple documents, which i can pass the id of. i want the routing id. use _routing
document example:
{
"_index" : "v_dev_dataset_document_tags_index",
"_type" : "_doc",
"_id" : "ZhxNyI4BWFZ4mUbq-rFX",
"_score" : 0.0,
"_routing" : "6b576762832bcb86c5fef8f8a26dc3494470a2... | dd295f4c7955d4ae4c862965f90da694 | {
"intermediate": 0.39954787492752075,
"beginner": 0.35725921392440796,
"expert": 0.2431928664445877
} |
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