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import * as pulumi from '@pulumi/pulumi'; | |
import * as aws from '@pulumi/aws'; | |
import * as k8s from '@pulumi/kubernetes'; | |
export interface S3ServiceAccountArgs { | |
oidcProvider: aws.iam.OpenIdConnectProvider; | |
namespace: pulumi.Input<string>; | |
readOnly: pulumi.Input<boolean>; | |
} |
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import * as pulumi from '@pulumi/pulumi'; | |
import * as k8s from '@pulumi/kubernetes'; | |
export interface TraefikRouteArgs { | |
namespace: pulumi.Input<string>; | |
prefix: pulumi.Input<string>; | |
service: pulumi.Input<k8s.core.v1.Service>; | |
} | |
export default class TraefikRoute extends pulumi.ComponentResource { |
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sepal.length | sepal.width | petal.length | petal.width | variety | |
---|---|---|---|---|---|
5.1 | 3.5 | 1.4 | .2 | Setosa | |
4.9 | 3 | 1.4 | .2 | Setosa | |
4.7 | 3.2 | 1.3 | .2 | Setosa | |
4.6 | 3.1 | 1.5 | .2 | Setosa | |
5 | 3.6 | 1.4 | .2 | Setosa | |
5.4 | 3.9 | 1.7 | .4 | Setosa | |
4.6 | 3.4 | 1.4 | .3 | Setosa | |
5 | 3.4 | 1.5 | .2 | Setosa | |
4.4 | 2.9 | 1.4 | .2 | Setosa |
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FROM python:3.8-slim | |
WORKDIR /my_model | |
STOPSIGNAL SIGINT | |
ENV LISTEN_PORT 80 | |
# System dependencies | |
RUN apt update && apt install -y libgomp1 | |
RUN pip3 install poetry |
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curl --request POST \ | |
--url <APORIA_HOST>/v1/tenant-hasura/v1/graphql \ | |
--header 'Authorization: Bearer <TOKEN>' \ | |
--header 'Content-Type: application/json' \ | |
--data \ | |
'{ | |
"query": "query { models { id name versions { id name } } }", | |
"variables": {} | |
}' |
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import fetch from "node-fetch"; | |
const APORIA_TOKEN = "<TOKEN>"; | |
async function logPredictions(data) { | |
const query = ` | |
mutation LogPredict( | |
$modelId: String!, | |
$modelVersion: String!, | |
$environment: String!, |
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@metric("median") | |
def median_metric(data: DataFrame) -> Optional[Union[float, int]]: | |
"""Computes the median of a data series. | |
Args: | |
data: Data series. | |
Returns: | |
DataFrame median value or None if DataFrame is empty. | |
""" | |
series = df_to_series(data) | |
if len(series) == 0: |
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import pandas as pd | |
from sklearn.metrics import accuracy_score | |
data = pd.read_csv("data.csv") | |
print(accuracy_score(data["actual"], data["sentiment"])) |
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import openai | |
import re | |
system_prompt = """ | |
Why does my music player only shuffle songs by the same artist even when I select the "shuffle all" option? | |
take a deep breath and explain your thoughts in a <thoughts> tag shortly. Then, answer the question. | |
""" | |
response = openai.chat.completions.create( |
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