Examples: query, "exact match", wildcard*, wild?ard, wild*rd
Fuzzy search: cake~ (finds cakes, bake)
Term boost: "red velvet"^4, chocolate^2
Field grouping: tags:(+work -"fun-stuff")
Escaping: Escape characters +-&|!(){}[]^"~*?:\ with \, e.g. \+
Range search: properties.timestamp:[1587729413488 TO *] (inclusive), properties.title:{A TO Z}(excluding A and Z)
Combinations: chocolate AND vanilla, chocolate OR vanilla, (chocolate OR vanilla) NOT "vanilla pudding"
Field search: properties.title:"The Title" AND text
Unanswered
What Sort Of Integration Is Possible With Clearml And Sagemaker? On The Page


Hi @<1532532498972545024:profile|LittleReindeer37> @<1523701205467926528:profile|AgitatedDove14>
I got the session with a bit of "hacking".
See this script:

import boto3, requests, json
from urllib.parse import urlparse

def get_notebook_data():
    log_path = "/opt/ml/metadata/resource-metadata.json"
    with open(log_path, "r") as logs:
        _logs = json.load(logs)
    return _logs

notebook_data = get_notebook_data()
client = boto3.client("sagemaker")
response = client.create_presigned_domain_url(
    DomainId=notebook_data["DomainId"],
    UserProfileName=notebook_data["UserProfileName"]
)
authorized_url = response["AuthorizedUrl"]
authorized_url_parsed = urlparse(authorized_url)
unauthorized_url = authorized_url_parsed.scheme + "://" + authorized_url_parsed.netloc
with requests.Session() as s:
    s.get(authorized_url)
    print(s.get(unauthorized_url + "/jupyter/default/api/sessions").content)

Basically, we can get the session directly from AWS, but we need to be authenticated.
One way I found was to create a presigned url through boto3, by getting the domain id and profile name from a resoure-metadata file that is found on the machine None .
Then use that to get the session...
Maybe there are some other ways to do this (safer), but this is a good start. We know it's possible

  
  
Posted one year ago
141 Views
0 Answers
one year ago
one year ago