Ejemplos de AdvisorClient.list_trials en Python

Ejemplo n.º 1

Archivo: command.py Proyecto: gridl/advisor

def describe_studie(args):
  client = AdvisorClient()
  study = client.get_study_by_name(args.study_name)

  # Print study
  table = PrettyTable()
  table.field_names = [
      "Id", "Name", "Algorithm", "Status", "Create", "Updated"
  ]
  table.add_row([
      study.id, study.name, study.algorithm, study.status, study.created_time,
      study.updated_time
  ])
  print(table)

  # Print study configuration
  """
  table = PrettyTable()
  table.field_names = ["Configuration"]
  table.add_row([study.study_configuration])
  print(table)
  """
  pprint.pprint(json.loads(study.study_configuration))

  # Print related trials
  study_trials = client.list_trials(args.study_name)
  if (len(study_trials)) > 0:
    print_trials_as_table(study_trials)

Ejemplo n.º 2

Archivo: example.py Proyecto: zyhuster1/advisor

from advisor_client.model import TrialMetric
from advisor_client.client import AdvisorClient

client = AdvisorClient()

# Create Study
name = "Study"
study_configuration = {
    "goal":
    "MAXIMIZE",
    "maxTrials":
    5,
    "maxParallelTrials":
    1,
    "params": [{
        "parameterName": "hidden1",
        "type": "INTEGER",
        "minValue": 40,
        "maxValue": 400,
        "scalingType": "LINEAR"
    }]
}

study = client.create_study(name, study_configuration)
print(study)
print(client.list_studies())

trials = client.get_suggestions(study.id, 3)
print(trials)
print(client.list_trials(study.id))

Ejemplo n.º 3

def list_trials(args):
  client = AdvisorClient()
  print_trials(client.list_trials(args.study_id))

Ejemplo n.º 4

Archivo: command.py Proyecto: gridl/advisor

def list_trials(args):
  client = AdvisorClient()
  print_trials_as_table(client.list_trials(args.study_name))

Ejemplo n.º 5

Archivo: command.py Proyecto: divfor/advisor

def list_trials(args):
  client = AdvisorClient()
  print_trials(client.list_trials(args.study_id))

Ejemplo n.º 6

Archivo: example.py Proyecto: divfor/advisor

from advisor_client.model import TrialMetric
from advisor_client.client import AdvisorClient

client = AdvisorClient()

# Create Study
name = "Study"
study_configuration = {
    "goal":
    "MAXIMIZE",
    "maxTrials":
    5,
    "maxParallelTrials":
    1,
    "params": [{
        "parameterName": "hidden1",
        "type": "INTEGER",
        "minValue": 40,
        "maxValue": 400,
        "scallingType": "LINEAR"
    }]
}

study = client.create_study(name, study_configuration)
print(study)
print(client.list_studies())

trials = client.get_suggestions(study.id, 3)
print(trials)
print(client.list_trials(study.id))