def as_array(array_data): # convert data to numpy.ndarray
from hypernets.utils import logging
logger = logging.get_logger(__name__)
def _is_numpy_ndarray(obj):
return isinstance(obj, np.ndarray)
def _is_pylist(obj):
return isinstance(obj, list)
def _is_pd_series(obj):
return isinstance(obj, pd.Series)
def _is_cudf_series(obj):
try:
import cudf
return isinstance(obj, cudf.Series) #
except Exception:
return False
def _is_cupy_array(obj):
try:
import cupy
return isinstance(obj, cupy.ndarray)
except Exception:
return False
if _is_pd_series(array_data):
return array_data.values
elif _is_numpy_ndarray(array_data):
return array_data
elif _is_pylist(array_data):
return np.array(array_data)
elif _is_cudf_series(array_data):
return array_data.to_numpy()
elif _is_cupy_array(array_data):
return np.array(array_data.tolist())
else:
logger.warning(f"unseen data type {type(array_data)} convert to numpy ndarray")
return array_data
import math
import queue
import time
from concurrent.futures import ThreadPoolExecutor, as_completed
import dask
from dask.distributed import Client, default_client
from hypernets.core.callbacks import EarlyStoppingError
from hypernets.core.dispatcher import Dispatcher
from hypernets.core.trial import Trial
from hypernets.utils import logging, fs
from hypernets.utils.common import config, Counter
logger = logging.get_logger(__name__)
class DaskTrialItem(Trial):
def __init__(self,
space_sample,
trial_no,
reward=math.nan,
elapsed=math.nan,
model_file=None):
super(DaskTrialItem, self).__init__(space_sample, trial_no, reward,
elapsed, model_file)
self.space_id = space_sample.space_id
self.queue_at = time.time()
def get_logger():
from hypernets.utils import logging
logger = logging.get_logger(__name__)
return logger
import os
import subprocess
import tempfile
from multiprocessing import cpu_count
from pathlib import Path
from typing import List
from paramiko import SFTPClient
from hypernets.hyperctl import consts, get_context
from hypernets.hyperctl.batch import ShellJob
from hypernets.hyperctl.dao import change_job_status
from hypernets.utils import logging as hyn_logging
from hypernets.utils import ssh_utils
logger = hyn_logging.get_logger(__name__)
class NoResourceException(Exception):
pass
class ShellExecutor:
def __init__(self, job: ShellJob):
self.job = job
def run(self):
pass
def post(self):
pass
# -*- coding:utf-8 -*-
__author__ = 'yangjian'
"""
"""
from hypernets.utils.logging import get_logger
from ._base import BaseDiscriminator, get_percentile_score
import numpy as np
logger = get_logger(__name__)
class PercentileDiscriminator(BaseDiscriminator):
def __init__(self,
percentile,
min_trials=5,
min_steps=5,
stride=1,
history=None,
optimize_direction='min'):
assert 0.0 <= percentile <= 100.0, f'Percentile which must be between 0 and 100 inclusive. got {percentile}'
BaseDiscriminator.__init__(self, min_trials, min_steps, stride,
history, optimize_direction)
self.percentile = percentile
def _is_promising(self,
iteration_trajectory,
group_id,
end_iteration=None):
n_step = len(iteration_trajectory) - 1
