Source code for nni.algorithms.hpo.batch_tuner

# Copyright (c) Microsoft Corporation.
# Licensed under the MIT license.

"""
batch_tuner.py including:
    class BatchTuner
"""

import logging

import nni
from nni.common.hpo_utils import validate_search_space
from nni.tuner import Tuner

TYPE = '_type'
CHOICE = 'choice'
VALUE = '_value'

LOGGER = logging.getLogger('batch_tuner_AutoML')

[docs]class BatchTuner(Tuner): """ Batch tuner is a special tuner that allows users to simply provide several hyperparameter sets, and it will evaluate each set. Batch tuner does **not** support standard search space. Search space of batch tuner looks like a single ``choice`` in standard search space, but it has different meaning. Consider following search space: .. code-block:: 'combine_params': { '_type': 'choice', '_value': [ {'x': 0, 'y': 1}, {'x': 1, 'y': 2}, {'x': 1, 'y': 3}, ] } Batch tuner will generate following 4 hyperparameter sets: 1. {'x': 0, 'y': 1} 2. {'x': 1, 'y': 2} 3. {'x': 1, 'y': 3} If this search space was used with grid search tuner, it would instead generate: 1. {'combine_params': {'x': 0, 'y': 1 }} 2. {'combine_params': {'x': 1, 'y': 2 }} 3. {'combine_params': {'x': 1, 'y': 3 }} Examples -------- .. code-block:: config.search_space = { 'combine_params': { '_type': 'choice', '_value': [ {'optimizer': 'Adam', 'learning_rate': 0.001}, {'optimizer': 'Adam', 'learning_rate': 0.0001}, {'optimizer': 'Adam', 'learning_rate': 0.00001}, {'optimizer': 'SGD', 'learning_rate': 0.01}, {'optimizer': 'SGD', 'learning_rate': 0.005}, ] } } config.tuner.name = 'Batch' """ def __init__(self): self._count = -1 self._values = [] def _is_valid(self, search_space): """ Check the search space is valid: only contains 'choice' type Parameters ---------- search_space : dict Returns ------- None or list If valid, return candidate values; else return None. """ if not len(search_space) == 1: raise RuntimeError('BatchTuner only supprt one combined-paramreters key.') for param in search_space: param_type = search_space[param][TYPE] if not param_type == CHOICE: raise RuntimeError('BatchTuner only supprt \ one combined-paramreters type is choice.') if isinstance(search_space[param][VALUE], list): return search_space[param][VALUE] raise RuntimeError('The combined-paramreters \ value in BatchTuner is not a list.') return None def update_search_space(self, search_space): validate_search_space(search_space, ['choice']) self._values = self._is_valid(search_space) def generate_parameters(self, parameter_id, **kwargs): self._count += 1 if self._count > len(self._values) - 1: raise nni.NoMoreTrialError('no more parameters now.') return self._values[self._count] def receive_trial_result(self, parameter_id, parameters, value, **kwargs): pass def import_data(self, data): if not self._values: LOGGER.info("Search space has not been initialized, skip this data import") return self._values = self._values[(self._count+1):] self._count = -1 _completed_num = 0 for trial_info in data: LOGGER .info("Importing data, current processing \ progress %s / %s", _completed_num, len(data)) # simply validate data format assert "parameter" in trial_info _params = trial_info["parameter"] assert "value" in trial_info _value = trial_info['value'] if not _value: LOGGER.info("Useless trial data, value is %s, skip this trial data.", _value) continue _completed_num += 1 if _params in self._values: self._values.remove(_params) LOGGER .info("Successfully import data to batch tuner, \ total data: %d, imported data: %d.", len(data), _completed_num)