Python choice示例

示例#1

文件： lfw_model_exploration.py 项目： yamins81/thor_model_exploration

import pymongo as pm
from hyperopt.genson_helpers import (null, false, true, choice, uniform,
                                     gaussian, lognormal, qlognormal, ref)
from thoreano.slm import (TheanoExtractedFeatures, use_memmap)
from thoreano.classifier import (evaluate_classifier_normalize,
                                 train_asgd_classifier_normalize)

import comparisons as comp_module

DEFAULT_COMPARISONS = ['mult', 'sqrtabsdiff']

############
######params
lnorm = {
    'kwargs': {
        'inker_shape': choice([(3, 3), (5, 5), (7, 7), (9, 9)]),
        'outker_shape': ref('this', 'inker_shape'),
        'remove_mean': choice([0, 1]),
        'stretch': uniform(0, 10),
        'threshold': choice([null, uniform(0, 10)])
    }
}

lpool = {
    'kwargs': {
        'ker_shape': choice([(3, 3), (5, 5), (7, 7), (9, 9)]),
        'order': choice([1, 2, 10])
    }
}

rescale = {'kwargs': {'stride': 2}}

示例#2

文件： lfw_model_exploration.py 项目： yamins81/thor_model_exploration

                         lognormal,
                         qlognormal,
                         ref)
from thoreano.slm import (TheanoExtractedFeatures,
                          use_memmap)
from thoreano.classifier import (evaluate_classifier_normalize,
                                 train_asgd_classifier_normalize)


import comparisons as comp_module

DEFAULT_COMPARISONS = ['mult', 'sqrtabsdiff']

############
######params
lnorm = {'kwargs':{'inker_shape' : choice([(3,3),(5,5),(7,7),(9,9)]),
         'outker_shape' : ref('this','inker_shape'),
         'remove_mean' : choice([0,1]),
         'stretch' : uniform(0,10),
         'threshold' : choice([null, uniform(0,10)])
         }}

lpool = {'kwargs': {'ker_shape' : choice([(3,3),(5,5),(7,7),(9,9)]),
          'order' : choice([1, 2, 10])
         }}

rescale = {'kwargs': {'stride' : 2}}

activ =  {'kwargs': {'min_out' : choice([null, 0]),
                     'max_out' : choice([1, null])}}

示例#3

文件： model_exploration_params.py 项目： yamins81/thor_model_exploration

import copy
import itertools
from hyperopt.genson_helpers import null, false, true, choice, uniform, gaussian, lognormal, qlognormal, ref


lnorm = {
    "kwargs": {
        "inker_shape": choice([(3, 3), (5, 5), (7, 7), (9, 9)]),
        "outker_shape": ref("this", "inker_shape"),
        "remove_mean": choice([0, 1]),
        "stretch": uniform(0, 10),
        "threshold": choice([null, uniform(0, 10)]),
    }
}

lpool = {"kwargs": {"ker_shape": choice([(3, 3), (5, 5), (7, 7), (9, 9)]), "order": choice([1, 2, 10])}}

rescale = {"kwargs": {"stride": 2}}

activ = {"kwargs": {"min_out": choice([null, 0]), "max_out": choice([1, null])}}

filter1 = dict(
    initialize=dict(
        filter_shape=choice([(3, 3), (5, 5), (7, 7), (9, 9)]),
        n_filters=choice([16, 32, 64]),
        generate=("random:uniform", {"rseed": choice(range(5))}),
    ),
    kwargs={},
)

filter2 = copy.deepcopy(filter1)

示例#4

文件： model_exploration_params.py 项目： yamins81/thor_model_exploration

import copy
import itertools
from hyperopt.genson_helpers import (null, false, true, choice, uniform,
                                     gaussian, lognormal, qlognormal, ref)

lnorm = {
    'kwargs': {
        'inker_shape': choice([(3, 3), (5, 5), (7, 7), (9, 9)]),
        'outker_shape': ref('this', 'inker_shape'),
        'remove_mean': choice([0, 1]),
        'stretch': uniform(0, 10),
        'threshold': choice([null, uniform(0, 10)])
    }
}

lpool = {
    'kwargs': {
        'ker_shape': choice([(3, 3), (5, 5), (7, 7), (9, 9)]),
        'order': choice([1, 2, 10])
    }
}

rescale = {'kwargs': {'stride': 2}}

activ = {
    'kwargs': {
        'min_out': choice([null, 0]),
        'max_out': choice([1, null])
    }
}