Python Evolution 예제들

예제 #1

파일: config.py 프로젝트: xiaoliangabc/MOTSFusion

import netdef_slim as nd
import os
schedule = nd.FixedStepSchedule('S_custom',
                                max_iter=200000,
                                steps=[50000, 90000, 150000],
                                base_lr=1e-05)
nd.evo_manager.set_training_dir(
    os.path.join(os.path.dirname(__file__), 'training'))
nd.add_evo(nd.Evolution('kitti.train', [], schedule))

예제 #2

파일: config.py 프로젝트: xiaoliangabc/MOTSFusion

import netdef_slim as nd
import os

nd.evo_manager.set_training_dir(os.path.join(os.path.dirname(__file__), 'training'))

nd.add_evo(nd.Evolution('SDMixture_no_hom', [], 'S_refinement'))

예제 #3

import netdef_slim as nd
import os
import json
from collections import namedtuple
from model_genotype import model_func
from netdef_slim.schedules.named_schedule import NamedSchedule

nd.evo_manager.set_training_dir(
    os.path.join(os.path.dirname(__file__), 'training'))

# add evolution
max_steps = 150000
evo = nd.Evolution('FT3D', [], NamedSchedule('genotype', max_steps))
nd.add_evo(evo)

nd.config['model_fn'] = model_func
nd.config['num_gpus'] = 1
nd.config['test_batch_size'] = 1
nd.config['no_bn'] = True

Genotype = namedtuple('Genotype', 'normal reduce upsample')

genotype = Genotype(normal=[('skip_connect', 0), ('sep_conv_5x5', 1),
                            ('sep_conv_3x3', 2), ('skip_connect', 0),
                            ('dil_conv_3x3', 2), ('dil_conv_3x3', 0)],
                    reduce=[('sep_conv_5x5', 1), ('sep_conv_3x3', 0),
                            ('sep_conv_5x5', 2), ('skip_connect', 0),
                            ('skip_connect', 1), ('sep_conv_5x5', 3)],
                    upsample=[('sep_conv_3x3', 3), ('dil_conv_3x3', 2),
                              ('sep_conv_3x3', 1), ('skip_connect', 0),
                              ('sep_conv_3x3', 3), ('sep_conv_3x3', 4),

예제 #4

파일: config.py 프로젝트: xiaoliangabc/MOTSFusion

import netdef_slim as nd
import os

nd.evo_manager.set_training_dir(
    os.path.join(os.path.dirname(__file__), 'training'))
nd.add_evo(
    nd.Evolution('flyingThings3D.train', ['flyingThings3D.test'], 'S_short'))

예제 #5

파일: config.py 프로젝트: zhouyingji/netdef_models

import netdef_slim as nd
import os

nd.evo_manager.set_training_dir(os.path.join(os.path.dirname(__file__), 'training'))
schedule = nd.FixedStepSchedule('S_custom', max_iter=200000, steps=[50000, 150000], base_lr=1e-05)
nd.add_evo(nd.Evolution('kitti_sceneflow_ft', [], schedule))

예제 #6

import netdef_slim as nd
import os

nd.evo_manager.set_training_dir(
    os.path.join(os.path.dirname(__file__), 'training'))

schedule = nd.FixedStepSchedule('S_custom',
                                max_iter=250000,
                                steps=[5000, 10000, 20000],
                                base_lr=1e-05)
nd.add_evo(nd.Evolution('sintel_mixture', [], schedule))

예제 #7

import netdef_slim as nd
import os

nd.evo_manager.set_training_dir(
    os.path.join(os.path.dirname(__file__), 'training'))
nd.add_evo(
    nd.Evolution('flyingThings3D.train', ['flyingThings3D.test'],
                 'S_fine_half'))

예제 #8

파일: config.py 프로젝트: zhouyingji/netdef_models

import netdef_slim as nd
import os

nd.evo_manager.set_training_dir(
    os.path.join(os.path.dirname(__file__), 'training'))
nd.add_evo(nd.Evolution('kitti.all.train', ['kitti.all.val'], 'S_short'))