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2019-02-01 01:27:38 +11:00
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from collections import namedtuple
Genotype = namedtuple('Genotype', 'normal normal_concat reduce reduce_concat')
PRIMITIVES = [
'none',
'max_pool_3x3',
'avg_pool_3x3',
'skip_connect',
'sep_conv_3x3',
'sep_conv_5x5',
'dil_conv_3x3',
'dil_conv_5x5'
]
NASNet = Genotype(
normal = [
('sep_conv_5x5', 1, 1.0),
('sep_conv_3x3', 0, 1.0),
('sep_conv_5x5', 0, 1.0),
('sep_conv_3x3', 0, 1.0),
('avg_pool_3x3', 1, 1.0),
('skip_connect', 0, 1.0),
('avg_pool_3x3', 0, 1.0),
('avg_pool_3x3', 0, 1.0),
('sep_conv_3x3', 1, 1.0),
('skip_connect', 1, 1.0),
],
normal_concat = [2, 3, 4, 5, 6],
reduce = [
('sep_conv_5x5', 1, 1.0),
('sep_conv_7x7', 0, 1.0),
('max_pool_3x3', 1, 1.0),
('sep_conv_7x7', 0, 1.0),
('avg_pool_3x3', 1, 1.0),
('sep_conv_5x5', 0, 1.0),
('skip_connect', 3, 1.0),
('avg_pool_3x3', 2, 1.0),
('sep_conv_3x3', 2, 1.0),
('max_pool_3x3', 1, 1.0),
],
reduce_concat = [4, 5, 6],
)
AmoebaNet = Genotype(
normal = [
('avg_pool_3x3', 0, 1.0),
('max_pool_3x3', 1, 1.0),
('sep_conv_3x3', 0, 1.0),
('sep_conv_5x5', 2, 1.0),
('sep_conv_3x3', 0, 1.0),
('avg_pool_3x3', 3, 1.0),
('sep_conv_3x3', 1, 1.0),
('skip_connect', 1, 1.0),
('skip_connect', 0, 1.0),
('avg_pool_3x3', 1, 1.0),
],
normal_concat = [4, 5, 6],
reduce = [
('avg_pool_3x3', 0, 1.0),
('sep_conv_3x3', 1, 1.0),
('max_pool_3x3', 0, 1.0),
('sep_conv_7x7', 2, 1.0),
('sep_conv_7x7', 0, 1.0),
('avg_pool_3x3', 1, 1.0),
('max_pool_3x3', 0, 1.0),
('max_pool_3x3', 1, 1.0),
('conv_7x1_1x7', 0, 1.0),
('sep_conv_3x3', 5, 1.0),
],
reduce_concat = [3, 4, 6]
)
DARTS_V1 = Genotype(
normal=[
('sep_conv_3x3', 1, 1.0),
('sep_conv_3x3', 0, 1.0),
('skip_connect', 0, 1.0),
('sep_conv_3x3', 1, 1.0),
('skip_connect', 0, 1.0),
('sep_conv_3x3', 1, 1.0),
('sep_conv_3x3', 0, 1.0),
('skip_connect', 2, 1.0)],
normal_concat=[2, 3, 4, 5],
reduce=[
('max_pool_3x3', 0, 1.0),
('max_pool_3x3', 1, 1.0),
('skip_connect', 2, 1.0),
('max_pool_3x3', 0, 1.0),
('max_pool_3x3', 0, 1.0),
('skip_connect', 2, 1.0),
('skip_connect', 2, 1.0),
('avg_pool_3x3', 0, 1.0)],
reduce_concat=[2, 3, 4, 5]
)
DARTS_V2 = Genotype(
normal=[
('sep_conv_3x3', 0, 1.0),
('sep_conv_3x3', 1, 1.0),
('sep_conv_3x3', 0, 1.0),
('sep_conv_3x3', 1, 1.0),
('sep_conv_3x3', 1, 1.0),
('skip_connect', 0, 1.0),
('skip_connect', 0, 1.0),
('dil_conv_3x3', 2, 1.0)],
normal_concat=[2, 3, 4, 5],
reduce=[
('max_pool_3x3', 0, 1.0),
('max_pool_3x3', 1, 1.0),
('skip_connect', 2, 1.0),
('max_pool_3x3', 1, 1.0),
('max_pool_3x3', 0, 1.0),
('skip_connect', 2, 1.0),
('skip_connect', 2, 1.0),
('max_pool_3x3', 1, 1.0)],
reduce_concat=[2, 3, 4, 5]
)
PNASNet = Genotype(
normal = [
('sep_conv_5x5', 0, 1.0),
('max_pool_3x3', 0, 1.0),
('sep_conv_7x7', 1, 1.0),
('max_pool_3x3', 1, 1.0),
('sep_conv_5x5', 1, 1.0),
('sep_conv_3x3', 1, 1.0),
('sep_conv_3x3', 4, 1.0),
('max_pool_3x3', 1, 1.0),
('sep_conv_3x3', 0, 1.0),
('skip_connect', 1, 1.0),
],
normal_concat = [2, 3, 4, 5, 6],
reduce = [
('sep_conv_5x5', 0, 1.0),
('max_pool_3x3', 0, 1.0),
('sep_conv_7x7', 1, 1.0),
('max_pool_3x3', 1, 1.0),
('sep_conv_5x5', 1, 1.0),
('sep_conv_3x3', 1, 1.0),
('sep_conv_3x3', 4, 1.0),
('max_pool_3x3', 1, 1.0),
('sep_conv_3x3', 0, 1.0),
('skip_connect', 1, 1.0),
],
reduce_concat = [2, 3, 4, 5, 6],
)
# https://arxiv.org/pdf/1802.03268.pdf
ENASNet = Genotype(
normal = [
('sep_conv_3x3', 1, 1.0),
('skip_connect', 1, 1.0),
('sep_conv_5x5', 1, 1.0),
('skip_connect', 0, 1.0),
('avg_pool_3x3', 0, 1.0),
('sep_conv_3x3', 1, 1.0),
('sep_conv_3x3', 0, 1.0),
('avg_pool_3x3', 1, 1.0),
('sep_conv_5x5', 1, 1.0),
('avg_pool_3x3', 0, 1.0),
],
normal_concat = [2, 3, 4, 5, 6],
reduce = [
('sep_conv_5x5', 0, 1.0),
('sep_conv_3x3', 1, 1.0), # 2
('sep_conv_3x3', 1, 1.0),
('avg_pool_3x3', 1, 1.0), # 3
('sep_conv_3x3', 1, 1.0),
('avg_pool_3x3', 1, 1.0), # 4
('avg_pool_3x3', 1, 1.0),
('sep_conv_5x5', 4, 1.0), # 5
('sep_conv_3x3', 5, 1.0),
('sep_conv_5x5', 0, 1.0),
],
reduce_concat = [2, 3, 4, 5, 6],
)
DARTS = DARTS_V2
# Search by normal and reduce
DMS_V1 = Genotype(
normal=[('skip_connect', 0, 0.13017432391643524), ('skip_connect', 1, 0.12947972118854523), ('skip_connect', 0, 0.13062666356563568), ('sep_conv_5x5', 2, 0.12980839610099792), ('sep_conv_3x3', 3, 0.12923765182495117), ('skip_connect', 0, 0.12901571393013), ('sep_conv_5x5', 4, 0.12938997149467468), ('sep_conv_3x3', 3, 0.1289220005273819)],
normal_concat=range(2, 6),
reduce=[('sep_conv_5x5', 0, 0.12862831354141235), ('sep_conv_3x3', 1, 0.12783904373645782), ('sep_conv_5x5', 2, 0.12725995481014252), ('sep_conv_5x5', 1, 0.12705285847187042), ('dil_conv_5x5', 2, 0.12797553837299347), ('sep_conv_3x3', 1, 0.12737272679805756), ('sep_conv_5x5', 0, 0.12833961844444275), ('sep_conv_5x5', 1, 0.12758426368236542)],
reduce_concat=range(2, 6)
)
# Search by normal and fixing reduction
DMS_F1 = Genotype(
normal=[('skip_connect', 0, 0.16), ('skip_connect', 1, 0.13), ('skip_connect', 0, 0.17), ('sep_conv_3x3', 2, 0.15), ('skip_connect', 0, 0.17), ('sep_conv_3x3', 2, 0.15), ('skip_connect', 0, 0.16), ('sep_conv_3x3', 2, 0.15)],
normal_concat=[2, 3, 4, 5],
reduce=None,
reduce_concat=[2, 3, 4, 5],
)
# Combine DMS_V1 and DMS_F1
GDAS_CC = Genotype(
normal=[('skip_connect', 0, 0.13017432391643524), ('skip_connect', 1, 0.12947972118854523), ('skip_connect', 0, 0.13062666356563568), ('sep_conv_5x5', 2, 0.12980839610099792), ('sep_conv_3x3', 3, 0.12923765182495117), ('skip_connect', 0, 0.12901571393013), ('sep_conv_5x5', 4, 0.12938997149467468), ('sep_conv_3x3', 3, 0.1289220005273819)],
normal_concat=range(2, 6),
reduce=None,
reduce_concat=range(2, 6)
)