def test_nasnet_fixwd():
# minimum
ss = searchspace.DARTS(width=16, num_cells=4)
_test_searchspace_on_dataset(ss)
# medium
ss = searchspace.NASNet(width=16, num_cells=12)
_test_searchspace_on_dataset(ss)
def test_nasnet_corner_case():
# The case is that output channel of reduce cell and normal cell are different
# CellPreprocessor needs to know whether its predecessors are normal cell / reduction cell
arch = {
"width": 32,
"depth": 8,
"normal/op_2_0": "max_pool_7x7",
"normal/op_2_1": "conv_1x1",
"normal/op_3_0": "sep_conv_5x5",
"normal/op_3_1": "max_pool_7x7",
"normal/op_4_0": "sep_conv_5x5",
"normal/op_4_1": "conv_1x1",
"normal/op_5_0": "max_pool_3x3",
"normal/op_5_1": "sep_conv_5x5",
"normal/op_6_0": "max_pool_7x7",
"normal/op_6_1": "sep_conv_5x5",
"normal/input_2_0": 0,
"normal/input_2_1": 0,
"normal/input_3_0": 0,
"normal/input_3_1": 1,
"normal/input_4_0": 1,
"normal/input_4_1": 2,
"normal/input_5_0": 0,
"normal/input_5_1": 1,
"normal/input_6_0": 0,
"normal/input_6_1": 2,
"reduce/op_2_0": "dil_conv_3x3",
"reduce/op_2_1": "max_pool_7x7",
"reduce/op_3_0": "dil_conv_3x3",
"reduce/op_3_1": "dil_conv_3x3",
"reduce/op_4_0": "conv_7x1_1x7",
"reduce/op_4_1": "conv_7x1_1x7",
"reduce/op_5_0": "max_pool_3x3",
"reduce/op_5_1": "conv_1x1",
"reduce/op_6_0": "sep_conv_7x7",
"reduce/op_6_1": "sep_conv_3x3",
"reduce/input_2_0": 1,
"reduce/input_2_1": 1,
"reduce/input_3_0": 0,
"reduce/input_3_1": 1,
"reduce/input_4_0": 2,
"reduce/input_4_1": 1,
"reduce/input_5_0": 0,
"reduce/input_5_1": 4,
"reduce/input_6_0": 3,
"reduce/input_6_1": 3,
}
_test_searchspace_on_dataset(searchspace.NASNet(), arch=arch)
def _hub_factory(alias):
if alias == 'nasbench101':
return ss.NasBench101()
if alias == 'nasbench201':
return ss.NasBench201()
if alias == 'mobilenetv3':
return ss.MobileNetV3Space()
if alias == 'mobilenetv3_small':
return ss.MobileNetV3Space(width_multipliers=(0.75, 1, 1.5),
expand_ratios=(4, 6))
if alias == 'proxylessnas':
return ss.ProxylessNAS()
if alias == 'shufflenet':
return ss.ShuffleNetSpace()
if alias == 'autoformer':
return ss.AutoformerSpace()
if '_smalldepth' in alias:
num_cells = (4, 8)
elif '_depth' in alias:
num_cells = (8, 12)
else:
num_cells = 8
if '_width' in alias:
width = (8, 16)
else:
width = 16
if '_imagenet' in alias:
dataset = 'imagenet'
else:
dataset = 'cifar'
if alias.startswith('nasnet'):
return ss.NASNet(width=width, num_cells=num_cells, dataset=dataset)
if alias.startswith('enas'):
return ss.ENAS(width=width, num_cells=num_cells, dataset=dataset)
if alias.startswith('amoeba'):
return ss.AmoebaNet(width=width, num_cells=num_cells, dataset=dataset)
if alias.startswith('pnas'):
return ss.PNAS(width=width, num_cells=num_cells, dataset=dataset)
if alias.startswith('darts'):
return ss.DARTS(width=width, num_cells=num_cells, dataset=dataset)
raise ValueError(f'Unrecognized space: {alias}')
def test_nasnet():
_test_searchspace_on_dataset(searchspace.NASNet())
_test_searchspace_on_dataset(searchspace.ENAS())
_test_searchspace_on_dataset(searchspace.AmoebaNet())
_test_searchspace_on_dataset(searchspace.PNAS())
_test_searchspace_on_dataset(searchspace.DARTS())