def __init__(self, genotype, i, C_pp, C_p, C, reduction_p, reduction, SSC):
super().__init__()
self.reduction = reduction
try:
self.n_nodes = len(genotype.normal)
except:
self.n_nodes = len(genotype["cell_0"])
if reduction_p:
self.preproc0 = ops.FactorizedReduce(C_pp, C)
else:
self.preproc0 = ops.StdConv(C_pp, C, 1, 1, 0)
self.preproc1 = ops.StdConv(C_p, C, 1, 1, 0)
# generate dag
if reduction:
try:
gene = genotype.reduce
self.concat = genotype.reduce_concat
except:
gene = genotype["cell_%d" % i]
self.concat = range(2, 2 + self.n_nodes)
else:
try:
gene = genotype.normal
self.concat = genotype.normal_concat
except:
gene = genotype["cell_%d" % i]
self.concat = range(2, 2 + self.n_nodes)
self.dag = gt.to_dag(C, gene, SSC, reduction)
def __init__(self, genotype, C_pp, C_p, C, reduction_p, reduction,
layer_id, n_layers):
super().__init__()
self.reduction = reduction
self.n_nodes = len(genotype.normal1)
self.layer_id = layer_id
if reduction_p:
self.preproc0 = ops.FactorizedReduce(C_pp, C)
else:
self.preproc0 = ops.StdConv(C_pp, C, 1, 1, 0)
self.preproc1 = ops.StdConv(C_p, C, 1, 1, 0)
if self.layer_id < n_layers // 3:
gene = genotype.normal1
self.concat = genotype.normal1_concat
elif self.layer_id == n_layers // 3:
gene = genotype.reduce1
self.concat = genotype.reduce1_concat
elif self.layer_id < 2 * n_layers // 3:
gene = genotype.normal2
self.concat = genotype.normal2_concat
elif self.layer_id == 2 * n_layers // 3:
gene = genotype.reduce2
self.concat = genotype.reduce2_concat
elif self.layer_id > 2 * n_layers // 3:
gene = genotype.normal3
self.concat = genotype.normal3_concat
self.dag = gt.to_dag(C, gene, reduction)
def __init__(self, genotype, C_pp, C_p, C, reduction):
super().__init__()
self.reduction = reduction
self.n_nodes = len(genotype.normal)
self.preproc0 = ops.StdConv(C_pp, C, 1, 1, 0)
self.preproc1 = ops.StdConv(C_p, C, 1, 1, 0)
if reduction:
gene = genotype.reduce
self.concat = genotype.reduce_concat
else:
gene = genotype.normal
self.concat = genotype.normal_concat
self.dag = gt.to_dag(C, gene, reduction)
def __init__(self, genotype, C_pp, C_p, C, reduction_p, reduction):
super().__init__()
self.reduction = reduction
self.n_nodes = len(genotype.normal)
if reduction_p:
self.preproc0 = ops.FactorizedReduce(C_pp, C)
else:
self.preproc0 = ops.Conv2dBlock(C_pp, C, 1, 1, 0)
self.preproc1 = ops.Conv2dBlock(C_p, C, 1, 1, 0)
# generate dag
if reduction:
gene = genotype.reduce
self.concat = genotype.reduce_concat
else:
gene = genotype.normal
self.concat = genotype.normal_concat
self.dag = gt.to_dag(C, gene, reduction)
def __init__(self, DAG, cells, start_p, end_p, C_pp, C_p, C):
super().__init__()
self.DAG = DAG
self.cells = cells
self.preproc0 = ops.StdConv(C_pp, C, 1, 1, 0, affine=True)
self.preproc1 = ops.StdConv(C_p, C, 1, 1, 0, affine=True)
if start_p == 0:
gene = DAG.DAG1
self.concat = DAG.DAG1_concat
elif start_p == len(DAG.DAG1) + 1:
gene = DAG.DAG2
self.concat = DAG.DAG2_concat
elif start_p == len(DAG.DAG1) + len(DAG.DAG2) + 2:
gene = DAG.DAG3
self.concat = DAG.DAG3_concat
self.bigDAG = gt.to_dag(C, gene, False)
for k in range(start_p, end_p + 1): # 4
self.bigDAG.append(cells[k])