update CVPR-2019-GDAS re-train NASNet-search-space searched models
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		| @@ -155,7 +155,7 @@ class NASNetSearchCell(nn.Module): | ||||
|     self.edges     = nn.ModuleDict() | ||||
|     for i in range(self._steps): | ||||
|       for j in range(2+i): | ||||
|         node_str = '{:}<-{:}'.format(i, j) | ||||
|         node_str = '{:}<-{:}'.format(i, j)  # indicate the edge from node-(j) to node-(i+2) | ||||
|         stride = 2 if reduction and j < 2 else 1 | ||||
|         op = MixedOp(space, C, stride, affine, track_running_stats) | ||||
|         self.edges[ node_str ] = op | ||||
|   | ||||
| @@ -5,8 +5,7 @@ import torch | ||||
| import torch.nn as nn | ||||
| from copy import deepcopy | ||||
| from typing import List, Text, Dict | ||||
| from .search_cells     import NASNetSearchCell as SearchCell | ||||
| from .genotypes        import Structure | ||||
| from .search_cells import NASNetSearchCell as SearchCell | ||||
|  | ||||
|  | ||||
| # The macro structure is based on NASNet | ||||
|   | ||||
| @@ -4,8 +4,7 @@ | ||||
| import torch | ||||
| import torch.nn as nn | ||||
| from copy import deepcopy | ||||
| from .search_cells     import NASNetSearchCell as SearchCell | ||||
| from .genotypes        import Structure | ||||
| from .search_cells import NASNetSearchCell as SearchCell | ||||
|  | ||||
|  | ||||
| # The macro structure is based on NASNet | ||||
|   | ||||
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