Move to xautodl

xautodl/nas_infer_model/__init__.py

@@ -0,0 +1,31 @@
+#####################################################
+# Copyright (c) Xuanyi Dong [GitHub D-X-Y], 2019.01 #
+#####################################################
+# I write this package to make AutoDL-Projects to be compatible with the old GDAS projects.
+# Ideally, this package will be merged into lib/models/cell_infers in future.
+# Currently, this package is used to reproduce the results in GDAS (Searching for A Robust Neural Architecture in Four GPU Hours, CVPR 2019).
+##################################################
+
+import os, torch
+
+def obtain_nas_infer_model(config, extra_model_path=None):
+  
+  if config.arch == 'dxys':
+    from .DXYs import CifarNet, ImageNet, Networks
+    from .DXYs import build_genotype_from_dict
+    if config.genotype is None:
+      if extra_model_path is not None and not os.path.isfile(extra_model_path):
+        raise ValueError('When genotype in confiig is None, extra_model_path must be set as a path instead of {:}'.format(extra_model_path))
+      xdata = torch.load(extra_model_path)
+      current_epoch = xdata['epoch']
+      genotype_dict = xdata['genotypes'][current_epoch-1]
+      genotype = build_genotype_from_dict(genotype_dict)
+    else:
+      genotype = Networks[config.genotype]
+    if config.dataset == 'cifar':
+      return CifarNet(config.ichannel, config.layers, config.stem_multi, config.auxiliary, genotype, config.class_num)
+    elif config.dataset == 'imagenet':
+      return ImageNet(config.ichannel, config.layers, config.auxiliary, genotype, config.class_num)
+    else: raise ValueError('invalid dataset : {:}'.format(config.dataset))
+  else:
+    raise ValueError('invalid nas arch type : {:}'.format(config.arch))