Update NATS-Bench (sss version 1.0)

lib/nats_bench/api_utils.py

@@ -10,10 +10,15 @@
 # History:
 # [2020.07.31] The first version, where most content reused nas_201_api/api_utils.py
 #
-import os, abc, copy, random, torch, numpy as np
-from pathlib import Path
+import abc, copy, random, numpy as np
+import importlib, warnings
 from typing import List, Text, Union, Dict, Optional
 from collections import OrderedDict, defaultdict
+USE_TORCH = importlib.find_loader('torch') is not None
+if USE_TORCH:
+  import torch
+else:
+  warnings.warn('Can not find PyTorch, and thus some features maybe invalid.')
 
 
 def remap_dataset_set_names(dataset, metric_on_set, verbose=False):
@@ -545,6 +550,8 @@ class ArchResults(object):
   def create_from_state_dict(state_dict_or_file):
     x = ArchResults(-1, -1)
     if isinstance(state_dict_or_file, str): # a file path
+      if not USE_TORCH:
+        raise ValueError('Since torch is not imported, this logic can not be used.')
       state_dict = torch.load(state_dict_or_file, map_location='cpu')
     elif isinstance(state_dict_or_file, dict):
       state_dict = state_dict_or_file

lib/utils/__init__.py

@@ -3,3 +3,4 @@ from .gpu_manager      import GPUManager
 from .flop_benchmark   import get_model_infos, count_parameters_in_MB
 from .affine_utils     import normalize_points, denormalize_points
 from .affine_utils     import identity2affine, solve2theta, affine2image
+from .hash_utils       import get_md5_file

lib/utils/hash_utils.py

@@ -0,0 +1,16 @@
+import os, hashlib
+
+
+def get_md5_file(file_path, post_truncated=5):
+  md5_hash = hashlib.md5()
+  if os.path.exists(file_path):
+    xfile = open(file_path, "rb")
+    content = xfile.read()
+    md5_hash.update(content)
+    digest = md5_hash.hexdigest()
+  else:
+    raise ValueError('[get_md5_file] {:} does not exist'.format(file_path))
+  if post_truncated is None:
+    return digest
+  else:
+    return digest[-post_truncated:]