Add visualize codes for Q

lib/procedures/basic_main.py

@@ -2,9 +2,11 @@
 # Copyright (c) Xuanyi Dong [GitHub D-X-Y], 2019 #
 ##################################################
 import os, sys, time, torch
+
+# modules in AutoDL
 from log_utils import AverageMeter
 from log_utils import time_string
-from utils import obtain_accuracy
+from .eval_funcs import obtain_accuracy
 
 
 def basic_train(

lib/procedures/eval_funcs.py

@@ -0,0 +1,14 @@
+def obtain_accuracy(output, target, topk=(1,)):
+    """Computes the precision@k for the specified values of k"""
+    maxk = max(topk)
+    batch_size = target.size(0)
+
+    _, pred = output.topk(maxk, 1, True, True)
+    pred = pred.t()
+    correct = pred.eq(target.view(1, -1).expand_as(pred))
+
+    res = []
+    for k in topk:
+        correct_k = correct[:k].view(-1).float().sum(0, keepdim=True)
+        res.append(correct_k.mul_(100.0 / batch_size))
+    return res

lib/procedures/funcs_nasbench.py

@@ -3,12 +3,14 @@
 #####################################################
 import os, time, copy, torch, pathlib
 
+# modules in AutoDL
 import datasets
 from config_utils import load_config
 from procedures import prepare_seed, get_optim_scheduler
-from utils import get_model_infos, obtain_accuracy
 from log_utils import AverageMeter, time_string, convert_secs2time
 from models import get_cell_based_tiny_net
+from utils import get_model_infos
+from .eval_funcs import obtain_accuracy
 
 
 __all__ = ["evaluate_for_seed", "pure_evaluate", "get_nas_bench_loaders"]

lib/procedures/search_main.py

@@ -3,9 +3,10 @@
 ##################################################
 import os, sys, time, torch
 from log_utils import AverageMeter, time_string
-from utils import obtain_accuracy
 from models import change_key
 
+from .eval_funcs import obtain_accuracy
+
 
 def get_flop_loss(expected_flop, flop_cur, flop_need, flop_tolerant):
     expected_flop = torch.mean(expected_flop)

lib/procedures/search_main_v2.py

@@ -2,9 +2,11 @@
 # Copyright (c) Xuanyi Dong [GitHub D-X-Y], 2019 #
 ##################################################
 import os, sys, time, torch
+
+# modules in AutoDL
 from log_utils import AverageMeter, time_string
-from utils import obtain_accuracy
 from models import change_key
+from .eval_funcs import obtain_accuracy
 
 
 def get_flop_loss(expected_flop, flop_cur, flop_need, flop_tolerant):

lib/procedures/simple_KD_main.py

@@ -4,9 +4,9 @@
 import os, sys, time, torch
 import torch.nn.functional as F
 
-# our modules
+# modules in AutoDL
 from log_utils import AverageMeter, time_string
-from utils import obtain_accuracy
+from .eval_funcs import obtain_accuracy
 
 
 def simple_KD_train(