|
|
@@ -29,18 +29,11 @@ import numpy as np
|
|
|
np.random.seed(5)
|
|
|
perm = np.random.permutation(len(test_dataset.file_list))
|
|
|
|
|
|
-for i in range(len(test_dataset.file_list)):
|
|
|
-
|
|
|
- # 可解释性可视化
|
|
|
- pdx.interpret.normlime(
|
|
|
- test_dataset.file_list[perm[i]][0],
|
|
|
- model,
|
|
|
- test_dataset,
|
|
|
- save_dir='./',
|
|
|
- normlime_weights_file='{}_{}.npy'.format(
|
|
|
- dataset.split('/')[-1], model.model_name))
|
|
|
-
|
|
|
- if i == 1:
|
|
|
- # first iter will have an initialization process, followed by the interpretation.
|
|
|
- # second iter will directly load the initialization process, followed by the interpretation.
|
|
|
- break
|
|
|
+# 可解释性可视化
|
|
|
+pdx.interpret.normlime(
|
|
|
+ test_dataset.file_list[0][0],
|
|
|
+ model,
|
|
|
+ test_dataset,
|
|
|
+ save_dir='./',
|
|
|
+ normlime_weights_file='{}_{}.npy'.format(
|
|
|
+ dataset.split('/')[-1], model.model_name))
|