Merge pull request #933 from wannature/singa_v5
update the lime interpretation module
diff --git a/examples/singa_easy/singa_easy/modules/explanations/lime/lime.py b/examples/singa_easy/singa_easy/modules/explanations/lime/lime.py
index 578af49..1405260 100644
--- a/examples/singa_easy/singa_easy/modules/explanations/lime/lime.py
+++ b/examples/singa_easy/singa_easy/modules/explanations/lime/lime.py
@@ -1,28 +1,6 @@
-
-#
-# Licensed to the Apache Software Foundation (ASF) under one
-# or more contributor license agreements. See the NOTICE file
-# distributed with this work for additional information
-# regarding copyright ownership. The ASF licenses this file
-# to you under the Apache License, Version 2.0 (the
-# "License"); you may not use this file except in compliance
-# with the License. You may obtain a copy of the License at
-#
-# http://www.apache.org/licenses/LICENSE-2.0
-#
-# Unless required by applicable law or agreed to in writing,
-# software distributed under the License is distributed on an
-# "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY
-# KIND, either express or implied. See the License for the
-# specific language governing permissions and limitations
-# under the License.
-#
-
from lime import lime_image
from skimage.segmentation import mark_boundaries
-import torch
-import torch.nn.functional as F
from singa_auto.model import utils
@@ -58,13 +36,8 @@
self._model.eval()
- # images are size of (B, W, H, C)
- with torch.no_grad():
- images = torch.FloatTensor(images).permute(0, 3, 1, 2).to(self.device)
-
images = images.to(self.device)
logits = self._model(images).to(self.device)
- probs = F.softmax(logits, dim=1)
return probs.detach().cpu().numpy()
@@ -81,4 +54,4 @@
hide_rest=False)
# (M, N, 3) array of float
img_boundry = mark_boundaries(temp / 255.0, mask)
- return img_boundry * 255
\ No newline at end of file
+ return img_boundry * 255
