Fix typo in multiple instance learning (#1158)

Fixes #1153.

### Description

- Fix the typo in `ScaleIntensityRanged`


https://github.com/Project-MONAI/tutorials/blob/e5a1876ec41be44ac7185b07768177110c316f52/pathology/multiple_instance_learning/panda_mil_train_evaluate_pytorch_gpu.py#L296

- update performance figures with correct normalization

### Checks
<!--- Put an `x` in all the boxes that apply, and remove the not
applicable items -->
- [x] Avoid including large-size files in the PR.
- [ ] For security purposes, please check the contents and remove any
sensitive info such as user names and private key.
- [ ] Ensure (1) hyperlinks and markdown anchors are working (2) use
relative paths for tutorial repo files (3) put figure and graphs in the
`./figure` folder
- [ ] Notebook runs automatically `./runner.sh -t <path to .ipynb file>`

Signed-off-by: KumoLiu <yunl@nvidia.com>
Co-authored-by: pre-commit-ci[bot] <66853113+pre-commit-ci[bot]@users.noreply.github.com>

Author: KumoLiu

pathology/multiple_instance_learning/mil_train_loss.png

@@ -1,3 +1,14 @@
+# Copyright (c) MONAI Consortium
+# Licensed 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.
+
 import argparse
 import collections.abc
 import os
@@ -293,7 +304,7 @@ def main_worker(gpu, args):
             RandFlipd(keys=["image"], spatial_axis=0, prob=0.5),
             RandFlipd(keys=["image"], spatial_axis=1, prob=0.5),
             RandRotate90d(keys=["image"], prob=0.5),
-            ScaleIntensityRanged(keys=["image"], a_min=np.float32(255), a_max=np.float32(0)),
+            ScaleIntensityRanged(keys=["image"], a_min=np.float32(0), a_max=np.float32(255)),
             ToTensord(keys=["image", "label"]),
         ]
     )
@@ -310,7 +321,7 @@ def main_worker(gpu, args):
                 constant_values=255,
             ),
             SplitDimd(keys=["image"], dim=0, keepdim=False, list_output=True),
-            ScaleIntensityRanged(keys=["image"], a_min=np.float32(255), a_max=np.float32(0)),
+            ScaleIntensityRanged(keys=["image"], a_min=np.float32(0), a_max=np.float32(255)),
             ToTensord(keys=["image", "label"]),
         ]
     )