Update README.md

Verify that the code works well in pytorch 1.7.0

Author: AlexHex7

README.md

@@ -12,7 +12,7 @@
 
 ## Environment
 - python 3.7.7
-- pytorch 1.4.0 (>=1.2.0, 1.6.0 works too)
+- pytorch 1.4.0 (>=1.2.0, 1.7.0 works too)
 - opencv 4.2.0.34 (others work too)
 
 ## Visualization
@@ -78,6 +78,8 @@ to **Non-Local_pytorch_0.3.1/**.
 
 10. The code also works well in **pytorch 1.6.0**. Add **demo_MNIST_AMP_train_with_single_gpu.py** with Automatic Mixed Precision Training (FP16), supported by **pytorch 1.6.0**. It can reduce GPU memory during training. What's more, if you use GPU 2080Ti (tensor cores), training speed can be increased. More details (such as how to train with multiple GPUs) can be found in [here](https://pytorch.org/docs/stable/notes/amp_examples.html#typical-mixed-precision-training)
 
+11. Verify that the code works well in **pytorch 1.7.0**.
+
 ## Todo
 - Experiments on Charades dataset.
 - Experiments on COCO dataset.
@@ -87,4 +89,4 @@ to **Non-Local_pytorch_0.3.1/**.
 1. [**Non-local ResNet-50 TSM**](https://github.com/MIT-HAN-LAB/temporal-shift-module) 
 ([**Paper**](https://arxiv.org/abs/1811.08383)) on Kinetics dataset. They report that their model achieves a good performance 
 of **75.6% on Kinetics**, which is even higher than Non-local ResNet-50 I3D 
-([**Here**](https://github.com/AlexHex7/Non-local_pytorch/issues/23)).
+([**Here**](https://github.com/AlexHex7/Non-local_pytorch/issues/23)).