PyTorch 2D Convolution
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- Опубликовано: 5 авг 2024
- In this video, we cover the input parameters for the PyTorch torch.nn.Conv2d module.
VIDEO CHAPTERS
0:00 Introduction
0:37 Example
2:46 torch.nn.Conv2d
3:28 Input/Output Channels
4:40 Kernel
5:15 Stride
6:17 Padding
8:01 Dilation
9:04 Groups
11:13 Bias
11:50 Output Shape
Thank you so much for this explanation! I have been looking everywhere, and most tutorials assume that the viewer has a grasp on these concepts. Finally found a good explanation!
Thank you very much for the positive feedback :)
Great video, made me understand the CNN-s in Python much better. Thank you!
Super clear explaination. Thanks !!!
perfect esplanation, straight foward and pure informative. tnx.
Thank you a lot! I finally understood from where all these filters comes!
great video, thank you so much. this video is worth more than 100 wiki pages
Thanks for the video! I believe for the group example, the input sample is (8x5x5) instead of (8x7x7)
Very good explanation, thank you. Please continue to make videos.
Thank you. One of the best and clearest explanations I have seen without wading through a ton of documentation.
thanks
Very good!
you goated for this one fam
Thank you!
Thank you this is the best explanation ❤❤❤
Thank you !
thx
My input always read (N, Hin, Win, Cin). How can i fix it to (N, Cin, Hin, Win)?
What if I change the kernel size and want to keep my input size? Would padding still be 1?
The best explanation. Thank you.