Scratch pytorch for Softmax regression

Enterprise 2022-04-05 02:46:25 views: null

1. The implementation of Softmax regression from scratch

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The input is a vector 784, which is the pixel length x width of the image.

784 = 28 * 28

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keepdim means keep dimension. Adding in the direction of 0 means removing the dimension of row, that is, the result is 1row; adding in the direction of 1 means removing the dimension of col, that is, the result is 1col.
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X.reshape((-1, W.shape[0])), the dimension is changed to bathSize * 784,bathSize = 256
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2. A concise implementation of Softmax regression in pytorch

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refer to

https://www.bilibili.com/video/BV1K64y1Q7wu

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Origin blog.csdn.net/zgpeace/article/details/123768541
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