Conversion of 2-D metric to 1-D vector

1

I have a 2-D matrix of activation values for every image. I want to made up 1-D activation vectors corresponding to each image. I am not sure how to do it. Any help regarding this would be great.

2

Is this topic related to distributed?
Anyway, could you give us more details about the activation value?

Describing it with a dimension would be helpful.

3

I updated the category. Thanks for indicating.

The activation values are the logits. The dimension is 8749 rows × 11 columns.

4

There are several ways to make the tensor flatten.
Among them, in this case,

  1. nn.Flatten would be the one you are looking for.
    (Flatten — PyTorch 1.12 documentation)
  2. tensor.view() is the popular option. activation_vector.view(batch_size, -1) makes the tensor flatten.

For any case, keep in mind that your tensor should have at least 2-D which indicates the size of batch in the first dimension.