Does ggml_cont really work?

[BayRanger]

Hi, I try to perform softmax at the last dimension of a tensor. So I need to permute it first, and perform softmax at every n continguous elements. To permute the tensor, I think the expected code in ggml, should be like
auto _tensor = ggml_cont(ctx, ggml_permute(ctx,input, 1,2,0,3));
But I print the content of content of _tensor via float* data = ggml_get_data_f32(input); , the content of _tensor is all zero, later I use ggml_cont_inplace instead of ggml_cont, the data looks the same as in "input", which is not what I expected.

In pytorch, when using contiguous() after permutation, the raw data layout would be changed, that is what I expected. In ggml, while the raw data would not be changed using ggml_cont... So further explaination is wanted about the design intention of ggml_cont,... Furthermore, could someone show how to perform softmax. at a specific dimension of a tensor in ggml ? like in following code dense = np.exp(input) # Softmax. dense = dense / (np.sum(dense, axis=0)+.00001) # Should sum to 1.