python tsne.transform does not exist?

I am trying to transform two datasets: x_train and x_test using tsne. I assume the way to do this is to fit tsne to x_train, and then transform x_test and x_train. But, I am not able to transform any of the datasets.

tsne = TSNE(random_state = 420, n_components=2, verbose=1, perplexity=5, n_iter=350).fit(x_train)

I assume that tsne has been fitted to x_train.

But, when I do this:

x_train_tse = tsne.transform(x_subset)

I get:

AttributeError: 'TSNE' object has no attribute 'transform'

Any help will be appreciated. (I know I could do fit_transform, but wouldn't I get the same error on x_test?)

Judging by the documentation of sklearn, TSNE simply does not have any transform method.

Also, TSNE is an unsupervised method for dimesionality reduction/visualization, so it does not really work with a TRAIN and TEST. You simply take all of your data and use fit_transform to have the transformation and plot it.

EDIT - It is actually not possible to learn a transformation and reuse it on different data (i.e. Train and Test), as T-sne does not learn a mapping function on a lower dimensional space, but rather runs an iterative procedure on a subspace to find an equilibrium that minimizes a loss/distance ON SOME DATA.

Therefore if you want to preprocess and reduce dimensionality of both a Train and Test datasets, the way to go is PCA/SVD or Autoencoders. T-Sne will only help you for unsupervised tasks :)