Flatten layer is used in several examples in the book and it is clear that it is a necessary tool for tensor dimensions reduction. What Flatten does is intuitively clear. Nevertheless I believe that it is useful to have more precise knowledge what happens behind the screen. Would it be possible to explain the mechanism in detail in the book?

It converts input tensor to output vector [1, N],
e.g. in numpy, vector = tensor.reshape(-1) (see https://docs.scipy.org/doc/numpy/reference/generated/numpy.reshape.html)
Number of elements in output vector remains the same as in input tensor, so, it is not about reduction