batch_dot is used to compute dot product of x and y when x and y
are data in batch, i.e. in a shape of (batch_size). batch_dot results in
a tensor or variable with less dimensions than the input. If the number of
dimensions is reduced to 1, we use expand_dims to make sure that ndim is
at least 2.
k_batch_dot(x, y, axes)Keras tensor or variable with 2 more more axes.
Keras tensor or variable with 2 or more axes
List of (or single) integer with target dimensions (axis indexes
are 1-based). The lengths of axes[[1]] and axes[[2]] should be the
same.
A tensor with shape equal to the concatenation of x's shape (less
the dimension that was summed over) and y's shape (less the batch
dimension and the dimension that was summed over). If the final rank is 1,
we reshape it to (batch_size, 1).
This function is part of a set of Keras backend functions that enable lower level access to the core operations of the backend tensor engine (e.g. TensorFlow, CNTK, Theano, etc.).
You can see a list of all available backend functions here: https://keras.rstudio.com/articles/backend.html#backend-functions.