Embedding layer for sequences: feed-forward layer that expects fixed-length number (inputLength) of integers/indices
per example as input, ranged from 0 to numClasses - 1. This input thus has shape [numExamples, inputLength] or shape
[numExamples, 1, inputLength]. The output of this layer is 3D (sequence/time series), namely of shape
[numExamples, nOut, inputLength].
Note: can only be used as the first layer for a network Note 2: For a given example index i, the output is activationFunction(weights.getRow(i) + bias), hence the
weight rows can be considered a vector/embedding of each index. Note also that embedding layer has an activation
function (set to IDENTITY to disable) and optional bias (which is disabled by default)
For the given type of input to this layer, what preprocessor (if any) is required?
Returns null if no preprocessor is required, otherwise returns an appropriate InputPreProcessor for this layer, such as a CnnToFeedForwardPreProcessor