![]() Inherits From: Layer. multiple outputs return out1, out2, out3 as this will again. ![]() nn.Squential will work exactly the way you know, as it will look like you gave it one input. Then I could train with a dataset with 10,000 pairs of sentences of the same author (desired output: 1), and 10,000 pairs of sentences with different authors (desired output: 0).īut I don't know if it would work by just stacking x1 and x2 as a 1000x2 matrix. A Layer characterized by iteratively given functions. Although I don’t know exactly how it works, it makes nn.Sequential feed the multiple inputs to a network if the type of inputs is a tuple. ![]() Of course I could build the layers like this: Input-size: None, 1000, 2 (x1, x2 stacked into a 1000x2 matrix) nn / a Go to file Go to file T Go to line L Copy path Copy This commit does not belong to any branch on this repository, and may belong to a. "The cat is sleeping" => x2 = Ġ.9 = high probability of same author, etc. Input #2: sentence2 by unknown author, idem "The sky is blue" => x1 = (zero-padded to have a length of 1000 items) Input #1: sentence1 by unknown author encoded, as list of words from a dictionary when I try to set the top level format property: timestampformatdd/mm/yyyy hh:nn:ss and. Is there a natural way, in terms of structure of the layers of a NN, in order to pass 2 inputs vectors to the NN? When I try to define the field as a timestamp it fails.
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