28 lines
1.1 KiB
Mathematica
28 lines
1.1 KiB
Mathematica
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function [train_input, train_target, valid_input, valid_target, test_input, test_target, vocab] = load_data(N)
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% This method loads the training, validation and test set.
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% It also divides the training set into mini-batches.
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% Inputs:
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% N: Mini-batch size.
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% Outputs:
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% train_input: An array of size D X N X M, where
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% D: number of input dimensions (in this case, 3).
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% N: size of each mini-batch (in this case, 100).
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% M: number of minibatches.
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% train_target: An array of size 1 X N X M.
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% valid_input: An array of size D X number of points in the validation set.
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% test: An array of size D X number of points in the test set.
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% vocab: Vocabulary containing index to word mapping.
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load data.mat;
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numdims = size(data.trainData, 1);
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D = numdims - 1;
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M = floor(size(data.trainData, 2) / N);
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train_input = reshape(data.trainData(1:D, 1:N * M), D, N, M);
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train_target = reshape(data.trainData(D + 1, 1:N * M), 1, N, M);
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valid_input = data.validData(1:D, :);
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valid_target = data.validData(D + 1, :);
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test_input = data.testData(1:D, :);
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test_target = data.testData(D + 1, :);
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vocab = data.vocab;
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end
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