27 lines
749 B
Matlab
27 lines
749 B
Matlab
function test_nn_gradients_are_numerically_correct
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batch_x = rand(20, 5);
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batch_y = rand(20, 2);
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for output = {'sigm', 'linear', 'softmax'}
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y=batch_y;
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if(strcmp(output,'softmax'))
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% softmax output requires a binary output vector
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y=(y==repmat(max(y,[],2),1,size(y,2)));
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end
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for activation_function = {'sigm', 'tanh_opt'}
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for dropoutFraction = {0 rand()}
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nn = nnsetup([5 3 4 2]);
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nn.activation_function = activation_function{1};
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nn.output = output{1};
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nn.dropoutFraction = dropoutFraction{1};
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rand('state',0)
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nn = nnff(nn, batch_x, y);
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nn = nnbp(nn);
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nnchecknumgrad(nn, batch_x, y);
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end
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end
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end
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