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#include <neuralnet/neuralnet.h>
#include <neuralnet/matrix.h>
#include "activation.h"
#include "neuralnet_impl.h"
#include "test.h"
#include "test_util.h"
#include <assert.h>
TEST_CASE(neuralnet_perceptron_test) {
const int num_layers = 1;
const int layer_sizes[] = { 1, 1 };
const nnActivation layer_activations[] = { nnSigmoid };
const R weights[] = { 0.3 };
nnNeuralNetwork* net = nnMakeNet(num_layers, layer_sizes, layer_activations);
assert(net);
nnSetWeights(net, weights);
nnQueryObject* query = nnMakeQueryObject(net, /*num_inputs=*/1);
const R input[] = { 0.9 };
R output[1];
nnQueryArray(net, query, input, output);
const R expected_output = sigmoid(input[0] * weights[0]);
printf("\nOutput: %f, Expected: %f\n", output[0], expected_output);
TEST_TRUE(double_eq(output[0], expected_output, EPS));
nnDeleteQueryObject(&query);
nnDeleteNet(&net);
}
TEST_CASE(neuralnet_xor_test) {
const int num_layers = 2;
const int layer_sizes[] = { 2, 2, 1 };
const nnActivation layer_activations[] = { nnRelu, nnIdentity };
const R weights[] = {
1, 1, 1, 1, // First (hidden) layer.
1, -2 // Second (output) layer.
};
const R biases[] = {
0, -1, // First (hidden) layer.
0 // Second (output) layer.
};
nnNeuralNetwork* net = nnMakeNet(num_layers, layer_sizes, layer_activations);
assert(net);
nnSetWeights(net, weights);
nnSetBiases(net, biases);
// First layer weights.
TEST_EQUAL(nnMatrixAt(&net->weights[0], 0, 0), 1);
TEST_EQUAL(nnMatrixAt(&net->weights[0], 0, 1), 1);
TEST_EQUAL(nnMatrixAt(&net->weights[0], 0, 2), 1);
TEST_EQUAL(nnMatrixAt(&net->weights[0], 0, 3), 1);
// Second layer weights.
TEST_EQUAL(nnMatrixAt(&net->weights[1], 0, 0), 1);
TEST_EQUAL(nnMatrixAt(&net->weights[1], 0, 1), -2);
// First layer biases.
TEST_EQUAL(nnMatrixAt(&net->biases[0], 0, 0), 0);
TEST_EQUAL(nnMatrixAt(&net->biases[0], 0, 1), -1);
// Second layer biases.
TEST_EQUAL(nnMatrixAt(&net->biases[1], 0, 0), 0);
// Test.
#define M 4
nnQueryObject* query = nnMakeQueryObject(net, /*num_inputs=*/M);
const R test_inputs[M][2] = { { 0., 0. }, { 1., 0. }, { 0., 1. }, { 1., 1. } };
nnMatrix test_inputs_matrix = nnMatrixMake(M, 2);
nnMatrixInit(&test_inputs_matrix, (const R*)test_inputs);
nnQuery(net, query, &test_inputs_matrix);
const R expected_outputs[M] = { 0., 1., 1., 0. };
for (int i = 0; i < M; ++i) {
const R test_output = nnMatrixAt(nnNetOutputs(query), i, 0);
printf("\nInput: (%f, %f), Output: %f, Expected: %f\n",
test_inputs[i][0], test_inputs[i][1], test_output, expected_outputs[i]);
}
for (int i = 0; i < M; ++i) {
const R test_output = nnMatrixAt(nnNetOutputs(query), i, 0);
TEST_TRUE(double_eq(test_output, expected_outputs[i], OUTPUT_EPS));
}
nnDeleteQueryObject(&query);
nnDeleteNet(&net);
}
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