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Implemented NeuralNet's tests for basic logical/binary gates
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| // SPDX-License-Identifier: BSD-3-Clause OR GPL-3.0-only | ||
| // Copyright (C) Wasym A. Alonso. All Rights Reserved. | ||
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| #include <carbon.h> | ||
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| CARBON_TEST(carbon_nn, or_gate) { | ||
| usz arch[] = {2, 1, 1}; | ||
| CBN_NeuralNet nn = carbon_nn_create(arch, CARBON_ARRAY_LEN(arch)); | ||
| carbon_math_srand(69); | ||
| carbon_nn_rand(nn, -1, 1); | ||
| CBN_Matrix train = carbon_math_mat_create(4, 3); | ||
| for (usz i = 0; i < 2; ++i) { | ||
| for (usz j = 0; j < 2; ++j) { | ||
| usz row = 2*i + j; | ||
| CARBON_MAT_AT(train, row, 0) = i, CARBON_MAT_AT(train, row, 1) = j; | ||
| CARBON_MAT_AT(train, row, 2) = i | j; | ||
| } | ||
| } | ||
| carbon_nn_fit(nn, 1e6, train, 1); | ||
| for (usz i = 0; i < 2; ++i) { | ||
| for (usz j = 0; j < 2; ++j) { | ||
| usz row = 2*i + j; | ||
| CARBON_MAT_AT(CARBON_NN_IN(nn), 0, 0) = i, CARBON_MAT_AT(CARBON_NN_IN(nn), 0, 1) = j; | ||
| carbon_nn_forward(nn); | ||
| carbon_should_be_f(CARBON_MAT_AT(train, row, 2), carbon_math_round(CARBON_MAT_AT(CARBON_NN_OUT(nn), 0, 0))); | ||
| } | ||
| } | ||
| carbon_math_mat_destroy(&train); | ||
| carbon_nn_destroy(&nn); | ||
| return CARBON_OK; | ||
| } | ||
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| CARBON_TEST(carbon_nn, nor_gate) { | ||
| usz arch[] = {2, 1, 1}; | ||
| CBN_NeuralNet nn = carbon_nn_create(arch, CARBON_ARRAY_LEN(arch)); | ||
| carbon_math_srand(69); | ||
| carbon_nn_rand(nn, -1, 1); | ||
| CBN_Matrix train = carbon_math_mat_create(4, 3); | ||
| for (usz i = 0; i < 2; ++i) { | ||
| for (usz j = 0; j < 2; ++j) { | ||
| usz row = 2*i + j; | ||
| CARBON_MAT_AT(train, row, 0) = i, CARBON_MAT_AT(train, row, 1) = j; | ||
| CARBON_MAT_AT(train, row, 2) = !(i | j); | ||
| } | ||
| } | ||
| carbon_nn_fit(nn, 1e6, train, 1); | ||
| for (usz i = 0; i < 2; ++i) { | ||
| for (usz j = 0; j < 2; ++j) { | ||
| usz row = 2*i + j; | ||
| CARBON_MAT_AT(CARBON_NN_IN(nn), 0, 0) = i, CARBON_MAT_AT(CARBON_NN_IN(nn), 0, 1) = j; | ||
| carbon_nn_forward(nn); | ||
| carbon_should_be_f(CARBON_MAT_AT(train, row, 2), carbon_math_round(CARBON_MAT_AT(CARBON_NN_OUT(nn), 0, 0))); | ||
| } | ||
| } | ||
| carbon_math_mat_destroy(&train); | ||
| carbon_nn_destroy(&nn); | ||
| return CARBON_OK; | ||
| } | ||
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| CARBON_TEST(carbon_nn, and_gate) { | ||
| usz arch[] = {2, 1, 1}; | ||
| CBN_NeuralNet nn = carbon_nn_create(arch, CARBON_ARRAY_LEN(arch)); | ||
| carbon_math_srand(69); | ||
| carbon_nn_rand(nn, -1, 1); | ||
| CBN_Matrix train = carbon_math_mat_create(4, 3); | ||
| for (usz i = 0; i < 2; ++i) { | ||
| for (usz j = 0; j < 2; ++j) { | ||
| usz row = 2*i + j; | ||
| CARBON_MAT_AT(train, row, 0) = i, CARBON_MAT_AT(train, row, 1) = j; | ||
| CARBON_MAT_AT(train, row, 2) = i & j; | ||
| } | ||
| } | ||
| carbon_nn_fit(nn, 1e6, train, 1); | ||
| for (usz i = 0; i < 2; ++i) { | ||
| for (usz j = 0; j < 2; ++j) { | ||
| usz row = 2*i + j; | ||
| CARBON_MAT_AT(CARBON_NN_IN(nn), 0, 0) = i, CARBON_MAT_AT(CARBON_NN_IN(nn), 0, 1) = j; | ||
| carbon_nn_forward(nn); | ||
| carbon_should_be_f(CARBON_MAT_AT(train, row, 2), carbon_math_round(CARBON_MAT_AT(CARBON_NN_OUT(nn), 0, 0))); | ||
| } | ||
| } | ||
| carbon_math_mat_destroy(&train); | ||
| carbon_nn_destroy(&nn); | ||
| return CARBON_OK; | ||
| } | ||
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| CARBON_TEST(carbon_nn, nand_gate) { | ||
| usz arch[] = {2, 1, 1}; | ||
| CBN_NeuralNet nn = carbon_nn_create(arch, CARBON_ARRAY_LEN(arch)); | ||
| carbon_math_srand(69); | ||
| carbon_nn_rand(nn, -1, 1); | ||
| CBN_Matrix train = carbon_math_mat_create(4, 3); | ||
| for (usz i = 0; i < 2; ++i) { | ||
| for (usz j = 0; j < 2; ++j) { | ||
| usz row = 2*i + j; | ||
| CARBON_MAT_AT(train, row, 0) = i, CARBON_MAT_AT(train, row, 1) = j; | ||
| CARBON_MAT_AT(train, row, 2) = !(i & j); | ||
| } | ||
| } | ||
| carbon_nn_fit(nn, 1e6, train, 1); | ||
| for (usz i = 0; i < 2; ++i) { | ||
| for (usz j = 0; j < 2; ++j) { | ||
| usz row = 2*i + j; | ||
| CARBON_MAT_AT(CARBON_NN_IN(nn), 0, 0) = i, CARBON_MAT_AT(CARBON_NN_IN(nn), 0, 1) = j; | ||
| carbon_nn_forward(nn); | ||
| carbon_should_be_f(CARBON_MAT_AT(train, row, 2), carbon_math_round(CARBON_MAT_AT(CARBON_NN_OUT(nn), 0, 0))); | ||
| } | ||
| } | ||
| carbon_math_mat_destroy(&train); | ||
| carbon_nn_destroy(&nn); | ||
| return CARBON_OK; | ||
| } | ||
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| CARBON_TEST(carbon_nn, xor_gate) { | ||
| usz arch[] = {2, 2, 1}; | ||
| CBN_NeuralNet nn = carbon_nn_create(arch, CARBON_ARRAY_LEN(arch)); | ||
| carbon_math_srand(69); | ||
| carbon_nn_rand(nn, -1, 1); | ||
| CBN_Matrix train = carbon_math_mat_create(4, 3); | ||
| for (usz i = 0; i < 2; ++i) { | ||
| for (usz j = 0; j < 2; ++j) { | ||
| usz row = 2*i + j; | ||
| CARBON_MAT_AT(train, row, 0) = i, CARBON_MAT_AT(train, row, 1) = j; | ||
| CARBON_MAT_AT(train, row, 2) = i ^ j; | ||
| } | ||
| } | ||
| carbon_nn_fit(nn, 1e6, train, 1); | ||
| for (usz i = 0; i < 2; ++i) { | ||
| for (usz j = 0; j < 2; ++j) { | ||
| usz row = 2*i + j; | ||
| CARBON_MAT_AT(CARBON_NN_IN(nn), 0, 0) = i, CARBON_MAT_AT(CARBON_NN_IN(nn), 0, 1) = j; | ||
| carbon_nn_forward(nn); | ||
| carbon_should_be_f(CARBON_MAT_AT(train, row, 2), carbon_math_round(CARBON_MAT_AT(CARBON_NN_OUT(nn), 0, 0))); | ||
| } | ||
| } | ||
| carbon_math_mat_destroy(&train); | ||
| carbon_nn_destroy(&nn); | ||
| return CARBON_OK; | ||
| } | ||
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| CARBON_TEST(carbon_nn, xnor_gate) { | ||
| usz arch[] = {2, 2, 1}; | ||
| CBN_NeuralNet nn = carbon_nn_create(arch, CARBON_ARRAY_LEN(arch)); | ||
| carbon_math_srand(69); | ||
| carbon_nn_rand(nn, -1, 1); | ||
| CBN_Matrix train = carbon_math_mat_create(4, 3); | ||
| for (usz i = 0; i < 2; ++i) { | ||
| for (usz j = 0; j < 2; ++j) { | ||
| usz row = 2*i + j; | ||
| CARBON_MAT_AT(train, row, 0) = i, CARBON_MAT_AT(train, row, 1) = j; | ||
| CARBON_MAT_AT(train, row, 2) = !(i ^ j); | ||
| } | ||
| } | ||
| carbon_nn_fit(nn, 1e6, train, 1); | ||
| for (usz i = 0; i < 2; ++i) { | ||
| for (usz j = 0; j < 2; ++j) { | ||
| usz row = 2*i + j; | ||
| CARBON_MAT_AT(CARBON_NN_IN(nn), 0, 0) = i, CARBON_MAT_AT(CARBON_NN_IN(nn), 0, 1) = j; | ||
| carbon_nn_forward(nn); | ||
| carbon_should_be_f(CARBON_MAT_AT(train, row, 2), carbon_math_round(CARBON_MAT_AT(CARBON_NN_OUT(nn), 0, 0))); | ||
| } | ||
| } | ||
| carbon_math_mat_destroy(&train); | ||
| carbon_nn_destroy(&nn); | ||
| return CARBON_OK; | ||
| } |