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changes made from review, added tests and all passed but only when ed…
…ge weights are allowed to train
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| Original file line number | Diff line number | Diff line change |
|---|---|---|
| @@ -0,0 +1,136 @@ | ||
| #include <chrono> | ||
| #include <fstream> | ||
| using std::getline; | ||
| using std::ifstream; | ||
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| #include <random> | ||
| using std::minstd_rand0; | ||
| using std::uniform_real_distribution; | ||
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| #include <string> | ||
| using std::string; | ||
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| #include <vector> | ||
| using std::vector; | ||
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| #include "common/arguments.hxx" | ||
| #include "common/log.hxx" | ||
| #include "gradient_test.hxx" | ||
| #include "rnn/cos_node_gp.hxx" | ||
| #include "rnn/generate_nn.hxx" | ||
| #include "rnn/rnn_edge.hxx" | ||
| #include "rnn/rnn_genome.hxx" | ||
| #include "rnn/rnn_node.hxx" | ||
| #include "rnn/rnn_node_interface.hxx" | ||
| #include "time_series/time_series.hxx" | ||
| #include "weights/weight_rules.hxx" | ||
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| int main(int argc, char** argv) { | ||
| vector<string> arguments = vector<string>(argv, argv + argc); | ||
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| Log::initialize(arguments); | ||
| Log::set_id("main"); | ||
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| initialize_generator(); | ||
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| RNN_Genome* genome; | ||
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| Log::info("TESTING COS_GP\n"); | ||
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| vector<vector<double> > inputs; | ||
| vector<vector<double> > outputs; | ||
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| int input_length = 10; | ||
| get_argument(arguments, "--input_length", true, input_length); | ||
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| WeightRules* weight_rules = new WeightRules(); | ||
| weight_rules->initialize_from_args(arguments); | ||
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| for (int32_t max_recurrent_depth = 1; max_recurrent_depth <= 5; max_recurrent_depth++) { | ||
| Log::info("testing with max recurrent depth: %d\n", max_recurrent_depth); | ||
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| inputs.resize(1); | ||
| outputs.resize(1); | ||
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| generate_random_vector(input_length, inputs[0]); | ||
| generate_random_vector(input_length, outputs[0]); | ||
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| vector<string> inputs1{"input 1"}; | ||
| vector<string> outputs1{"output 1"}; | ||
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| // Test 1 input, 1 output, no hidden | ||
| genome = create_cos_gp(inputs1, 0, 0, outputs1, max_recurrent_depth, weight_rules); | ||
| gradient_test("COS_GP: 1 Input, 1 Output", genome, inputs, outputs); | ||
| delete genome; | ||
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| genome = create_cos_gp(inputs1, 1, 1, outputs1, max_recurrent_depth, weight_rules); | ||
| gradient_test("COS_GP: 1 Input, 1x1 Hidden, 1 Output", genome, inputs, outputs); | ||
| delete genome; | ||
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| genome = create_cos_gp(inputs1, 1, 2, outputs1, max_recurrent_depth, weight_rules); | ||
| gradient_test("COS_GP: 1 Input, 1x2 Hidden, 1 Output", genome, inputs, outputs); | ||
| delete genome; | ||
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| genome = create_cos_gp(inputs1, 2, 2, outputs1, max_recurrent_depth, weight_rules); | ||
| gradient_test("COS_GP: 1 Input, 2x2 Hidden, 1 Output", genome, inputs, outputs); | ||
| delete genome; | ||
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| vector<string> inputs2{"input 1", "input 2"}; | ||
| vector<string> outputs2{"output 1", "output 2"}; | ||
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| // //Test 2 inputs, 2 outputs, no hidden | ||
| genome = create_cos_gp(inputs2, 0, 0, outputs2, max_recurrent_depth, weight_rules); | ||
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| inputs.resize(2); | ||
| outputs.resize(2); | ||
| generate_random_vector(input_length, inputs[0]); | ||
| generate_random_vector(input_length, outputs[0]); | ||
| generate_random_vector(input_length, inputs[1]); | ||
| generate_random_vector(input_length, outputs[1]); | ||
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| gradient_test("COS_GP: 2 Input, 2 Output", genome, inputs, outputs); | ||
| delete genome; | ||
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| genome = create_cos_gp(inputs2, 2, 2, outputs2, max_recurrent_depth, weight_rules); | ||
| gradient_test("COS_GP: 2 Input, 2x2 Hidden, 2 Output", genome, inputs, outputs); | ||
| delete genome; | ||
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| genome = create_cos_gp(inputs2, 2, 3, outputs2, max_recurrent_depth, weight_rules); | ||
| gradient_test("COS_GP: 2 Input, 2x3 Hidden, 2 Output", genome, inputs, outputs); | ||
| delete genome; | ||
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| genome = create_cos_gp(inputs2, 3, 3, outputs2, max_recurrent_depth, weight_rules); | ||
| gradient_test("COS_GP: 2 Input, 3x3 Hidden, 2 Output", genome, inputs, outputs); | ||
| delete genome; | ||
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| vector<string> inputs3{"input 1", "input 2", "input 3"}; | ||
| vector<string> outputs3{"output 1", "output 2", "input 3"}; | ||
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| // Test 3 inputs, 3 outputs, no hidden | ||
| genome = create_cos_gp(inputs3, 0, 0, outputs3, max_recurrent_depth, weight_rules); | ||
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| inputs.resize(3); | ||
| outputs.resize(3); | ||
| generate_random_vector(input_length, inputs[0]); | ||
| generate_random_vector(input_length, outputs[0]); | ||
| generate_random_vector(input_length, inputs[1]); | ||
| generate_random_vector(input_length, outputs[1]); | ||
| generate_random_vector(input_length, inputs[2]); | ||
| generate_random_vector(input_length, outputs[2]); | ||
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| gradient_test("COS_GP: Three Input, Three Output", genome, inputs, outputs); | ||
| delete genome; | ||
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| genome = create_cos_gp(inputs3, 3, 3, outputs3, max_recurrent_depth, weight_rules); | ||
| gradient_test("COS_GP: 3 Input, 3x3 Hidden, 3 Output", genome, inputs, outputs); | ||
| delete genome; | ||
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| genome = create_cos_gp(inputs3, 3, 4, outputs3, max_recurrent_depth, weight_rules); | ||
| gradient_test("COS_GP: 3 Input, 3x4 Hidden, 3 Output", genome, inputs, outputs); | ||
| delete genome; | ||
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| genome = create_cos_gp(inputs3, 4, 4, outputs3, max_recurrent_depth, weight_rules); | ||
| gradient_test("COS_gp: 3 Input, 4x4 Hidden, 3 Output", genome, inputs, outputs); | ||
| delete genome; | ||
| } | ||
| } |
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