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| Original file line number | Diff line number | Diff line change |
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| @@ -0,0 +1,194 @@ | ||
| #include <unistd.h> | ||
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| #include <cassert> | ||
| #include <cstdlib> | ||
| #include <cstring> | ||
| #include <limits> | ||
| #include <stdexcept> | ||
| #include <wf/basedb.hpp> | ||
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| #include "AMS.h" | ||
| #include "ml/surrogate.hpp" | ||
| #include "wf/debug.h" | ||
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| using namespace ams; | ||
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| AMSDType getDataType(char *d_type) | ||
| { | ||
| AMSDType dType = AMSDType::AMS_DOUBLE; | ||
| if (std::strcmp(d_type, "float") == 0) { | ||
| dType = AMSDType::AMS_SINGLE; | ||
| } else if (std::strcmp(d_type, "double") == 0) { | ||
| dType = AMSDType::AMS_DOUBLE; | ||
| } else { | ||
| assert(false && "Unknown data type"); | ||
| } | ||
| return dType; | ||
| } | ||
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| template <typename DType> | ||
| struct Problem { | ||
| int num_inputs; | ||
| int num_outputs; | ||
| int multiplier; | ||
| Problem(int ni, int no) : num_inputs(ni), num_outputs(no), multiplier(100) {} | ||
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| void run(long num_elements, DType **inputs, DType **outputs, DType constant) | ||
| { | ||
| for (int i = 0; i < num_elements; i++) { | ||
| DType sum = constant; | ||
| for (int j = 0; j < num_inputs - 1; j++) { | ||
| sum += inputs[j][i]; | ||
| } | ||
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| for (int j = 0; j < num_outputs; j++) { | ||
| outputs[j][i] = sum; | ||
| } | ||
| } | ||
| } | ||
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| DType *initialize_inputs(DType *inputs, long length) | ||
| { | ||
| for (int i = 0; i < length; i++) { | ||
| inputs[i] = static_cast<DType>(i); | ||
| } | ||
| return inputs; | ||
| } | ||
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| void ams_run(AMSExecutor &wf, | ||
| AMSResourceType resource, | ||
| int iterations, | ||
| int num_elements) | ||
| { | ||
| DType value = 1.0; | ||
| for (int i = 0; i < iterations; i++) { | ||
| int elements = num_elements; // * ((DType)(rand()) / RAND_MAX) + 1; | ||
| SmallVector<AMSTensor> input_tensors; | ||
| SmallVector<AMSTensor> output_tensors; | ||
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| // Allocate Input memory | ||
| for (int j = 0; j < num_inputs - 1; j++) { | ||
| DType *data = new DType[elements]; | ||
| input_tensors.push_back( | ||
| AMSTensor::view(initialize_inputs(data, elements), | ||
| {num_elements, 1}, | ||
| {1, 1}, | ||
| resource)); | ||
| } | ||
| value = num_inputs - 1; | ||
| input_tensors.push_back( | ||
| AMSTensor::view(&value, {num_elements, 1}, {0, 0}, resource)); | ||
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| // Allocate Output memory | ||
| for (int j = 0; j < num_outputs; j++) { | ||
| auto tmp = new DType[elements]; | ||
| output_tensors.push_back( | ||
| AMSTensor::view(initialize_inputs(tmp, elements), | ||
| {num_elements, 1}, | ||
| {1, 1}, | ||
| resource)); | ||
| } | ||
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| EOSLambda OrigComputation = | ||
| [&](const ams::SmallVector<ams::AMSTensor> &ams_ins, | ||
| ams::SmallVector<ams::AMSTensor> &ams_inouts, | ||
| ams::SmallVector<ams::AMSTensor> &ams_outs) { | ||
| DType *ins[num_inputs - 1]; | ||
| DType *outs[num_outputs]; | ||
| if (num_inputs != ams_ins.size()) | ||
| throw std::runtime_error( | ||
| "Expecting dimensions of inputs to remain the same"); | ||
| else if (num_outputs != ams_outs.size()) | ||
| throw std::runtime_error( | ||
| "Expecting dimensions of outputs to remain the same"); | ||
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| // Here I can use domain knowledge (inouts is empty) | ||
| int num_elements = ams_ins[0].shape()[0]; | ||
| for (int i = 0; i < num_inputs - 1; i++) { | ||
| ins[i] = ams_ins[i].data<DType>(); | ||
| if (ams_ins[i].shape()[0] != num_elements) | ||
| throw std::runtime_error( | ||
| "Expected tensors to have the same shape"); | ||
| } | ||
| for (int i = 0; i < num_outputs; i++) { | ||
| outs[i] = ams_outs[i].data<DType>(); | ||
| if (ams_outs[i].shape()[0] != num_elements) | ||
| throw std::runtime_error( | ||
| "Expected tensors to have the same shape"); | ||
| } | ||
| run(num_elements, | ||
| ins, | ||
| outs, | ||
| *ams_ins[num_inputs - 1].data<DType>()); | ||
| }; | ||
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| ams::SmallVector<AMSTensor> inouts; | ||
| AMSExecute(wf, OrigComputation, input_tensors, inouts, output_tensors); | ||
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| for (int i = 0; i < input_tensors.size() - 1; i++) { | ||
| delete input_tensors[i].data<DType>(); | ||
| } | ||
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| for (int i = 0; i < output_tensors.size(); i++) { | ||
| delete output_tensors[i].data<DType>(); | ||
| } | ||
| } | ||
| } | ||
| }; | ||
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| int main(int argc, char **argv) | ||
| { | ||
| if (argc != 12) { | ||
| std::cout << "Wrong cli\n"; | ||
| std::cout << argv[0] | ||
| << " use_device(0|1) num_inputs num_outputs model_path " | ||
| "data_type(float|double) uq_policy(random|deltaUQ " | ||
| "(mean)|deltaUQ (max)) threshold(0) " | ||
| "num_iterations avg_num_values db_type(none|csv|hdf5) " | ||
| "db_path(path to existing path to store data)"; | ||
| return -1; | ||
| } | ||
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| int use_device = std::atoi(argv[1]); | ||
| int num_inputs = std::atoi(argv[2]); | ||
| int num_outputs = std::atoi(argv[3]); | ||
| char *model_path = argv[4]; | ||
| AMSDType data_type = getDataType(argv[5]); | ||
| std::string uq_name = std::string(argv[6]); | ||
| const AMSUQPolicy uq_policy = UQ::UQPolicyFromStr(uq_name); | ||
| float threshold = std::atof(argv[7]); | ||
| int num_iterations = std::atoi(argv[8]); | ||
| int avg_elements = std::atoi(argv[9]); | ||
| std::string db_type_str = std::string(argv[10]); | ||
| std::string fs_path = std::string(argv[11]); | ||
| AMSDBType db_type = ams::db::getDBType(db_type_str); | ||
| AMSResourceType resource = AMSResourceType::AMS_HOST; | ||
| srand(time(NULL)); | ||
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| AMSConfigureFSDatabase(db_type, fs_path.c_str()); | ||
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| assert((uq_policy == AMSUQPolicy::AMS_DELTAUQ_MAX || | ||
| uq_policy == AMSUQPolicy::AMS_DELTAUQ_MEAN || | ||
| uq_policy == AMSUQPolicy::AMS_RANDOM) && | ||
| "Test only supports duq models"); | ||
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| AMSCAbstrModel model_descr = AMSRegisterAbstractModel( | ||
| "test", uq_policy, threshold, model_path, "test"); | ||
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| AMSExecutor wf = AMSCreateExecutor(model_descr, 0, 1); | ||
| if (data_type == AMSDType::AMS_SINGLE) { | ||
| Problem<float> prob(num_inputs, num_outputs); | ||
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| prob.ams_run(wf, resource, num_iterations, avg_elements); | ||
| } else { | ||
| Problem<double> prob(num_inputs, num_outputs); | ||
| prob.ams_run(wf, resource, num_iterations, avg_elements); | ||
| } | ||
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| return 0; | ||
| } |