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mnist.cpp
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#include <iostream>
#include <vector>
#include "OnnxMlirRuntime.h"
// Declare the inference entry point.
extern "C" OMTensorList *run_main_graph(OMTensorList *);
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int main() {
// Create an input tensor list of 1 tensor.
int inputNum = 1;
OMTensor **inputTensors = (OMTensor **)malloc(inputNum * sizeof(OMTensor *));
// The first input is of tensor<1x1x28x28xf32>.
int64_t rank = 4;
int64_t shape[] = {1, 1, 28, 28};
OMTensor *tensor = omTensorCreate(img_data, shape, rank, ONNX_TYPE_FLOAT);
// Create a tensor list.
inputTensors[0] = tensor;
OMTensorList *tensorListIn = omTensorListCreate(inputTensors, inputNum);
// Compute outputs.
OMTensorList *tensorListOut = run_main_graph(tensorListIn);
// Extract the output. The model defines one output of type tensor<1x10xf32>.
OMTensor *y = omTensorListGetOmtByIndex(tensorListOut, 0);
float *prediction = (float *)omTensorGetDataPtr(y);
// Analyze the output.
int digit = -1;
float prob = 0.;
for (int i = 0; i < 10; i++) {
printf("prediction[%d] = %f\n", i, prediction[i]);
if (prediction[i] > prob) {
digit = i;
prob = prediction[i];
}
}
printf("The digit is %d\n", digit);
return 0;
}