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#include "Halide.h"
#include <algorithm>
#include <stdio.h>
using namespace Halide;
int main(int argc, char **argv) {
// Compute the variance of a 3x3 patch about each pixel
RDom r(-1, 3, -1, 3);
// Test a complex summation
Func input;
Var x, y, z;
input(x, y) = cast<float>(x * y + 1);
Func local_variance;
Expr input_val = input(x + r.x, y + r.y);
Expr local_mean = sum(input_val) / 9.0f;
local_variance(x, y) = sum(input_val * input_val) / 81.0f - local_mean * local_mean;
Buffer<float> result = local_variance.realize({10, 10});
for (int y = 0; y < 10; y++) {
for (int x = 0; x < 10; x++) {
float local_mean = 0;
float local_variance = 0;
for (int rx = -1; rx < 2; rx++) {
for (int ry = -1; ry < 2; ry++) {
float val = (x + rx) * (y + ry) + 1.0f;
local_mean += val;
local_variance += val * val;
}
}
local_mean /= 9.0f;
float correct = local_variance / 81.0f - local_mean * local_mean;
float r = result(x, y);
float delta = correct - r;
if (delta < -0.001 || delta > 0.001) {
printf("result(%d, %d) was %f instead of %f\n", x, y, r, correct);
return 1;
}
}
}
// Test the other reductions.
Func local_product, local_max, local_min;
local_product(x, y) = product(input_val);
local_max(x, y) = maximum(input_val);
local_min(x, y) = minimum(input_val);
// Try a separable form of minimum too, so we test two reductions
// in one pipeline. Use a user-provided Func for one of them and
// unroll the reduction domain.
Func min_x, min_y;
RDom kx(-1, 3), ky(-1, 3);
Func min_y_inner;
min_x(x, y) = minimum(input(x + kx, y));
min_y(x, y) = minimum(min_x(x, y + ky), min_y_inner);
// Vectorize them all, to make life more interesting.
local_product.vectorize(x, 4);
local_max.vectorize(x, 4);
local_min.vectorize(x, 4);
min_y.vectorize(x, 4);
// This would fail if the provided Func went unused.
min_y_inner.update().unroll(ky);
Buffer<float> prod_im = local_product.realize({10, 10});
Buffer<float> max_im = local_max.realize({10, 10});
Buffer<float> min_im = local_min.realize({10, 10});
Buffer<float> min_im_separable = min_y.realize({10, 10});
for (int y = 0; y < 10; y++) {
for (int x = 0; x < 10; x++) {
float correct_prod = 1.0f;
float correct_min = 1e10f;
float correct_max = -1e10f;
for (int rx = -1; rx < 2; rx++) {
for (int ry = -1; ry < 2; ry++) {
float val = (x + rx) * (y + ry) + 1.0f;
correct_prod *= val;
correct_min = std::min(correct_min, val);
correct_max = std::max(correct_max, val);
}
}
float delta;
delta = (correct_prod + 10) / (prod_im(x, y) + 10);
if (delta < 0.99 || delta > 1.01) {
printf("prod_im(%d, %d) = %f instead of %f\n", x, y, prod_im(x, y), correct_prod);
return 1;
}
delta = correct_min - min_im(x, y);
if (delta < -0.001 || delta > 0.001) {
printf("min_im(%d, %d) = %f instead of %f\n", x, y, min_im(x, y), correct_min);
return 1;
}
delta = correct_min - min_im_separable(x, y);
if (delta < -0.001 || delta > 0.001) {
printf("min_im(%d, %d) = %f instead of %f\n", x, y, min_im_separable(x, y), correct_min);
return 1;
}
delta = correct_max - max_im(x, y);
if (delta < -0.001 || delta > 0.001) {
printf("max_im(%d, %d) = %f instead of %f\n", x, y, max_im(x, y), correct_max);
return 1;
}
}
}
// Verify that all inline reductions compile with implicit argument syntax.
Buffer<float> input_3d = lambda(x, y, z, x * 100.0f + y * 10.0f + ((z + 5 % 10))).realize({10, 10, 10});
RDom all_z(input_3d.min(2), input_3d.extent(2));
Func sum_implicit_inner, sum_implicit;
sum_implicit(_) = sum(input_3d(_, all_z), sum_implicit_inner);
Buffer<float> sum_implicit_im = sum_implicit.realize({10, 10});
// The inner Func ends with with _0, _1, etc as its free vars.
auto args = sum_implicit_inner.args();
if (args.size() != 2 ||
args[0].name() != Var(_0).name() ||
args[1].name() != Var(_1).name()) {
printf("sum_implicit_inner has the wrong args\n");
return 1;
}
Func product_implicit;
product_implicit(_) = product(input_3d(_, all_z));
Buffer<float> product_implicit_im = product_implicit.realize({10, 10});
Func min_implicit;
min_implicit(_) = minimum(input_3d(_, all_z));
Buffer<float> min_implicit_im = min_implicit.realize({10, 10});
Func max_implicit;
max_implicit(_, y) = maximum(input_3d(_, y, all_z));
Buffer<float> max_implicit_im = max_implicit.realize({10, 10});
Func argmin_implicit;
argmin_implicit(_) = argmin(input_3d(_, all_z))[0];
Buffer<int32_t> argmin_implicit_im = argmin_implicit.realize({10, 10});
Func argmax_implicit;
argmax_implicit(x, _) = argmax(input_3d(x, _, all_z))[0];
Buffer<int32_t> argmax_implicit_im = argmax_implicit.realize({10, 10});
// Verify that the min of negative floats and doubles is correct
// (this used to be buggy due to the minimum float being the
// smallest positive float instead of the smallest float).
float result_f32 = evaluate<float>(minimum(RDom(0, 11) * -0.5f));
if (result_f32 != -5.0f) {
printf("minimum is %f instead of -5.0f\n", result_f32);
return 1;
}
double result_f64 = evaluate<double>(minimum(RDom(0, 11) * cast<double>(-0.5f)));
if (result_f64 != -5.0) {
printf("minimum is %f instead of -5.0\n", result_f64);
return 1;
}
// Check that min of a bunch of infinities is infinity.
// Be sure to use strict_float() so that LLVM doesn't optimize away
// the infinities.
const float inf_f32 = std::numeric_limits<float>::infinity();
const double inf_f64 = std::numeric_limits<double>::infinity();
result_f32 = evaluate<float>(minimum(strict_float(RDom(1, 10) * inf_f32)));
if (result_f32 != inf_f32) {
printf("minimum is %f instead of infinity\n", result_f32);
return 1;
}
result_f64 = evaluate<double>(minimum(strict_float(RDom(1, 10) * Expr(inf_f64))));
if (result_f64 != inf_f64) {
printf("minimum is %f instead of infinity\n", result_f64);
return 1;
}
result_f32 = evaluate<float>(maximum(strict_float(RDom(1, 10) * -inf_f32)));
if (result_f32 != -inf_f32) {
printf("maximum is %f instead of -infinity\n", result_f32);
return 1;
}
result_f64 = evaluate<double>(maximum(strict_float(RDom(1, 10) * Expr(-inf_f64))));
if (result_f64 != -inf_f64) {
printf("maximum is %f instead of -infinity\n", result_f64);
return 1;
}
printf("Success!\n");
return 0;
}
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