Revision 3657cf5f363fd64aeaf06432e62e3960800927b0 authored by Andrew Adams on 26 January 2024, 17:26:12 UTC, committed by GitHub on 26 January 2024, 17:26:12 UTC
* Fix bounds_of_nested_lanes bounds_of_nested_lanes assumed that one layer of nested vectorization could be removed at a time. When faced with the expression: min(ramp(x8(a), x8(b), 5), x40(27)) It panicked, because on the left hand side it reduced the bounds to x8(a) ... x8(a) + x8(b) * 4, and on the right hand side it reduced the bounds to 27. It then attempted to take a min of mismatched types. In general we can't assume that binary operators on nested vectors have the same nesting structure on both sides, so I just rewrote it to reduce directly to a scalar. Fixes #8038
1 parent 4590a09
lesson_01_basics.cpp
// Halide tutorial lesson 1: Getting started with Funcs, Vars, and Exprs
// This lesson demonstrates basic usage of Halide as a JIT compiler for imaging.
// On linux, you can compile and run it like so:
// g++ lesson_01*.cpp -g -I <path/to/Halide.h> -L <path/to/libHalide.so> -lHalide -lpthread -ldl -o lesson_01 -std=c++17
// LD_LIBRARY_PATH=<path/to/libHalide.so> ./lesson_01
// On os x:
// g++ lesson_01*.cpp -g -I <path/to/Halide.h> -L <path/to/libHalide.so> -lHalide -o lesson_01 -std=c++17
// DYLD_LIBRARY_PATH=<path/to/libHalide.dylib> ./lesson_01
// If you have the entire Halide source tree, you can also build it by
// running:
// make tutorial_lesson_01_basics
// in a shell with the current directory at the top of the halide
// source tree.
// The only Halide header file you need is Halide.h. It includes all of Halide.
#include "Halide.h"
// We'll also include stdio for printf.
#include <stdio.h>
int main(int argc, char **argv) {
// This program defines a single-stage imaging pipeline that
// outputs a grayscale diagonal gradient.
// A 'Func' object represents a pipeline stage. It's a pure
// function that defines what value each pixel should have. You
// can think of it as a computed image.
Halide::Func gradient;
// Var objects are names to use as variables in the definition of
// a Func. They have no meaning by themselves.
Halide::Var x, y;
// We typically use Vars named 'x' and 'y' to correspond to the x
// and y axes of an image, and we write them in that order. If
// you're used to thinking of images as having rows and columns,
// then x is the column index, and y is the row index.
// Funcs are defined at any integer coordinate of its variables as
// an Expr in terms of those variables and other functions.
// Here, we'll define an Expr which has the value x + y. Vars have
// appropriate operator overloading so that expressions like
// 'x + y' become 'Expr' objects.
Halide::Expr e = x + y;
// Now we'll add a definition for the Func object. At pixel x, y,
// the image will have the value of the Expr e. On the left hand
// side we have the Func we're defining and some Vars. On the right
// hand side we have some Expr object that uses those same Vars.
gradient(x, y) = e;
// This is the same as writing:
//
// gradient(x, y) = x + y;
//
// which is the more common form, but we are showing the
// intermediate Expr here for completeness.
// That line of code defined the Func, but it didn't actually
// compute the output image yet. At this stage it's just Funcs,
// Exprs, and Vars in memory, representing the structure of our
// imaging pipeline. We're meta-programming. This C++ program is
// constructing a Halide program in memory. Actually computing
// pixel data comes next.
// Now we 'realize' the Func, which JIT compiles some code that
// implements the pipeline we've defined, and then runs it. We
// also need to tell Halide the domain over which to evaluate the
// Func, which determines the range of x and y above, and the
// resolution of the output image. Halide.h also provides a basic
// templatized image type we can use. We'll make an 800 x 600
// image.
Halide::Buffer<int32_t> output = gradient.realize({800, 600});
// Halide does type inference for you. Var objects represent
// 32-bit integers, so the Expr object 'x + y' also represents a
// 32-bit integer, and so 'gradient' defines a 32-bit image, and
// so we got a 32-bit signed integer image out when we call
// 'realize'. Halide types and type-casting rules are equivalent
// to C.
// Let's check everything worked, and we got the output we were
// expecting:
for (int j = 0; j < output.height(); j++) {
for (int i = 0; i < output.width(); i++) {
// We can access a pixel of an Buffer object using similar
// syntax to defining and using functions.
if (output(i, j) != i + j) {
printf("Something went wrong!\n"
"Pixel %d, %d was supposed to be %d, but instead it's %d\n",
i, j, i + j, output(i, j));
return -1;
}
}
}
// Everything worked! We defined a Func, then called 'realize' on
// it to generate and run machine code that produced an Buffer.
printf("Success!\n");
return 0;
}
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