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#include <gtest/gtest.h>
#include <stdexcept>
#include "test/cpp/tensorexpr/test_base.h"
#include <torch/csrc/jit/tensorexpr/expr.h>
#include <torch/csrc/jit/tensorexpr/ir.h>
#include <torch/csrc/jit/tensorexpr/ir_printer.h>
#include <torch/csrc/jit/tensorexpr/loopnest.h>
#include <torch/csrc/jit/tensorexpr/tensor.h>
#include <torch/csrc/jit/testing/file_check.h>
#include <sstream>
namespace torch {
namespace jit {
using namespace torch::jit::tensorexpr;
TEST(IRPrinter, BasicValueTest) {
ExprHandle a = IntImm::make(2), b = IntImm::make(3);
ExprHandle c = Add::make(a, b);
std::stringstream ss;
ss << c;
ASSERT_EQ(ss.str(), "2 + 3");
}
TEST(IRPrinter, BasicValueTest02) {
ExprHandle a(2.0f);
ExprHandle b(3.0f);
ExprHandle c(4.0f);
ExprHandle d(5.0f);
ExprHandle f = (a + b) - (c + d);
std::stringstream ss;
ss << f;
ASSERT_EQ(ss.str(), "(2.f + 3.f) - (4.f + 5.f)");
}
TEST(IRPrinter, CastTest) {
VarHandle x("x", kHalf);
VarHandle y("y", kFloat);
ExprHandle body = ExprHandle(2.f) +
(Cast::make(kFloat, x) * ExprHandle(3.f) + ExprHandle(4.f) * y);
std::stringstream ss;
ss << body;
ASSERT_EQ(ss.str(), "2.f + (float(x) * 3.f + 4.f * y)");
}
TEST(IRPrinter, FunctionName) {
int M = 4;
int N = 20;
Tensor producer = Compute(
"producer", {M, N}, [&](const ExprHandle& m, const ExprHandle& n) {
return m * n;
});
Tensor chunk_0 = Compute(
"chunk_0", {M, N / 2}, [&](const ExprHandle& m, const ExprHandle& n) {
return producer.load(m, n);
});
Tensor chunk_1 = Compute(
"chunk_1", {M, N / 2}, [&](const ExprHandle& m, const ExprHandle& n) {
return producer.load(m, n + ExprHandle(N / 2));
});
Tensor consumer = Compute(
"consumer", {M, N / 2}, [&](const ExprHandle& i, const ExprHandle& j) {
return i * chunk_1.load(i, j);
});
LoopNest l({chunk_0, chunk_1, consumer});
auto body = LoopNest::sanitizeNames(l.root_stmt());
std::stringstream ss;
ss << *body;
const std::string& verification_pattern =
R"IR(
# CHECK: for (int i_2
# CHECK: for (int j_2
# CHECK: consumer[i_2, j_2] = i_2 * (chunk_1[i_2, j_2])IR";
torch::jit::testing::FileCheck().run(verification_pattern, ss.str());
}
} // namespace jit
} // namespace torch
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