mirror of
https://github.com/zebrajr/pytorch.git
synced 2025-12-07 12:21:27 +01:00
72b1194464
Summary: Hooks into existing autograd codegen script (generate_code.py) to take advantage of its integrations into buck/cmake/bazel. Adds a new option (--gen_lazy_ts_backend) to. generate_code.py, calling this from CMake OSS build and fbcode build, but not from other internal xplat/ovrsource builds (these could be opted in later) Bazel support is added in a later diff. Includes one generated file (torch/csrc/lazy/generated/LazyIr.h) in a unit test (test/cpp/lazy/test_ir.cpp) to partially verify the generator is working, but does not compile the remaining output sources from the generator yet as they depend on other files not yet landed from lazy_tensor_staging branch. Pull Request resolved: https://github.com/pytorch/pytorch/pull/73996 Test Plan: OSS/internal CI - verify all builds are working and test_ir.cpp compiles LazyIr.h Reviewed By: ezyang Differential Revision: D34408536 fbshipit-source-id: 8af0aea3b95d81eccafc17d64390d70ddd176515 (cherry picked from commit f930612f2bad61c76eb02d85cfbec9f33a1459dc)
83 lines
3.0 KiB
C++
83 lines
3.0 KiB
C++
#include <gtest/gtest.h>
|
|
#include <string>
|
|
|
|
#include <torch/csrc/lazy/core/hash.h>
|
|
#include <c10/util/int128.h>
|
|
|
|
namespace torch {
|
|
namespace lazy {
|
|
|
|
template <typename T>
|
|
void test_hash_repeatable_sensitive(const T& example_a, const T& example_b) {
|
|
// repeatable
|
|
EXPECT_EQ(Hash(example_a), Hash(example_a));
|
|
EXPECT_EQ(MHash(example_a), MHash(example_a));
|
|
EXPECT_EQ(MHash(example_a, example_a), MHash(example_a, example_a));
|
|
|
|
// sensitive
|
|
EXPECT_NE(Hash(example_a), Hash(example_b));
|
|
EXPECT_NE(MHash(example_a), MHash(example_b));
|
|
EXPECT_NE(MHash(example_a, example_a), MHash(example_a, example_b));
|
|
}
|
|
|
|
TEST(HashTest, Scalar) {
|
|
c10::Scalar a(0);
|
|
c10::Scalar b(0);
|
|
|
|
// simulate some garbage in the unused bits of the
|
|
// the tagged union that is c10::Scalar, which is bigger
|
|
// than the size of the int64_t we're currently using it with
|
|
*((uint8_t*)&b) = 1;
|
|
// actual 'value' of the Scalar as a 64 bit int shouldn't have changed
|
|
EXPECT_EQ(a.toLong(), b.toLong());
|
|
// and hash should ignore this garbage
|
|
EXPECT_EQ(Hash(a), Hash(b));
|
|
EXPECT_EQ(MHash(a), MHash(b));
|
|
EXPECT_EQ(MHash(a, a), MHash(a, b));
|
|
}
|
|
|
|
TEST(HashTest, Sanity) {
|
|
// String
|
|
test_hash_repeatable_sensitive(
|
|
std::string(
|
|
"Lorem ipsum dolor sit amet, consectetur adipiscing elit. Ut at suscipit purus."),
|
|
std::string(
|
|
"Lorem Jpsum dolor sit amet, consectetur adipiscing elit. Ut at suscipit purus."));
|
|
|
|
// Number types
|
|
test_hash_repeatable_sensitive(true, false);
|
|
test_hash_repeatable_sensitive((int8_t)0xfa, (int8_t)0xfb);
|
|
test_hash_repeatable_sensitive((int16_t)0xface, (int16_t)0xfade);
|
|
test_hash_repeatable_sensitive((int32_t)0xfaceb000, (int32_t)0xfadeb000);
|
|
test_hash_repeatable_sensitive((int64_t)0x1faceb000, (int64_t)0x1fadeb000);
|
|
test_hash_repeatable_sensitive((uint8_t)0xfa, (uint8_t)0xfb);
|
|
test_hash_repeatable_sensitive((uint16_t)0xface, (uint16_t)0xfade);
|
|
test_hash_repeatable_sensitive((uint32_t)0xfaceb000, (uint32_t)0xfadeb000);
|
|
test_hash_repeatable_sensitive((uint64_t)0x1faceb000, (uint64_t)0x1fadeb000);
|
|
|
|
// c10 types
|
|
test_hash_repeatable_sensitive(c10::ScalarType::Bool, c10::ScalarType::Byte);
|
|
test_hash_repeatable_sensitive(c10::Scalar(1.334), c10::Scalar(1.335));
|
|
test_hash_repeatable_sensitive(c10::Scalar(true), c10::Scalar(false));
|
|
test_hash_repeatable_sensitive(c10::Scalar(12345), c10::Scalar(12354));
|
|
|
|
// c10::optional
|
|
test_hash_repeatable_sensitive(
|
|
c10::optional<std::string>("I have value!"),
|
|
c10::optional<std::string>(c10::nullopt));
|
|
|
|
// Containers
|
|
auto a = std::vector<int32_t>({0, 1, 1, 2, 3, 5, 8});
|
|
auto b = std::vector<int32_t>({1, 1, 2, 3, 5, 8, 12});
|
|
test_hash_repeatable_sensitive(a, b);
|
|
test_hash_repeatable_sensitive(c10::ArrayRef<int32_t>(a), c10::ArrayRef<int32_t>(b));
|
|
|
|
// vector<bool> is a special case bc it is implemented as vector<bit>
|
|
auto bool_a = std::vector<bool>({true, false, false, true});
|
|
auto bool_b = std::vector<bool>({true, true, false, true});
|
|
test_hash_repeatable_sensitive(bool_a, bool_b);
|
|
}
|
|
|
|
} // namespace lazy
|
|
} // namespace torch
|