mirror of
https://github.com/zebrajr/pytorch.git
synced 2025-12-07 12:21:27 +01:00
4cb534f92e
Summary:
This is an automatic change generated by the following script:
```
#!/usr/bin/env python3
from subprocess import check_output, check_call
import os
def get_compiled_files_list():
import json
with open("build/compile_commands.json") as f:
data = json.load(f)
files = [os.path.relpath(node['file']) for node in data]
for idx, fname in enumerate(files):
if fname.startswith('build/') and fname.endswith('.DEFAULT.cpp'):
files[idx] = fname[len('build/'):-len('.DEFAULT.cpp')]
return files
def run_clang_tidy(fname):
check_call(["python3", "tools/clang_tidy.py", "-c", "build", "-x", fname,"-s"])
changes = check_output(["git", "ls-files", "-m"])
if len(changes) == 0:
return
check_call(["git", "commit","--all", "-m", f"NOLINT stubs for {fname}"])
def main():
git_files = check_output(["git", "ls-files"]).decode("ascii").split("\n")
compiled_files = get_compiled_files_list()
for idx, fname in enumerate(git_files):
if fname not in compiled_files:
continue
if fname.startswith("caffe2/contrib/aten/"):
continue
print(f"[{idx}/{len(git_files)}] Processing {fname}")
run_clang_tidy(fname)
if __name__ == "__main__":
main()
```
Pull Request resolved: https://github.com/pytorch/pytorch/pull/56892
Reviewed By: H-Huang
Differential Revision: D27991944
Pulled By: malfet
fbshipit-source-id: 5415e1eb2c1b34319a4f03024bfaa087007d7179
159 lines
6.0 KiB
C++
159 lines
6.0 KiB
C++
#include <gtest/gtest.h>
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#include <torch/torch.h>
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#include <test/cpp/api/support.h>
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// Naive DFT of a 1 dimensional tensor
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torch::Tensor naive_dft(torch::Tensor x, bool forward=true) {
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TORCH_INTERNAL_ASSERT(x.dim() == 1);
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x = x.contiguous();
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auto out_tensor = torch::zeros_like(x);
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const int64_t len = x.size(0);
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// Roots of unity, exp(-2*pi*j*n/N) for n in [0, N), reversed for inverse transform
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std::vector<c10::complex<double>> roots(len);
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const auto angle_base = (forward ? -2.0 : 2.0) * M_PI / len;
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for (int64_t i = 0; i < len; ++i) {
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auto angle = i * angle_base;
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roots[i] = c10::complex<double>(std::cos(angle), std::sin(angle));
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}
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const auto in = x.data_ptr<c10::complex<double>>();
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const auto out = out_tensor.data_ptr<c10::complex<double>>();
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for (int64_t i = 0; i < len; ++i) {
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for (int64_t j = 0; j < len; ++j) {
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out[i] += roots[(j * i) % len] * in[j];
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}
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}
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return out_tensor;
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}
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// NOTE: Visual Studio and ROCm builds don't understand complex literals
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// as of August 2020
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// NOLINTNEXTLINE(cppcoreguidelines-avoid-non-const-global-variables)
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TEST(FFTTest, fft) {
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// NOLINTNEXTLINE(cppcoreguidelines-avoid-magic-numbers)
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auto t = torch::randn(128, torch::kComplexDouble);
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auto actual = torch::fft::fft(t);
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auto expect = naive_dft(t);
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ASSERT_TRUE(torch::allclose(actual, expect));
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}
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// NOLINTNEXTLINE(cppcoreguidelines-avoid-non-const-global-variables)
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TEST(FFTTest, fft_real) {
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// NOLINTNEXTLINE(cppcoreguidelines-avoid-magic-numbers)
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auto t = torch::randn(128, torch::kDouble);
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auto actual = torch::fft::fft(t);
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auto expect = torch::fft::fft(t.to(torch::kComplexDouble));
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ASSERT_TRUE(torch::allclose(actual, expect));
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}
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// NOLINTNEXTLINE(cppcoreguidelines-avoid-non-const-global-variables)
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TEST(FFTTest, fft_pad) {
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// NOLINTNEXTLINE(cppcoreguidelines-avoid-magic-numbers)
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auto t = torch::randn(128, torch::kComplexDouble);
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// NOLINTNEXTLINE(cppcoreguidelines-avoid-magic-numbers)
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auto actual = torch::fft::fft(t, 200);
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// NOLINTNEXTLINE(cppcoreguidelines-avoid-magic-numbers)
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auto expect = torch::fft::fft(torch::constant_pad_nd(t, {0, 72}));
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ASSERT_TRUE(torch::allclose(actual, expect));
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// NOLINTNEXTLINE(cppcoreguidelines-avoid-magic-numbers)
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actual = torch::fft::fft(t, 64);
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// NOLINTNEXTLINE(cppcoreguidelines-avoid-magic-numbers)
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expect = torch::fft::fft(torch::constant_pad_nd(t, {0, -64}));
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ASSERT_TRUE(torch::allclose(actual, expect));
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}
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// NOLINTNEXTLINE(cppcoreguidelines-avoid-non-const-global-variables)
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TEST(FFTTest, fft_norm) {
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// NOLINTNEXTLINE(cppcoreguidelines-avoid-magic-numbers)
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auto t = torch::randn(128, torch::kComplexDouble);
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// NOLINTNEXTLINE(bugprone-argument-comment)
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auto unnorm = torch::fft::fft(t, /*n=*/{}, /*axis=*/-1, /*norm=*/{});
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// NOLINTNEXTLINE(bugprone-argument-comment)
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auto norm = torch::fft::fft(t, /*n=*/{}, /*axis=*/-1, /*norm=*/"forward");
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ASSERT_TRUE(torch::allclose(unnorm / 128, norm));
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// NOLINTNEXTLINE(bugprone-argument-comment)
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auto ortho_norm = torch::fft::fft(t, /*n=*/{}, /*axis=*/-1, /*norm=*/"ortho");
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ASSERT_TRUE(torch::allclose(unnorm / std::sqrt(128), ortho_norm));
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}
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// NOLINTNEXTLINE(cppcoreguidelines-avoid-non-const-global-variables)
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TEST(FFTTest, ifft) {
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// NOLINTNEXTLINE(cppcoreguidelines-avoid-magic-numbers)
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auto T = torch::randn(128, torch::kComplexDouble);
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auto actual = torch::fft::ifft(T);
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// NOLINTNEXTLINE(cppcoreguidelines-avoid-magic-numbers)
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auto expect = naive_dft(T, /*forward=*/false) / 128;
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ASSERT_TRUE(torch::allclose(actual, expect));
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}
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// NOLINTNEXTLINE(cppcoreguidelines-avoid-non-const-global-variables)
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TEST(FFTTest, fft_ifft) {
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// NOLINTNEXTLINE(cppcoreguidelines-avoid-magic-numbers)
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auto t = torch::randn(77, torch::kComplexDouble);
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auto T = torch::fft::fft(t);
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ASSERT_EQ(T.size(0), 77);
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ASSERT_EQ(T.scalar_type(), torch::kComplexDouble);
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auto t_round_trip = torch::fft::ifft(T);
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ASSERT_EQ(t_round_trip.size(0), 77);
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ASSERT_EQ(t_round_trip.scalar_type(), torch::kComplexDouble);
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ASSERT_TRUE(torch::allclose(t, t_round_trip));
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}
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// NOLINTNEXTLINE(cppcoreguidelines-avoid-non-const-global-variables)
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TEST(FFTTest, rfft) {
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// NOLINTNEXTLINE(cppcoreguidelines-avoid-magic-numbers)
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auto t = torch::randn(129, torch::kDouble);
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auto actual = torch::fft::rfft(t);
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// NOLINTNEXTLINE(cppcoreguidelines-avoid-magic-numbers)
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auto expect = torch::fft::fft(t.to(torch::kComplexDouble)).slice(0, 0, 65);
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ASSERT_TRUE(torch::allclose(actual, expect));
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}
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// NOLINTNEXTLINE(cppcoreguidelines-avoid-non-const-global-variables)
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TEST(FFTTest, rfft_irfft) {
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// NOLINTNEXTLINE(cppcoreguidelines-avoid-magic-numbers)
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auto t = torch::randn(128, torch::kDouble);
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auto T = torch::fft::rfft(t);
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ASSERT_EQ(T.size(0), 65);
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ASSERT_EQ(T.scalar_type(), torch::kComplexDouble);
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auto t_round_trip = torch::fft::irfft(T);
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ASSERT_EQ(t_round_trip.size(0), 128);
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ASSERT_EQ(t_round_trip.scalar_type(), torch::kDouble);
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ASSERT_TRUE(torch::allclose(t, t_round_trip));
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}
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// NOLINTNEXTLINE(cppcoreguidelines-avoid-non-const-global-variables)
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TEST(FFTTest, ihfft) {
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// NOLINTNEXTLINE(cppcoreguidelines-avoid-magic-numbers)
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auto T = torch::randn(129, torch::kDouble);
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auto actual = torch::fft::ihfft(T);
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// NOLINTNEXTLINE(cppcoreguidelines-avoid-magic-numbers)
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auto expect = torch::fft::ifft(T.to(torch::kComplexDouble)).slice(0, 0, 65);
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ASSERT_TRUE(torch::allclose(actual, expect));
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}
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// NOLINTNEXTLINE(cppcoreguidelines-avoid-non-const-global-variables)
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TEST(FFTTest, hfft_ihfft) {
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// NOLINTNEXTLINE(cppcoreguidelines-avoid-magic-numbers)
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auto t = torch::randn(64, torch::kComplexDouble);
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// NOLINTNEXTLINE(cppcoreguidelines-avoid-magic-numbers)
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t[0] = .5; // Must be purely real to satisfy hermitian symmetry
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// NOLINTNEXTLINE(cppcoreguidelines-avoid-magic-numbers)
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auto T = torch::fft::hfft(t, 127);
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ASSERT_EQ(T.size(0), 127);
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ASSERT_EQ(T.scalar_type(), torch::kDouble);
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auto t_round_trip = torch::fft::ihfft(T);
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ASSERT_EQ(t_round_trip.size(0), 64);
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ASSERT_EQ(t_round_trip.scalar_type(), torch::kComplexDouble);
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ASSERT_TRUE(torch::allclose(t, t_round_trip));
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}
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