File: misc.cpp

package info (click to toggle)
pytorch 1.13.1%2Bdfsg-4
  • links: PTS, VCS
  • area: main
  • in suites: bookworm
  • size: 139,252 kB
  • sloc: cpp: 1,100,274; python: 706,454; ansic: 83,052; asm: 7,618; java: 3,273; sh: 2,841; javascript: 612; makefile: 323; xml: 269; ruby: 185; yacc: 144; objc: 68; lex: 44
file content (104 lines) | stat: -rw-r--r-- 2,472 bytes parent folder | download | duplicates (3)
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
77
78
79
80
81
82
83
84
85
86
87
88
89
90
91
92
93
94
95
96
97
98
99
100
101
102
103
104
#include <gtest/gtest.h>

#include <torch/torch.h>

#include <test/cpp/api/support.h>

#include <functional>

using namespace torch::test;

void torch_warn_once_A() {
  TORCH_WARN_ONCE("warn once");
}

void torch_warn_once_B() {
  TORCH_WARN_ONCE("warn something else once");
}

void torch_warn() {
  TORCH_WARN("warn multiple times");
}

TEST(UtilsTest, WarnOnce) {
  {
    WarningCapture warnings;

    torch_warn_once_A();
    torch_warn_once_A();
    torch_warn_once_B();
    torch_warn_once_B();

    ASSERT_EQ(count_substr_occurrences(warnings.str(), "warn once"), 1);
    ASSERT_EQ(
        count_substr_occurrences(warnings.str(), "warn something else once"),
        1);
  }
  {
    WarningCapture warnings;

    torch_warn();
    torch_warn();
    torch_warn();

    ASSERT_EQ(
        count_substr_occurrences(warnings.str(), "warn multiple times"), 3);
  }
}

TEST(NoGradTest, SetsGradModeCorrectly) {
  torch::manual_seed(0);
  torch::NoGradGuard guard;
  torch::nn::Linear model(5, 2);
  auto x = torch::randn({10, 5}, torch::requires_grad());
  auto y = model->forward(x);
  torch::Tensor s = y.sum();

  // Mimicking python API behavior:
  ASSERT_THROWS_WITH(
      s.backward(),
      "element 0 of tensors does not require grad and does not have a grad_fn")
}

struct AutogradTest : torch::test::SeedingFixture {
  AutogradTest() {
    x = torch::randn({3, 3}, torch::requires_grad());
    y = torch::randn({3, 3});
    z = x * y;
  }
  torch::Tensor x, y, z;
};

TEST_F(AutogradTest, CanTakeDerivatives) {
  z.backward(torch::ones_like(z));
  ASSERT_TRUE(x.grad().allclose(y));
}

TEST_F(AutogradTest, CanTakeDerivativesOfZeroDimTensors) {
  z.sum().backward();
  ASSERT_TRUE(x.grad().allclose(y));
}

TEST_F(AutogradTest, CanPassCustomGradientInputs) {
  z.sum().backward(torch::ones({}) * 2);
  ASSERT_TRUE(x.grad().allclose(y * 2));
}

TEST(UtilsTest, AmbiguousOperatorDefaults) {
  auto tmp = at::empty({}, at::kCPU);
  at::_test_ambiguous_defaults(tmp);
  at::_test_ambiguous_defaults(tmp, 1);
  at::_test_ambiguous_defaults(tmp, 1, 1);
  at::_test_ambiguous_defaults(tmp, 2, "2");
}

int64_t get_first_element(c10::OptionalIntArrayRef arr) {
  return arr.value()[0];
}

TEST(OptionalArrayRefTest, DanglingPointerFix) {
  // Ensure that the converting constructor of `OptionalArrayRef` does not
  // create a dangling pointer when given a single value
  ASSERT_TRUE(get_first_element(300) == 300);
  ASSERT_TRUE(get_first_element({400}) == 400);
}