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[hotfix] modify tensor split unit tests
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This pull request addresses issues in the split unit test cases that had incorrect tensor initialization.

1. Build test: [X]Passed [ ]Failed [ ]Skipped
2. Run test:   [X]Passed [ ]Failed [ ]Skipped

Signed-off-by: Donghyeon Jeong <[email protected]>
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@djeong20
djeong20 committed Jan 24, 2025
1 parent 091c496 commit 0b0144f
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Showing 4 changed files with 127 additions and 110 deletions.
6 changes: 2 additions & 4 deletions nntrainer/tensor/float_tensor.cpp
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Original file line number Diff line number Diff line change
Expand Up @@ -954,7 +954,7 @@ std::vector<Tensor> FloatTensor::split(std::vector<size_t> sizes, int axis) {
<< dim.getTensorDim(axis) << " total size: " << total_size;

std::vector<TensorDim> ret_dims;
ret_dims.reserve(num_size);
ret_dims.resize(num_size);
for (unsigned int i = 0; i < num_size; ++i) {
ret_dims[i] = dim;
ret_dims[i].setTensorDim(axis, sizes[i]);
Expand All @@ -980,8 +980,6 @@ std::vector<Tensor> FloatTensor::split(std::vector<size_t> sizes, int axis) {
return value;
};

ret.reserve(num_size);

unsigned int accumulated_size = 0;
for (unsigned int i = 0; i < num_size; ++i) {
std::array<size_t, 4> loc = {0, 0, 0, 0};
Expand All @@ -998,7 +996,7 @@ std::vector<Tensor> FloatTensor::split(std::vector<size_t> sizes, int axis) {
}
}

ret.emplace_back(ret_dims[i]);
ret.push_back(Tensor(ret_dims[i]));
auto &ret_t = ret.back();

std::array<size_t, 4> end_loc;
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2 changes: 1 addition & 1 deletion nntrainer/tensor/half_tensor.cpp
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Original file line number Diff line number Diff line change
Expand Up @@ -796,7 +796,7 @@ std::vector<Tensor> HalfTensor::split(std::vector<size_t> sizes, int axis) {
}
}

ret.emplace_back(ret_dims[i]);
ret.emplace_back(Tensor(ret_dims[i]));
auto &ret_t = ret.back();

std::array<size_t, 4> end_loc;
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105 changes: 62 additions & 43 deletions test/unittest/unittest_nntrainer_tensor.cpp
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Original file line number Diff line number Diff line change
Expand Up @@ -4345,42 +4345,44 @@ TEST(nntrainer_Tensor, split_01_p) {
nntrainer::TensorDim ref_dim(3, 2, 4, 5);
nntrainer::Tensor t = ranged(3, 2, 4, 5);
std::vector<nntrainer::Tensor> answer;
answer.reserve(3);
{
float answer_data[] = {0, 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};
answer.emplace_back(ml::train::TensorDim{1, 2, 4, 5}, answer_data);
answer.push_back(
nntrainer::Tensor(ml::train::TensorDim{1, 2, 4, 5}, answer_data));
}
{
float answer_data[] = {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};
answer.emplace_back(ml::train::TensorDim{1, 2, 4, 5}, answer_data);
answer.push_back(
nntrainer::Tensor(ml::train::TensorDim{1, 2, 4, 5}, answer_data));
}
{
float answer_data[] = {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, 105, 106, 107, 108, 109,
110, 111, 112, 113, 114, 115, 116, 117, 118, 119};
answer.emplace_back(ml::train::TensorDim{1, 2, 4, 5}, answer_data);
answer.push_back(
nntrainer::Tensor(ml::train::TensorDim{1, 2, 4, 5}, answer_data));
}
EXPECT_EQ(t.split(3, 0), answer);
}
{
nntrainer::TensorDim ref_dim(3, 2, 4, 5);
nntrainer::Tensor t = ranged(3, 2, 4, 5);
std::vector<nntrainer::Tensor> answer;
answer.reserve(2);
{
float answer_data[] = {0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11,
12, 13, 14, 15, 16, 17, 18, 19, 40, 41, 42, 43,
44, 45, 46, 47, 48, 49, 50, 51, 52, 53, 54, 55,
56, 57, 58, 59, 80, 81, 82, 83, 84, 85, 86, 87,
88, 89, 90, 91, 92, 93, 94, 95, 96, 97, 98, 99};
answer.emplace_back(ml::train::TensorDim{3, 1, 4, 5}, answer_data);
answer.push_back(
nntrainer::Tensor(ml::train::TensorDim{3, 1, 4, 5}, answer_data));
}
{
float answer_data[] = {20, 21, 22, 23, 24, 25, 26, 27, 28, 29,
Expand All @@ -4389,82 +4391,89 @@ TEST(nntrainer_Tensor, split_01_p) {
70, 71, 72, 73, 74, 75, 76, 77, 78, 79,
100, 101, 102, 103, 104, 105, 106, 107, 108, 109,
110, 111, 112, 113, 114, 115, 116, 117, 118, 119};
answer.emplace_back(ml::train::TensorDim{3, 1, 4, 5}, answer_data);
answer.push_back(
nntrainer::Tensor(ml::train::TensorDim{3, 1, 4, 5}, answer_data));
}
EXPECT_EQ(t.split(2, 1), answer);
}
{
nntrainer::TensorDim ref_dim(3, 2, 4, 5);
nntrainer::Tensor t = ranged(3, 2, 4, 5);
std::vector<nntrainer::Tensor> answer;
answer.reserve(2);
{
float answer_data[] = {
0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 20, 21, 22, 23, 24,
25, 26, 27, 28, 29, 40, 41, 42, 43, 44, 45, 46, 47, 48, 49,
60, 61, 62, 63, 64, 65, 66, 67, 68, 69, 80, 81, 82, 83, 84,
85, 86, 87, 88, 89, 100, 101, 102, 103, 104, 105, 106, 107, 108, 109};
answer.emplace_back(ml::train::TensorDim{3, 2, 2, 5}, answer_data);
answer.push_back(
nntrainer::Tensor(ml::train::TensorDim{3, 2, 2, 5}, answer_data));
}
{
float answer_data[] = {
10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 30, 31, 32, 33, 34,
35, 36, 37, 38, 39, 50, 51, 52, 53, 54, 55, 56, 57, 58, 59,
70, 71, 72, 73, 74, 75, 76, 77, 78, 79, 90, 91, 92, 93, 94,
95, 96, 97, 98, 99, 110, 111, 112, 113, 114, 115, 116, 117, 118, 119};
answer.emplace_back(ml::train::TensorDim{3, 2, 2, 5}, answer_data);
answer.push_back(
nntrainer::Tensor(ml::train::TensorDim{3, 2, 2, 5}, answer_data));
}
EXPECT_EQ(t.split(2, 2), answer);
}
{
nntrainer::TensorDim ref_dim(3, 2, 4, 5);
nntrainer::Tensor t = ranged(3, 2, 4, 5);
std::vector<nntrainer::Tensor> answer;
answer.reserve(5);
{
float answer_data[] = {0, 5, 10, 15, 20, 25, 30, 35,
40, 45, 50, 55, 60, 65, 70, 75,
80, 85, 90, 95, 100, 105, 110, 115};
answer.emplace_back(ml::train::TensorDim{3, 2, 4, 1}, answer_data);
answer.push_back(
nntrainer::Tensor(ml::train::TensorDim{3, 2, 4, 1}, answer_data));
}
{
float answer_data[] = {1, 6, 11, 16, 21, 26, 31, 36,
41, 46, 51, 56, 61, 66, 71, 76,
81, 86, 91, 96, 101, 106, 111, 116};
answer.emplace_back(ml::train::TensorDim{3, 2, 4, 1}, answer_data);
answer.push_back(
nntrainer::Tensor(ml::train::TensorDim{3, 2, 4, 1}, answer_data));
}
{
float answer_data[] = {2, 7, 12, 17, 22, 27, 32, 37,
42, 47, 52, 57, 62, 67, 72, 77,
82, 87, 92, 97, 102, 107, 112, 117};
answer.emplace_back(ml::train::TensorDim{3, 2, 4, 1}, answer_data);
answer.push_back(
nntrainer::Tensor(ml::train::TensorDim{3, 2, 4, 1}, answer_data));
}
{
float answer_data[] = {3, 8, 13, 18, 23, 28, 33, 38,
43, 48, 53, 58, 63, 68, 73, 78,
83, 88, 93, 98, 103, 108, 113, 118};
answer.emplace_back(ml::train::TensorDim{3, 2, 4, 1}, answer_data);
answer.push_back(
nntrainer::Tensor(ml::train::TensorDim{3, 2, 4, 1}, answer_data));
}
{
float answer_data[] = {4, 9, 14, 19, 24, 29, 34, 39,
44, 49, 54, 59, 64, 69, 74, 79,
84, 89, 94, 99, 104, 109, 114, 119};
answer.emplace_back(ml::train::TensorDim{3, 2, 4, 1}, answer_data);
answer.push_back(
nntrainer::Tensor(ml::train::TensorDim{3, 2, 4, 1}, answer_data));
}
EXPECT_EQ(t.split(5, 3), answer);
}
{
nntrainer::TensorDim ref_dim(1, 1, 4, 6);
nntrainer::Tensor t = ranged(1, 1, 4, 6);
std::vector<nntrainer::Tensor> answer;
answer.reserve(2);
{
float answer_data[] = {0, 1, 2, 6, 7, 8, 12, 13, 14, 18, 19, 20};
answer.emplace_back(ml::train::TensorDim{1, 1, 4, 3}, answer_data);
answer.push_back(
nntrainer::Tensor(ml::train::TensorDim{1, 1, 4, 3}, answer_data));
}
{
float answer_data[] = {3, 4, 5, 9, 10, 11, 15, 16, 17, 21, 22, 23};
answer.emplace_back(ml::train::TensorDim{1, 1, 4, 3}, answer_data);
answer.push_back(
nntrainer::Tensor(ml::train::TensorDim{1, 1, 4, 3}, answer_data));
}
EXPECT_EQ(t.split(2, 3), answer);
}
Expand All @@ -4485,37 +4494,38 @@ TEST(nntrainer_Tensor, split_04_p) {
nntrainer::TensorDim ref_dim(3, 2, 4, 5);
nntrainer::Tensor t = ranged(3, 2, 4, 5);
std::vector<nntrainer::Tensor> answer;
answer.reserve(2);
{
float answer_data[] = {
0, 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};
answer.emplace_back(ml::train::TensorDim{2, 2, 4, 5}, answer_data);
answer.push_back(
nntrainer::Tensor(ml::train::TensorDim{2, 2, 4, 5}, answer_data));
}
{
float answer_data[] = {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, 105, 106, 107, 108, 109,
110, 111, 112, 113, 114, 115, 116, 117, 118, 119};
answer.emplace_back(ml::train::TensorDim{1, 2, 4, 5}, answer_data);
answer.push_back(
nntrainer::Tensor(ml::train::TensorDim{1, 2, 4, 5}, answer_data));
}
EXPECT_EQ(t.split({2, 1}, 0), answer);
}
{
nntrainer::TensorDim ref_dim(3, 2, 4, 5);
nntrainer::Tensor t = ranged(3, 2, 4, 5);
std::vector<nntrainer::Tensor> answer;
answer.reserve(2);
{
float answer_data[] = {0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11,
12, 13, 14, 15, 16, 17, 18, 19, 40, 41, 42, 43,
44, 45, 46, 47, 48, 49, 50, 51, 52, 53, 54, 55,
56, 57, 58, 59, 80, 81, 82, 83, 84, 85, 86, 87,
88, 89, 90, 91, 92, 93, 94, 95, 96, 97, 98, 99};
answer.emplace_back(ml::train::TensorDim{3, 1, 4, 5}, answer_data);
answer.push_back(
nntrainer::Tensor(ml::train::TensorDim{3, 1, 4, 5}, answer_data));
}
{
float answer_data[] = {20, 21, 22, 23, 24, 25, 26, 27, 28, 29,
Expand All @@ -4524,43 +4534,45 @@ TEST(nntrainer_Tensor, split_04_p) {
70, 71, 72, 73, 74, 75, 76, 77, 78, 79,
100, 101, 102, 103, 104, 105, 106, 107, 108, 109,
110, 111, 112, 113, 114, 115, 116, 117, 118, 119};
answer.emplace_back(ml::train::TensorDim{3, 1, 4, 5}, answer_data);
answer.push_back(
nntrainer::Tensor(ml::train::TensorDim{3, 1, 4, 5}, answer_data));
}
EXPECT_EQ(t.split({1, 1}, 1), answer);
}
{
nntrainer::TensorDim ref_dim(3, 2, 4, 5);
nntrainer::Tensor t = ranged(3, 2, 4, 5);
std::vector<nntrainer::Tensor> answer;
answer.reserve(2);
{
float answer_data[] = {
0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 20, 21, 22, 23, 24,
25, 26, 27, 28, 29, 40, 41, 42, 43, 44, 45, 46, 47, 48, 49,
60, 61, 62, 63, 64, 65, 66, 67, 68, 69, 80, 81, 82, 83, 84,
85, 86, 87, 88, 89, 100, 101, 102, 103, 104, 105, 106, 107, 108, 109};
answer.emplace_back(ml::train::TensorDim{3, 2, 2, 5}, answer_data);
answer.push_back(
nntrainer::Tensor(ml::train::TensorDim{3, 2, 2, 5}, answer_data));
}
{
float answer_data[] = {
10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 30, 31, 32, 33, 34,
35, 36, 37, 38, 39, 50, 51, 52, 53, 54, 55, 56, 57, 58, 59,
70, 71, 72, 73, 74, 75, 76, 77, 78, 79, 90, 91, 92, 93, 94,
95, 96, 97, 98, 99, 110, 111, 112, 113, 114, 115, 116, 117, 118, 119};
answer.emplace_back(ml::train::TensorDim{3, 2, 2, 5}, answer_data);
answer.push_back(
nntrainer::Tensor(ml::train::TensorDim{3, 2, 2, 5}, answer_data));
}
EXPECT_EQ(t.split({2, 2}, 2), answer);
}
{
nntrainer::TensorDim ref_dim(3, 2, 4, 5);
nntrainer::Tensor t = ranged(3, 2, 4, 5);
std::vector<nntrainer::Tensor> answer;
answer.reserve(3);
{
float answer_data[] = {0, 5, 10, 15, 20, 25, 30, 35,
40, 45, 50, 55, 60, 65, 70, 75,
80, 85, 90, 95, 100, 105, 110, 115};
answer.emplace_back(ml::train::TensorDim{3, 2, 4, 1}, answer_data);
answer.push_back(
nntrainer::Tensor(ml::train::TensorDim{3, 2, 4, 1}, answer_data));
}
{
float answer_data[] = {
Expand All @@ -4569,54 +4581,58 @@ TEST(nntrainer_Tensor, split_04_p) {
51, 52, 53, 56, 57, 58, 61, 62, 63, 66, 67, 68, 71, 72, 73,
76, 77, 78, 81, 82, 83, 86, 87, 88, 91, 92, 93, 96, 97, 98,
101, 102, 103, 106, 107, 108, 111, 112, 113, 116, 117, 118};
answer.emplace_back(ml::train::TensorDim{3, 2, 4, 3}, answer_data);
answer.push_back(
nntrainer::Tensor(ml::train::TensorDim{3, 2, 4, 3}, answer_data));
}
{
float answer_data[] = {4, 9, 14, 19, 24, 29, 34, 39,
44, 49, 54, 59, 64, 69, 74, 79,
84, 89, 94, 99, 104, 109, 114, 119};
answer.emplace_back(ml::train::TensorDim{3, 2, 4, 1}, answer_data);
answer.push_back(
nntrainer::Tensor(ml::train::TensorDim{3, 2, 4, 1}, answer_data));
}
EXPECT_EQ(t.split({1, 3, 1}, 3), answer);
}
{
nntrainer::TensorDim ref_dim(3, 2, 4, 5);
nntrainer::Tensor t = ranged(3, 2, 4, 5);
std::vector<nntrainer::Tensor> answer;
answer.reserve(3);
{
float answer_data[] = {
0, 1, 5, 6, 10, 11, 15, 16, 20, 21, 25, 26, 30, 31, 35, 36,
40, 41, 45, 46, 50, 51, 55, 56, 60, 61, 65, 66, 70, 71, 75, 76,
80, 81, 85, 86, 90, 91, 95, 96, 100, 101, 105, 106, 110, 111, 115, 116};
answer.emplace_back(ml::train::TensorDim{3, 2, 4, 2}, answer_data);
answer.push_back(
nntrainer::Tensor(ml::train::TensorDim{3, 2, 4, 2}, answer_data));
}
{
float answer_data[] = {
2, 3, 7, 8, 12, 13, 17, 18, 22, 23, 27, 28, 32, 33, 37, 38,
42, 43, 47, 48, 52, 53, 57, 58, 62, 63, 67, 68, 72, 73, 77, 78,
82, 83, 87, 88, 92, 93, 97, 98, 102, 103, 107, 108, 112, 113, 117, 118};
answer.emplace_back(ml::train::TensorDim{3, 2, 4, 2}, answer_data);
answer.push_back(
nntrainer::Tensor(ml::train::TensorDim{3, 2, 4, 2}, answer_data));
}
{
float answer_data[] = {4, 9, 14, 19, 24, 29, 34, 39,
44, 49, 54, 59, 64, 69, 74, 79,
84, 89, 94, 99, 104, 109, 114, 119};
answer.emplace_back(ml::train::TensorDim{3, 2, 4, 1}, answer_data);
answer.push_back(
nntrainer::Tensor(ml::train::TensorDim{3, 2, 4, 1}, answer_data));
}
EXPECT_EQ(t.split({2, 2, 1}, 3), answer);
}
{
nntrainer::TensorDim ref_dim(3, 2, 4, 5);
nntrainer::Tensor t = ranged(3, 2, 4, 5);
std::vector<nntrainer::Tensor> answer;
answer.reserve(2);
{
float answer_data[] = {
0, 1, 5, 6, 10, 11, 15, 16, 20, 21, 25, 26, 30, 31, 35, 36,
40, 41, 45, 46, 50, 51, 55, 56, 60, 61, 65, 66, 70, 71, 75, 76,
80, 81, 85, 86, 90, 91, 95, 96, 100, 101, 105, 106, 110, 111, 115, 116};
answer.emplace_back(ml::train::TensorDim{3, 2, 4, 2}, answer_data);
answer.push_back(
nntrainer::Tensor(ml::train::TensorDim{3, 2, 4, 2}, answer_data));
}
{
float answer_data[] = {
Expand All @@ -4625,26 +4641,29 @@ TEST(nntrainer_Tensor, split_04_p) {
52, 53, 54, 57, 58, 59, 62, 63, 64, 67, 68, 69, 72, 73, 74,
77, 78, 79, 82, 83, 84, 87, 88, 89, 92, 93, 94, 97, 98, 99,
102, 103, 104, 107, 108, 109, 112, 113, 114, 117, 118, 119};
answer.emplace_back(ml::train::TensorDim{3, 2, 4, 3}, answer_data);
answer.push_back(
nntrainer::Tensor(ml::train::TensorDim{3, 2, 4, 3}, answer_data));
}
EXPECT_EQ(t.split({2, 3}, 3), answer);
}
{
nntrainer::TensorDim ref_dim(1, 1, 4, 6);
nntrainer::Tensor t = ranged(1, 1, 4, 6);
std::vector<nntrainer::Tensor> answer;
answer.reserve(3);
{
float answer_data[] = {0, 6, 12, 18};
answer.emplace_back(ml::train::TensorDim{1, 1, 4, 1}, answer_data);
answer.push_back(
nntrainer::Tensor(ml::train::TensorDim{1, 1, 4, 1}, answer_data));
}
{
float answer_data[] = {1, 2, 3, 7, 8, 9, 13, 14, 15, 19, 20, 21};
answer.emplace_back(ml::train::TensorDim{1, 1, 4, 3}, answer_data);
answer.push_back(
nntrainer::Tensor(ml::train::TensorDim{1, 1, 4, 3}, answer_data));
}
{
float answer_data[] = {4, 5, 10, 11, 16, 17, 22, 23};
answer.emplace_back(ml::train::TensorDim{1, 1, 4, 2}, answer_data);
answer.push_back(
nntrainer::Tensor(ml::train::TensorDim{1, 1, 4, 2}, answer_data));
}
EXPECT_EQ(t.split({1, 3, 2}, 3), answer);
}
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