IntenseWebs/openvino
3
0
Fork 0
Code Issues Pull Requests Packages Projects Releases Wiki Activity

[IE CLDNN] Fix reduce accumulate issue in unittest. (#4448)

Browse Source
This commit is contained in:
hyunback kim 2021-02-27 00:53:54 +09:00 committed by GitHub
parent a1ef9498a3
commit d72c20528e
No known key found for this signature in database
GPG Key ID: 4AEE18F83AFDEB23
1 changed files with 28 additions and 10 deletions
Show Stats Download Patch File Download Diff File Expand all files Collapse all files

38
inference-engine/thirdparty/clDNN/tests/test_cases/reduce_gpu_test.cpp vendored
View File

@ -75,7 +75,7 @@ struct reduce_accumulator {
return acc;
};
AccT accumulate(AccT& acc, AccT& input_val, cldnn::reduce_mode reduce_mode) {
AccT accumulate(AccT& acc, AccT& input_val, cldnn::reduce_mode reduce_mode, bool sum_only) {
if (reduce_mode == cldnn::reduce_mode::sum || reduce_mode == cldnn::reduce_mode::mean ||
reduce_mode == cldnn::reduce_mode::log_sum)
acc += input_val;
@ -89,14 +89,26 @@ struct reduce_accumulator {
acc = acc && input_val;
else if (reduce_mode == cldnn::reduce_mode::logical_or)
acc = acc || input_val;
else if (reduce_mode == cldnn::reduce_mode::sum_square)
acc += input_val * input_val;
else if (reduce_mode == cldnn::reduce_mode::sum_square) {
if (sum_only)
acc += input_val;
else
acc += input_val * input_val;
}
else if (reduce_mode == cldnn::reduce_mode::l1)
acc += abs(input_val);
else if (reduce_mode == cldnn::reduce_mode::l2)
acc += input_val * input_val;
else if (reduce_mode == cldnn::reduce_mode::log_sum_exp)
acc += exp(input_val);
else if (reduce_mode == cldnn::reduce_mode::l2) {
if (sum_only)
acc += input_val;
else
acc += input_val * input_val;
}
else if (reduce_mode == cldnn::reduce_mode::log_sum_exp) {
if (sum_only)
acc += input_val;
else
acc += exp(input_val);
}
return acc;
};
@ -287,10 +299,10 @@ VVVVVVF<OutputT> reference_reduce(VVVVVVF<InputT>& input,
temp_output[bi % out_dims[0]][fi % out_dims[1]]
[wi % out_dims[2]][zi % out_dims[3]]
[yi % out_dims[4]][xi % out_dims[5]] = reduce.accumulate(acc, input_val, reduce_mode);
[yi % out_dims[4]][xi % out_dims[5]] = reduce.accumulate(acc, input_val, reduce_mode, &axis != &reduce_axis.front());
}
}
if (&axis == &reduce_axis.back() || reduce_mode != cldnn::reduce_mode::mean)
if (&axis == &reduce_axis.back())
if (reduce_mode == cldnn::reduce_mode::mean || reduce_mode == cldnn::reduce_mode::l2 ||
reduce_mode == cldnn::reduce_mode::log_sum || reduce_mode == cldnn::reduce_mode::log_sum_exp) {
for (size_t bi = 0; bi < temp_output.size(); ++bi)
@ -647,7 +659,13 @@ INSTANTIATE_TEST_CASE_P(reduce_gpu_b_fs_yx_fsv16_i8_i8,
TestParamType_general_reduce_gpu(16, 16, 1, 1, 15, 8, format::b_fs_yx_fsv16, reduce_mode::log_sum, {reduce::along_b}, "reduce_gpu_b_fs_yx_fsv16", true, data_types::f32, false, data_types::f32),
TestParamType_general_reduce_gpu(17, 34, 1, 1, 14, 11, format::b_fs_yx_fsv16, reduce_mode::l2, {reduce::along_f}, "reduce_gpu_b_fs_yx_fsv16", true, data_types::f32, false, data_types::f32),
TestParamType_general_reduce_gpu(16, 16, 1, 1, 12, 8, format::b_fs_yx_fsv16, reduce_mode::sum_square, {reduce::along_y}, "reduce_gpu_b_fs_yx_fsv16", true, data_types::f32, false, data_types::f32),
TestParamType_general_reduce_gpu(17, 34, 1, 1, 12, 11, format::b_fs_yx_fsv16, reduce_mode::log_sum, {reduce::along_x}, "reduce_gpu_b_fs_yx_fsv16", true, data_types::f32, false, data_types::f32)
TestParamType_general_reduce_gpu(17, 34, 1, 1, 12, 11, format::b_fs_yx_fsv16, reduce_mode::log_sum, {reduce::along_x}, "reduce_gpu_b_fs_yx_fsv16", true, data_types::f32, false, data_types::f32),
TestParamType_general_reduce_gpu(1, 2, 1, 1, 12, 12, format::b_fs_yx_fsv16, reduce_mode::sum_square, {reduce::along_x, reduce::along_y}, "reduce_gpu_b_fs_yx_fsv16", true, data_types::f32, false, data_types::f32),
TestParamType_general_reduce_gpu(1, 2, 1, 1, 12, 12, format::b_fs_yx_fsv16, reduce_mode::sum_square, {reduce::along_f, reduce::along_x, reduce::along_y}, "reduce_gpu_b_fs_yx_fsv16", true, data_types::f32, false, data_types::f32),
TestParamType_general_reduce_gpu(1, 2, 1, 1, 12, 12, format::b_fs_yx_fsv16, reduce_mode::l2, {reduce::along_x, reduce::along_y}, "reduce_gpu_b_fs_yx_fsv16", true, data_types::f32, false, data_types::f32),
TestParamType_general_reduce_gpu(1, 2, 1, 1, 12, 12, format::b_fs_yx_fsv16, reduce_mode::log_sum, {reduce::along_x, reduce::along_y}, "reduce_gpu_b_fs_yx_fsv16", true, data_types::f32, false, data_types::f32),
TestParamType_general_reduce_gpu(1, 2, 1, 1, 12, 12, format::b_fs_yx_fsv16, reduce_mode::log_sum_exp, {reduce::along_x, reduce::along_y}, "reduce_gpu_b_fs_yx_fsv16", true, data_types::f32, false, data_types::f32)
),
general_reduce_gpu::PrintToStringParamName);