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Fixed CumSum dnn layer #24353

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Merged
merged 4 commits into from
Oct 3, 2023
Merged

Fixed CumSum dnn layer #24353

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914fd8e
Fixed cumsum dnn layer
Oct 3, 2023
7865a09
returned reading axis from constant nodes
Oct 3, 2023
2118451
excluded new cumsum tests from cuda, halide and vulcan platforms
Oct 3, 2023
6da446d
removed trailing whitespaces
Oct 3, 2023
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103 changes: 53 additions & 50 deletions modules/dnn/src/layers/cumsum_layer.cpp
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Expand Up @@ -47,76 +47,79 @@ class CumSumLayerImpl CV_FINAL : public CumSumLayer
inputs_arr.getMatVector(inputs);
outputs_arr.getMatVector(outputs);

// Get x tensor.
const auto &src_mat = inputs[0];
const auto *src_ptr = src_mat.ptr<float>();
// Get input tensor.
const auto& src_mat = inputs[0];
const auto* src_ptr = src_mat.ptr<float>();

// Get axis.
const int axis = normalize_axis(axis_raw, src_mat.dims);
// Get target axis.
int axis = inputs.size() > 1 ? parseAxis(inputs[1]) : axis_raw;
axis = normalize_axis(axis, src_mat.dims);

// Get y tensor.
auto &dst_mat = outputs[0];
src_mat.copyTo(dst_mat);
auto *dst_ptr = dst_mat.ptr<float>();

// Get output tensor.
auto& dst_mat = outputs[0];
auto* dst_ptr = dst_mat.ptr<float>();

// Get flags.
const auto exclusive = exclusive_raw == 1;
const auto reverse = reverse_raw == 1;

// Get parameters to iterate outer dimension.
// Data with [dim_1, .. , dim_k-1, target_dim, dim_k+1, .. , dim_n]
// dimensions is represented here as [outer_dim, target_dim, inner_dim]
const size_t outer_size = src_mat.total(0, axis);
const size_t outer_step_length = src_mat.total(axis);

// Get parameters to iterate inner dimension.
const size_t inner_size = src_mat.size[axis];

if (!inner_size)
return;
const size_t target_size = src_mat.size[axis];
const size_t inner_size = src_mat.total(axis + 1);
const size_t outer_step_length = target_size * inner_size;

const size_t inner_step_length = src_mat.total(axis + 1);
const int inner_step = (reverse ? -1 : 1) * inner_step_length;
const int inner_start = reverse ? inner_size - 1 : 0;
const int inner_stop = reverse ? -1 : inner_size;
const int inner_delta = reverse ? -1 : 1;
// Calculating steps in target dimensions
const int target_start = reverse ? target_size - 1 : 0;
const int target_stop = reverse ? -1 : target_size;
const int target_delta = reverse ? -1 : 1;
const int target_step = target_delta * inner_size;

// Get parameters to populate channels.
const size_t num_channels = src_mat.total(axis + 1);
// If exclusive, the j-th output element would be the sum of the first (j-1) elements.
// Otherwise, it would be the sum of the first j elements.
const int exclusive_delta = exclusive ? target_step : 0;

for (size_t outer_dim = 0; outer_dim < outer_size; outer_dim++)
for (size_t outer_idx = 0; outer_idx < outer_size; outer_idx++)
{
const size_t outer_offset = outer_dim * outer_step_length;
size_t src_offset = outer_offset + inner_start * inner_step_length;

// Populate first element of inner dimension.
for (size_t channel = 0; channel < num_channels; channel++)
{
if (exclusive)
{
dst_ptr[src_offset + channel] = 0.0f;
}
else
{
dst_ptr[src_offset + channel] = src_ptr[src_offset + channel];
src_offset += inner_step;
}
}

// Populate remaining elements of inner dimension.
for (int inner_dim = inner_start + inner_delta; inner_dim != inner_stop; inner_dim += inner_delta)
const size_t target_offset = outer_idx * outer_step_length;

// Handle first element of target dimension.
size_t first_inner_offset = target_offset + target_start * inner_size;
if (exclusive)
for (size_t inner_idx = 0; inner_idx < inner_size; inner_idx++)
dst_ptr[first_inner_offset + inner_idx] = 0.0f;
else
for (size_t inner_idx = 0; inner_idx < inner_size; inner_idx++)
dst_ptr[first_inner_offset + inner_idx] = src_ptr[first_inner_offset + inner_idx];

// Handle remaining elements of target dimension.
for (int target_idx = target_start + target_delta; target_idx != target_stop; target_idx += target_delta)
{
const size_t dst_offset = outer_offset + inner_dim * inner_step_length;
const size_t inner_offset = target_offset + target_idx * inner_size;

for (size_t channel = 0; channel < num_channels; channel++)
for (size_t inner_idx = 0; inner_idx < inner_size; inner_idx++)
{
const size_t previous_dst_offset = dst_offset - inner_step;
dst_ptr[dst_offset + channel] = dst_ptr[previous_dst_offset + channel] +
src_ptr[src_offset + channel];
src_offset += inner_step;
dst_ptr[inner_offset + inner_idx] = dst_ptr[inner_offset - target_step + inner_idx] +
src_ptr[inner_offset - exclusive_delta + inner_idx];
}
}
}
}

int parseAxis(const Mat& axis_mat) {
CV_CheckEQ(axis_mat.total(), 1u, "Axis tensor should contain single value");
if (axis_mat.type() == CV_32SC1)
return axis_mat.at<int32_t>(0);
else
{
Mat axis_mat_int;
axis_mat.convertTo(axis_mat_int, CV_32SC1);
return axis_mat_int.at<int32_t>(0);
}
}

int axis_raw;
int exclusive_raw;
int reverse_raw;
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7 changes: 7 additions & 0 deletions modules/dnn/test/test_onnx_conformance_layer_filter__cuda_denylist.inl.hpp
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Original file line number Diff line number Diff line change
Expand Up @@ -46,6 +46,13 @@
"test_conv_with_strides_and_asymmetric_padding",
"test_conv_with_strides_no_padding",
"test_conv_with_strides_padding",
"test_cumsum_1d",
"test_cumsum_1d_exclusive",
"test_cumsum_1d_reverse",
"test_cumsum_1d_reverse_exclusive",
"test_cumsum_2d_axis_0",
"test_cumsum_2d_axis_1",
"test_cumsum_2d_negative_axis",
"test_div_bcast",
"test_div_uint8",
"test_dropout_default_ratio",
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7 changes: 7 additions & 0 deletions modules/dnn/test/test_onnx_conformance_layer_filter__halide_denylist.inl.hpp
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Original file line number Diff line number Diff line change
Expand Up @@ -45,6 +45,13 @@
"test_castlike_FLOAT_to_STRING_expanded",
"test_castlike_STRING_to_FLOAT_expanded",
"test_ceil",
"test_cumsum_1d",
"test_cumsum_1d_exclusive",
"test_cumsum_1d_reverse",
"test_cumsum_1d_reverse_exclusive",
"test_cumsum_2d_axis_0",
"test_cumsum_2d_axis_1",
"test_cumsum_2d_negative_axis",
"test_concat_1d_axis_negative_1",
"test_concat_3d_axis_1",
"test_div",
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7 changes: 7 additions & 0 deletions modules/dnn/test/test_onnx_conformance_layer_filter__vulkan_denylist.inl.hpp
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Original file line number Diff line number Diff line change
Expand Up @@ -40,6 +40,13 @@
"test_cast_STRING_to_FLOAT",
"test_castlike_FLOAT_to_STRING_expanded",
"test_castlike_STRING_to_FLOAT_expanded",
"test_cumsum_1d",
"test_cumsum_1d_exclusive",
"test_cumsum_1d_reverse",
"test_cumsum_1d_reverse_exclusive",
"test_cumsum_2d_axis_0",
"test_cumsum_2d_axis_1",
"test_cumsum_2d_negative_axis",
"test_concat_1d_axis_negative_1",
"test_div_uint8",
"test_flatten_axis0",
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7 changes: 0 additions & 7 deletions modules/dnn/test/test_onnx_conformance_layer_parser_denylist.inl.hpp
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Original file line number Diff line number Diff line change
Expand Up @@ -89,13 +89,6 @@
"test_convtranspose_pad",
"test_convtranspose_pads",
"test_convtranspose_with_kernel",
"test_cumsum_1d",
"test_cumsum_1d_exclusive",
"test_cumsum_1d_reverse",
"test_cumsum_1d_reverse_exclusive",
"test_cumsum_2d_axis_0",
"test_cumsum_2d_axis_1",
"test_cumsum_2d_negative_axis",
"test_dequantizelinear",
"test_dequantizelinear_axis",
"test_det_2d",
Expand Down