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Merge pull request #27710 from abhishek-gola:pow_layer_add

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Added Pow layer to new DNN engine #27710

### Pull Request Readiness Checklist

See details at https://github.com/opencv/opencv/wiki/How_to_contribute#making-a-good-pull-request

- [x] I agree to contribute to the project under Apache 2 License.
- [x] To the best of my knowledge, the proposed patch is not based on a code under GPL or another license that is incompatible with OpenCV
- [x] The PR is proposed to the proper branch
- [x] There is a reference to the original bug report and related work
- [x] There is accuracy test, performance test and test data in opencv_extra repository, if applicable
      Patch to opencv_extra has the same branch name.
- [x] The feature is well documented and sample code can be built with the project CMake
This commit is contained in:
Abhishek Gola
2025-09-10 00:46:08 +05:30
committed by GitHub
parent 8562b15924
commit 83b771f379
4 changed files with 88 additions and 47 deletions
Download Patch File Download Diff File Expand all files Collapse all files
modules/dnn/src/layers/nary_eltwise_layers.cpp
+50 -9
View File
@@ -33,6 +33,7 @@ static int _mod(int x, int y) {
}
return res;
}
}
class NaryEltwiseHelper CV_FINAL
@@ -361,12 +362,33 @@ public:
}
if (op == OPERATION::POW) {
/*
First input: exponent of Type T;
Second input: power of the exponent of Type T1;
Output: same type T as first input's.
*/
outputs.assign(1, inputs.front());
CV_Assert(inputs.size() == 2);
auto isIntegerType = [](int t) {
return t == CV_8S || t == CV_8U || t == CV_16S || t == CV_16U || t == CV_32S || t == CV_32U || t == CV_64S || t == CV_64U;
};
auto isFloatType = [](int t) {
return t == CV_32F || t == CV_64F || t == CV_16F || t == CV_16BF;
};
int out_type;
const bool baseIsInt = isIntegerType(inputs[0]);
const bool expIsInt = isIntegerType(inputs[1]);
const bool baseIsFloat = isFloatType(inputs[0]);
const bool expIsFloat = isFloatType(inputs[1]);
if ((baseIsInt && expIsInt) || (baseIsFloat && expIsFloat))
{
out_type = (inputs[0] == inputs[1]) ? inputs[0] : CV_32F;
}
else if (baseIsFloat != expIsFloat)
{
out_type = inputs[0];
}
else
{
out_type = CV_32F;
}
outputs.assign(1, out_type);
return;
}
@@ -766,8 +788,22 @@ public:
return;
}
int type_for_dispatch = op == OPERATION::WHERE ? outputs.front().type() : inputs.front().type();
typeDispatch(type_for_dispatch, inputs.size(), inputs, outputs);
std::vector<Mat> used_inputs = inputs;
if (op == OPERATION::POW) {
CV_Assert(used_inputs.size() == 2);
const int out_type = outputs[0].type();
if (used_inputs[0].type() != out_type || used_inputs[1].type() != out_type) {
Mat a_conv, b_conv;
used_inputs[0].convertTo(a_conv, out_type);
used_inputs[1].convertTo(b_conv, out_type);
used_inputs = {a_conv, b_conv};
helper.init(used_inputs, outputs);
CV_CheckTrue(helper.prepare_for_broadcast_op(), "NaryEltwiseLayer: Preparation for broadcasting failed");
}
}
int type_for_dispatch = (op == OPERATION::WHERE || op == OPERATION::POW) ? outputs.front().type() : used_inputs.front().type();
typeDispatch(type_for_dispatch, used_inputs.size(), used_inputs, outputs);
}
template<typename T, typename... Args>
@@ -801,7 +837,7 @@ public:
break;
}
case OPERATION::POW: {
auto pow = [] (const T& a, const T& b) { return std::pow(a, b); };
auto pow = [] (const T& a, const T& b) { return saturate_cast<T>(std::pow((double)a, (double)b)); };
binary_forward<T, T>(pow, std::forward<Args>(args)..., 1e5);
break;
}
@@ -944,6 +980,11 @@ public:
op != OPERATION::OR && op != OPERATION::XOR);
opDispatch<float>(std::forward<Args>(args)...);
break;
case CV_64F:
CV_Assert(op != OPERATION::BITSHIFT && op != OPERATION::AND &&
op != OPERATION::OR && op != OPERATION::XOR);
opDispatch<double>(std::forward<Args>(args)...);
break;
case CV_16S:
opDispatch<int16_t>(std::forward<Args>(args)...);
break;
modules/dnn/test/test_onnx_conformance_layer_filter__openvino.inl.hpp
+19 -19
View File
@@ -411,15 +411,15 @@ CASE(test_concat_3d_axis_negative_2)
CASE(test_concat_3d_axis_negative_3)
// no filter
CASE(test_constant)
// no filter
SKIP;
CASE(test_constant_pad)
// no filter
SKIP;
CASE(test_constantofshape_float_ones)
// no filter
SKIP;
CASE(test_constantofshape_int_shape_zero)
// no filter
CASE(test_constantofshape_int_zeros)
// no filter
SKIP;
CASE(test_conv_with_autopad_same)
#if SKIP_SET_1
SKIP_MYRIAD;
@@ -547,7 +547,7 @@ CASE(test_dynamicquantizelinear_min_adjusted)
CASE(test_dynamicquantizelinear_min_adjusted_expanded)
// no filter
CASE(test_edge_pad)
// no filter
SKIP;
CASE(test_einsum_batch_diagonal)
SKIP;
CASE(test_hardmax_axis_0)
@@ -911,13 +911,13 @@ CASE(test_lrn)
CASE(test_lrn_default)
// no filter
CASE(test_lstm_batchwise)
// no filter
SKIP;
CASE(test_lstm_defaults)
// no filter
SKIP;
CASE(test_lstm_with_initial_bias)
// no filter
SKIP;
CASE(test_lstm_with_peepholes)
// no filter
SKIP;
CASE(test_matmul_2d)
// no filter
CASE(test_matmul_3d)
@@ -1266,23 +1266,23 @@ CASE(test_pow_bcast_scalar)
CASE(test_pow_example)
// no filter
CASE(test_pow_types_float)
// no filter
SKIP;
CASE(test_pow_types_float32_int32)
// no filter
SKIP;
CASE(test_pow_types_float32_int64)
// no filter
SKIP;
CASE(test_pow_types_float32_uint32)
// no filter
SKIP;
CASE(test_pow_types_float32_uint64)
// no filter
SKIP;
CASE(test_pow_types_int)
// no filter
SKIP;
CASE(test_pow_types_int32_float32)
// no filter
SKIP;
CASE(test_pow_types_int32_int32)
// no filter
SKIP;
CASE(test_pow_types_int64_float32)
// no filter
SKIP;
CASE(test_pow_types_int64_int64)
SKIP;
CASE(test_prelu_broadcast)
@@ -1560,7 +1560,7 @@ CASE(test_reduce_sum_square_negative_axes_keepdims_random)
}
#endif
CASE(test_reflect_pad)
// no filter
SKIP;
CASE(test_relu)
// no filter
CASE(test_reshape_allowzero_reordered)
modules/dnn/test/test_onnx_conformance_layer_filter_opencv_classic_denylist.inl.hpp
+19
View File
@@ -120,3 +120,22 @@
"test_gridsample_reflection_padding",
"test_gridsample_zeros_padding",
"test_gridsample_nearest",
"test_edge_pad",
"test_lstm_batchwise",
"test_lstm_defaults",
"test_lstm_with_initial_bias",
"test_lstm_with_peepholes",
"test_pow_types_float",
"test_pow_types_float32_int32",
"test_pow_types_float32_int64",
"test_pow_types_float32_uint32",
"test_pow_types_float32_uint64",
"test_pow_types_int",
"test_pow_types_int32_float32",
"test_pow_types_int32_int32",
"test_pow_types_int64_float32",
"test_reflect_pad",
"test_constant",
"test_constant_pad",
"test_constantofshape_float_ones",
"test_constantofshape_int_zeros",
modules/dnn/test/test_onnx_conformance_layer_parser_denylist.inl.hpp
-19
View File
@@ -44,11 +44,7 @@
"test_compress_1", // ---- same as above ---
"test_compress_default_axis", // ---- same as above ---
"test_compress_negative_axis", // ---- same as above ---
"test_constant", // Issue::Wrong output
"test_constant_pad", // Issue:: Unkonwn error
"test_constantofshape_float_ones", // Issue::Parser::Weights are required as inputs
"test_constantofshape_int_shape_zero", // Issue::Parser::Weights are required as inputs
"test_constantofshape_int_zeros", // Issue::Parser::Weights are required as inputs
"test_convinteger_with_padding", // Issues::Layer::Can't create layer "onnx_node_output_0!y" of type "ConvInteger" in function 'getLayerInstance'
"test_convinteger_without_padding", //Issues::Layer::Can't create layer "onnx_node_output_0!y" of type "ConvInteger" in function 'getLayerInstance'
"test_convtranspose", // Issue::Parser::Weights are required as inputs
@@ -69,7 +65,6 @@
"test_dynamicquantizelinear_max_adjusted_expanded", // ---- same as above ---
"test_dynamicquantizelinear_min_adjusted", // ---- same as above ---
"test_dynamicquantizelinear_min_adjusted_expanded", // ---- same as above ---
"test_edge_pad", // Issue::Parser::Weights are required as inputs
"test_einsum_inner_prod", // Issue::Output shape does not match with reference
"test_elu_default_expanded_ver18",
"test_elu_example_expanded_ver18",
@@ -93,10 +88,6 @@
"test_loop11", // Issue::'Graph' is not supported in function 'getLayerParams'
"test_loop13_seq", // Issue::typeProto.has_tensor_type() in function 'populateNet'
"test_loop16_seq_none", // Issue::Failed to allocate 179812654996800 bytes in function 'OutOfMemoryError'
"test_lstm_batchwise", // Issues::Parser:: !name.empty() && constBlobs.count(name) == 1 in function 'parseLSTM'
"test_lstm_defaults", // ---- same as above ---
"test_lstm_with_initial_bias", // ---- same as above ---
"test_lstm_with_peepholes", // ---- same as above ---
"test_matmulinteger", // Issues::Layer does not exist. Can't create layer "onnx_node_output_0!Y" of type "MatMulInteger" in function 'getLayerInstance'
"test_momentum", // Issues::Layer does not exist. Can't create layer "onnx_node_output_0!X1_new" of type "ai.onnx.preview.training.Momentum" in function 'getLayerInstance'
"test_momentum_multiple", // ---- same as above ---
@@ -150,15 +141,6 @@
"test_optional_get_element_sequence", // ---- same as above ---
"test_optional_has_element", // Issue::typeProto.has_tensor_type() in function 'populateNet'
"test_optional_has_element_empty", // ---- same as above ---
"test_pow_types_float", // Issue:: Unsupported data type
"test_pow_types_float32_int32", // ---- same as above ---
"test_pow_types_float32_int64", // ---- same as above ---
"test_pow_types_float32_uint32", // ---- same as above ---
"test_pow_types_float32_uint64", // ---- same as above ---
"test_pow_types_int", // Issue:: Unsupported data type
"test_pow_types_int32_float32", // ---- same as above ---
"test_pow_types_int32_int32", // ---- same as above ---
"test_pow_types_int64_float32", // ---- same as above ---
"test_prelu_broadcast", // Issue::Parser:Blob slope not found in const blobs in function 'getBlob' (weights are required as inputs)
"test_prelu_example", // ---- same as above ---
"test_qlinearconv", // Issue::Parser: Blob x_scale not found in const blobs in function 'getBlob' (weights are required as inputs)
@@ -176,7 +158,6 @@
"test_reduce_sum_keepdims_random", // ---- same as above ---
"test_reduce_sum_negative_axes_keepdims_example",
"test_reduce_sum_negative_axes_keepdims_random", // ---- same as above ---
"test_reflect_pad", // Issue:: Parser: Blob shape not found in const blobs in function 'getBlob' (weights are required as inputs)
"test_reshape_allowzero_reordered", // incompatible type of input tensor #0 'data': CV_8UC1 given, CV_32FC1 expected in function 'setGraphInput'
"test_resize_downsample_scales_cubic", // Issue:: Parser: layer_id.find(node_proto.input(i)) == layer_id.end() in function 'parseResize'
"test_resize_downsample_scales_cubic_A_n0p5_exclude_outside", // ---- same as above ---