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[OV2.0] Preprocessing: support convert HWC->NCHW layout (#9540)

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* Initial implementation

* Template reference tests

* cpu & gpu tests for HWC -> NCHW conversion
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Mikhail Nosov authored and GitHub committed 2022-01-11 13:13:37 +03:00
1 parent 062523c9e1
commit bd3a996239
8 files changed
+347 -6
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docs/template_plugin/tests/functional/subgraph_reference/preprocess.cpp
+65
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@@ -430,6 +430,68 @@ static RefPreprocessParams convert_layout_nhwc_to_nchw() {
return res;
}
static RefPreprocessParams convert_layout_nhwc_to_nchw_fully_dynamic() {
RefPreprocessParams res("convert_layout_nhwc_to_nchw_fully_dynamic");
res.function = []() {
auto f = create_simple_function(element::u8, PartialShape::dynamic());
f->get_parameters()[0]->set_layout("NCHW");
auto p = PrePostProcessor(f);
p.input().tensor().set_layout("NHWC");
p.input().preprocess().convert_layout("NCHW");
p.build();
return f;
};
res.inputs.emplace_back(element::u8, Shape{1, 2, 2, 3}, std::vector<uint8_t>{1, 2, 3, // [H=0, W=0, RGB]
4, 5, 6, // [H=0, W=1]
7, 8, 9, // [H=1, W=0]
10, 11, 12}); // [H=1, W=1]
res.expected.emplace_back(Shape{1, 3, 2, 2}, element::u8, std::vector<uint8_t>{1, 4, 7, 10, // R
2, 5, 8, 11, // G
3, 6, 9, 12}); // B
return res;
}
static RefPreprocessParams convert_layout_hwc_to_nchw() {
RefPreprocessParams res("convert_layout_hwc_to_nchw");
res.function = []() {
auto f = create_simple_function(element::f32, {Dimension::dynamic(), 3, 2, 2});
auto p = PrePostProcessor(f);
p.input().tensor().set_layout("HWC").set_element_type(element::u8);
p.input().model().set_layout("NCHW");
p.build();
return f;
};
res.inputs.emplace_back(Shape{2, 2, 3}, element::u8, std::vector<uint8_t>{1, 2, 3, // [H=0, W=0, RGB]
4, 5, 6, // [H=0, W=1]
7, 8, 9, // [H=1, W=0]
10, 11, 12}); // [H=1, W=1]
res.expected.emplace_back(Shape{1, 3, 2, 2}, element::f32, std::vector<float>{1, 4, 7, 10, // R
2, 5, 8, 11, // G
3, 6, 9, 12}); // B
return res;
}
static RefPreprocessParams convert_layout_hwc_to_nchw_fully_dynamic() {
RefPreprocessParams res("convert_layout_hwc_to_nchw_fully_dynamic");
res.function = []() {
auto f = create_simple_function(element::f32, PartialShape::dynamic());
auto p = PrePostProcessor(f);
p.input().tensor().set_layout("HWC").set_element_type(element::u8);
p.input().model().set_layout("NCHW");
p.build();
return f;
};
res.inputs.emplace_back(element::u8, Shape{2, 2, 3}, std::vector<uint8_t>{1, 2, 3, // [H=0, W=0, RGB]
4, 5, 6, // [H=0, W=1]
7, 8, 9, // [H=1, W=0]
10, 11, 12}); // [H=1, W=1]
res.expected.emplace_back(Shape{1, 3, 2, 2}, element::f32, std::vector<float>{1, 4, 7, 10, // R
2, 5, 8, 11, // G
3, 6, 9, 12}); // B
return res;
}
static RefPreprocessParams convert_layout_nhwc_to_net_no_tensor_shape() {
RefPreprocessParams res("convert_layout_nhwc_to_net_no_tensor_shape");
res.function = []() {
@@ -1056,10 +1118,13 @@ std::vector<RefPreprocessParams> allPreprocessTests() {
resize_to_network_width_height(),
resize_to_specified_width_height(),
convert_layout_nhwc_to_nchw(),
convert_layout_nhwc_to_nchw_fully_dynamic(),
convert_layout_nhwc_to_net_no_tensor_shape(),
convert_layout_by_dims(),
convert_layout_by_dims_multi(),
convert_layout_by_dims_multi_layout(),
convert_layout_hwc_to_nchw(),
convert_layout_hwc_to_nchw_fully_dynamic(),
resize_and_convert_layout(),
convert_color_nv12_to_bgr_two_planes(),
convert_color_nv12_single_plane(),